WO2022024259A1 - Data correction method and data correction device - Google Patents
Data correction method and data correction device Download PDFInfo
- Publication number
- WO2022024259A1 WO2022024259A1 PCT/JP2020/029047 JP2020029047W WO2022024259A1 WO 2022024259 A1 WO2022024259 A1 WO 2022024259A1 JP 2020029047 W JP2020029047 W JP 2020029047W WO 2022024259 A1 WO2022024259 A1 WO 2022024259A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- data
- vehicle
- measurement
- traveling
- measurement time
- Prior art date
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
- G01S19/49—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system whereby the further system is an inertial position system, e.g. loosely-coupled
Definitions
- the present invention relates to a data correction method and a data correction device for correcting data related to measurement conditions when measuring point cloud data.
- FIG 16 shows a use case (for example, non-use case) proposed by mmWave Networks in TIP (Telecom InfraProjcet) (main members: Facebook, Deutsche Telecom, Intel, NOKIA, etc.), which is a consortium that promotes open specifications of communication network equipment in general. It is a diagram which has been partially modified and schematicized with reference to Patent Documents 1 to 3).
- mmWave Networks is one of the TIP project groups, aiming to build networks faster and cheaper than laying optical fibers using unlicensed millimeter-wave radio.
- terminal station devices (hereinafter referred to as “terminal stations”) 840 to 844 and electric poles 821 to 826 installed on the respective wall surfaces of the building.
- the installed base station devices (hereinafter referred to as “base stations”) 830 to 834 are devices called mmWave DN (Distribution Node).
- the base stations 830 to 834 are connected to the communication device provided in the station building (Fiber PoP (Point of Presence)) 850, 851 by optical fibers 900, 901. This communication device is connected to the communication network of the provider. Between the terminal stations 840 to 844 and the base stations 830 to 834 (hereinafter, also referred to as "between both stations"), mmWaveLink, that is, millimeter wave radio is performed. In FIG. 16, the millimeter-wave radio link is shown by a dashed line.
- Base stations 830 to 834 are installed on utility poles 821 to 826, terminal stations 840 to 844 are installed on the wall of a building, and base stations 830 to 834 and terminal stations 840 to communicate in a form in which both stations are communicated by millimeter wave radio. Selecting a candidate position for installing the 844 is called station design (hereinafter also referred to as "station design").
- FIG. 17 shows the schematic configuration of the MMS (Mobile Mapping System) that collects the point cloud data used for the station placement design of the millimeter wave station, the types of data collected by the MMS, and the station placement support tool that uses the point cloud data. It is a figure which showed the displayed screen 500.
- the MMS is, for example, a vehicle 700 including a laser radar 702, an antenna 703 that receives radio waves from a GPS (Global Positioning System), and a measuring device 701. While the vehicle 700 is traveling, the laser radar 702 irradiates the surroundings with laser light at each measurement time. The laser radar 702 measures the time until the reflected light returns from the measurement target such as a building existing in the surroundings, and calculates the distance to the measurement target based on the measured time.
- the measuring device 701 generates point cloud data by recording the distance to the object to be measured at each measurement time and the irradiation direction of the laser beam.
- the measuring device 701 receives radio waves from a plurality of GPS satellites 600-1 and 600-2 at each observation time.
- the measuring device 701 detects the position of the vehicle 700 for each observation time based on the data superimposed on the received radio wave.
- the measuring device 701 generates the traveling locus data 711 from the history of the position of the vehicle 700 for each detected observation time.
- the measuring device 701 estimates the position, speed, and traveling direction of the vehicle 700 for each measurement time from the generated travel locus data 711. Next, the measuring device 701 calculates the irradiation position of the laser radar 702 in the three-dimensional space from the estimated position of the vehicle 700. Then, the measuring device 701 calculates the direction in which the laser radar 702 is facing from the traveling direction of the vehicle 700. Based on the detected irradiation position of the laser radar 702, the direction in which the laser radar 702 is facing, and the point cloud data, the coordinates of each point included in the point cloud data in the three-dimensional space can be specified. ..
- the point group data at the measurement time is determined.
- a reliability index "high” indicating that the degree of reliability is high is given to the data, and the data is classified as point group data (type A) 712.
- the measuring device 701 determines that the vehicle 700 is not traveling at a constant speed or is not traveling straight based on the estimated speed and traveling direction of the vehicle 700 at each measurement time, the measurement is performed.
- a reliability index "low” indicating that the degree of reliability is low is given to the point group data at the time, and the point group data (type B) 713 is classified.
- the vehicle 700 When the vehicle 700 is not traveling at a constant speed, for example, it is accelerating or decelerating, and when the vehicle 700 is not traveling straight, for example, it is traveling in a curved manner including a right / left turn. If there is.
- the reason why the reliability index "low” is given is that the position, speed, and estimation accuracy of the traveling direction of the vehicle 700 are lowered when the vehicle is accelerating, decelerating, or traveling in a curved manner including right / left turn. .. If the point cloud data is not reliable and cannot be used instead of the reliability index "low", the reliability index "not” may be given.
- the reliability index is an index showing the priority of use when using the point cloud data in the station support tool. For example, the point cloud data to which "none” is given is not used, and when the point cloud data to which "low” is given is used, "high” indicating the same position is given. It is used when other point cloud data does not exist, and processing is performed so that the point cloud data to which "high” is given is preferentially used.
- the station station support tool uses the point cloud data to detect the presence or absence of a line-of-sight between the position where the base station 501 shown on the screen 500 is installed and the position where each of the terminal stations 511 to 514 is installed. For example, the station support tool sets a line-of-sight detection line between the position of the base station 501 and the position where each of the terminal stations 511 to 514 is installed, and point cloud data indicating the shape of the building is displayed on the line-of-sight detection line. The presence or absence of a line of sight is detected depending on whether or not it exists.
- the station support tool displays map data on the screen 500.
- the area surrounded by the solid line indicated by the reference numerals 521 and 522 is a section in which a building or the like shown in the map data exists, and the blank space between the sections is a road.
- the station station support tool displays the travel locus 540 of the vehicle 700 on the map data based on the travel locus data 711.
- a region having a certain width along the solid arrow indicated by reference numerals 531,532 (hereinafter referred to as “region A”) is a place where the point cloud data (type A) 712 exists. ..
- region B a region having a certain width along the dotted line indicated by reference numeral 533, 534
- the screen 500 shows a portion of the pattern of the plurality of areas A and a portion of the pattern of the plurality of areas B.
- the locus indicated by the traveling locus data 711 is a straight line.
- the locus indicated by the traveling locus data 711 is bent at the portion of the pattern in the region B.
- the reason for assigning the confidence index "low” or “none” to the point cloud data classified as the point cloud data (type B) 713 shown in FIG. 17 is acceleration, deceleration, or right. This is because the position, speed, and estimation accuracy of the traveling direction of the vehicle 700 are lowered when the vehicle is traveling in a curved manner including a left turn. Specific examples of this reason are shown in FIGS. 18 and 19.
- FIG. 18 is a view of the road 550 and the sidewalk 570, which are in the vicinity of the road in one direction of the straight two-lane road on one side, from the sky.
- the line indicated by reference numeral 552 is a center line indicating a boundary with an oncoming lane.
- the double-lined arrow indicated by the reference numeral 541 is a locus on which the vehicle 700, which is an MMS, has traveled, and is hereinafter referred to as a travel locus 541.
- the vehicle 700 is traveling in the right direction indicated by the arrow of the traveling locus 541.
- the vehicle 750 is stopped near the sidewalk 570.
- the overtaking lane 562 temporarily crosses the line 551 that separates the traveling lane 561 and the overtaking lane 562.
- a driving operation is performed in which the vehicle travels and then returns to the traveling lane 561.
- the traveling locus 541 of the vehicle 700 is in a bent state at two places.
- the plurality of dotted lines shown along the traveling locus 541 are laser irradiation lines indicating the irradiation direction of the laser light emitted by the laser radar 702 mounted on the vehicle 700 at each measurement time.
- the laser irradiation line is perpendicular to the traveling direction. It becomes a regular arrangement parallel to each other at equal intervals.
- the laser irradiation lines are not parallel but disturbed. Will occur, and if the speed is not constant, it will not be evenly spaced.
- FIG. 19 is a diagram showing a travel locus 542 in which a vehicle 700, which is an MMS, travels at an intersection where roads with one lane on each side intersect. Similar to FIG. 18, in FIG. 19, the laser irradiation line for each measurement time is shown by a dotted line.
- the lines indicated by reference numerals 580-1 and 580-2 are center lines, and the lines indicated by reference numerals 581-1 to 581-4 are lines indicating the boundary between the roadway and the roadside zone.
- the vehicle 700 as indicated by the arrow of the traveling locus 542, the vehicle travels upward from the lower part of FIG. 19, approaches the center line 580-1 side before turning right at the intersection, and then turns right at the intersection and goes straight to the right. The driving operation is being performed.
- the traveling locus 542 of the vehicle 700 is not parallel but turbulent in the section 403 approaching the center line 580-1 side and in the section 404 turning right at the intersection. If it occurs and becomes irregular, and if it is not constant velocity, it will not be evenly spaced.
- the vehicle 700 is traveling straight at a constant speed, so that the laser irradiation lines are perpendicular to the traveling direction and are arranged in a regular arrangement parallel to each other at equal intervals.
- the laser irradiation lines are not parallel when the traveling lane is changed, or when the vehicle does not go straight, such as when turning right or left at an intersection, and when the speed is not constant, the laser irradiation lines are not evenly spaced.
- the reliability level is lowered, so that the reliability index "low” or the reliability index "none" is given.
- Such a phenomenon that the laser irradiation line is disturbed is not limited to the horizontal plane shown in FIGS. 18 and 19, and for example, the vehicle 700 climbs a slope from a flat ground, returns from a slope to a flat ground, or has irregularities. It also occurs when driving on the road.
- an object of the present invention is to provide a technique capable of making available point cloud data whose reliability is lowered due to disturbance of a laser irradiation line.
- One aspect of the present invention is the point group when the laser radar device mounted on the moving body measures the distance to the object to be measured by irradiating the laser light at each measurement time and generates point group data.
- the collected data generated in association with the data and indicating the measurement conditions of the laser radar device estimated from the horizontal plane position data indicating the position of the moving object on the horizontal plane obtained at each observation time is corrected.
- This is a data correction method for acquiring horizontal plane position data with higher accuracy than the horizontal plane position data obtained at each observation time, or vertical plane position data indicating the position of the moving body on the vertical plane.
- the movement trajectory data generation data generation step and the movement For each measurement time, based on the movement locus analysis step that analyzes the locus data and estimates the position and movement state of the moving body at each measurement time, and the position and movement state of the moving body at each measurement time. It is a data correction method including a measurement condition generation step for generating measurement condition data indicating the measurement conditions of the laser radar device, and a correction processing step for correcting the collected data based on the measurement condition data.
- One aspect of the present invention is the point group when the laser radar device mounted on the moving body measures the distance to the object to be measured by irradiating the laser light at each measurement time and generates point group data.
- the collected data generated in association with the data and indicating the measurement conditions of the laser radar device estimated from the horizontal plane position data indicating the position of the moving object on the horizontal plane obtained at each observation time is corrected.
- This is a data correction device that acquires horizontal plane position data with higher accuracy than the horizontal plane position data obtained at each observation time, or vertical plane position data indicating the position of the moving body on the vertical plane.
- the movement locus data generation unit that generates the movement locus data indicating the movement locus of the moving body based on the acquired high-precision horizontal plane position data or the vertical plane position data, and the movement locus data.
- the movement locus analysis unit that estimates the position and the moving state of the moving body at each measurement time, and the movement locus analysis unit that estimates the position and the moving state of the moving body at each measurement time, and the said at each measurement time based on the position and the moving state of the moving body at each measurement time.
- It is a data correction device including a measurement condition generation unit that generates measurement condition data indicating measurement conditions of a laser radar device, and a correction processing unit that corrects the collected data based on the measurement condition data.
- FIG. 1st Embodiment It is a block diagram which shows the structure of the point cloud data collection system in 1st Embodiment. It is a figure which shows the data which the storage part of 1st Embodiment stores. It is a figure which showed the method of estimating the position and the traveling direction of a vehicle for each measurement time from the traveling locus data by the traveling locus analysis unit of 1st Embodiment. It is a figure which showed the method of obtaining the position and the traveling direction of a vehicle by applying the traveling state data to the position of the vehicle estimated in FIG. It is a figure for demonstrating the estimation accuracy of a laser irradiation direction when only GPS observation data is used.
- FIG. 1 is a block diagram showing a configuration of a point cloud data collection system ⁇ according to the first embodiment.
- the point cloud data collection system ⁇ includes a vehicle 1 equipped with a point cloud data collection device 2, a plurality of GPS satellites 10-1, 10-2, and a quasi-zenith satellite 11.
- the vehicle 1 is, for example, a moving body such as an automobile, and corresponds to the above-mentioned MMS.
- FIG. 1 two GPS satellites 10-1 and 10-2 are shown as an example, but in reality, more than two GPS satellites are in operation.
- one quasi-zenith satellite 11 is shown as an example, but in the future, a plurality of quasi-zenith satellites 11 are scheduled to be operated. Since the line-of-sight state changes depending on the position where the vehicle 1 is traveling, the number of GPS satellites 10-1, 10-2 and the quasi-zenith satellite 11 that can receive radio waves while the vehicle 1 is traveling changes.
- the data superimposed on the radio waves received from the GPS satellites 10-1 and 10-2 is used.
- the outline of the quasi-zenith satellite 11 will be described.
- QZSS Quadsi-Zenith Satellite System
- the accuracy is higher than when GPS is used. Attempts have been made to detect the position.
- Non-Patent Document 4 shows an example of an experimental system configuration for a GPS complementary function effect.
- a receiver corresponding to the quasi-zenith satellite 11 is mounted on the MMS, which is a mobile positioning device, and the reference MMS travels along with the reception logs of the quasi-zenith satellite 11 and GPS satellites 10-1 and 10-2. Collecting trajectories.
- the "complementary" function was realized by performing the positioning calculation by adding the information from the quasi-zenith satellite 11 to the GPS satellites 10-1 and 10-2 by the experimental system, from the quasi-zenith satellite 11. The verification of the improvement effect of the mobile body positioning performance in the urban area by the addition of the information of is shown.
- Non-Patent Document 5 On page 16 of Non-Patent Document 5, an example is shown in which a positioning terminal is mounted on an MMS, real-time mobile positioning is performed on a forest road, and a centimeter-class positioning reinforcement for use verification is conducted. Results with a FIX rate of 79% and a positioning accuracy of 2.4 cm were obtained, indicating that the results are good.
- the accuracy of positioning using only GPS satellites 10-1 and 10-2 is at most several meters to several tens of meters.
- an accuracy of 2.4 cm can be obtained in a good environment for traveling on a forest road shown in Non-Patent Document 5.
- the point cloud data collecting device 2 includes a laser radar device 21, a satellite radio wave receiving antenna 22, an information receiving unit 23, a traveling state measuring unit 24, a storage unit 25, a collected data generation unit 26, and a data correction unit 3. To prepare for.
- the laser radar device 21 can irradiate the laser beam by rotating the irradiation hole of the laser beam 360 ° around the rotation axis, for example, and the surface formed by the irradiated laser beam and the rotation axis are perpendicular to each other. It is configured to intersect with.
- the direction in which the rotation axis of the laser radar device 21 faces is referred to as the direction of the laser radar device 21.
- the laser radar device 21 is fixedly mounted on the top of the vehicle 1 so that the surface formed by the irradiated laser beam is perpendicular to the traveling direction of the vehicle 1. Therefore, as shown in FIG. 1, the direction of the laser radar device 21 is the direction indicated by the arrow of reference numeral 4, and is 180 ° opposite to the traveling direction of the vehicle 1.
- the laser radar device 21 irradiates the surroundings with laser light at each measurement time.
- the laser radar device 21 measures the time until the reflected light returns from the measurement target such as a building existing in the surroundings, and calculates the distance to the measurement target based on the measured time.
- the interval of the measurement time is a constant time, for example, about 0.005 seconds.
- the laser radar device 21 rotates at a rotation speed of, for example, about 200 [Hz] during the interval of the measurement time.
- the laser radar device 21 generates point cloud data 43 in association with the distance to the object to be measured at each measurement time and the irradiation direction of the laser beam, and writes the generated point cloud data 43 in the storage unit 25.
- the irradiation hole of the laser beam rotates clockwise, for example, in the direction of the laser radar device 21, the direction in which the irradiation angle of the laser beam "0 °" is directed toward the sky, that is, the direction directly above. Then, the irradiation angle of the laser beam increases clockwise, and the direction from the front surface to the back surface of FIG. 1, that is, the left direction with respect to the traveling direction of the vehicle 1 becomes "90 °".
- the direction toward the ground, that is, the direction directly below is "180 °”
- the direction from the back surface to the front surface of FIG. 1, that is, the direction to the right of the traveling direction of the vehicle 1 is "270 °".
- the current high-precision laser radar device 21 can measure measurement positions of about 1 million points (1 million points / second) per second.
- the laser radar device 21 has 720,000 points per second (720,000 / sec ( ⁇ 200 [Hz] ⁇ 360 [°] ⁇ 0.1 [°]]. )) It shall be possible to measure the measurement position.
- the satellite radio wave receiving antenna 22 receives radio waves from GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11.
- the information receiving unit 23 corresponds to a receiver or a positioning terminal of the GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11.
- the information receiving unit 23 detects the data superimposed on the radio waves received from the GPS satellites 10-1 and 10-2 by the satellite radio wave receiving antenna 22 at each observation time, and the vehicle 1 at the observation time from the detected data.
- the position of the GPS observation data 40 is calculated, and the calculated position of the vehicle 1 is associated with the observation time and written in the storage unit 25 as GPS observation data 40.
- the information receiving unit 23 detects the data superimposed on the radio waves received from the quasi-zenith satellite 11 by the satellite radio wave receiving antenna 22 at each observation time, and calculates the position of the vehicle 1 at the observation time from the detected data. , The calculated position of the vehicle 1 and the observation time are associated with each other and written in the storage unit 25 as quasi-zenith satellite observation data 41.
- the interval of the observation time for receiving radio waves from the GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11 is a fixed time, for example, 1 second.
- the traveling state measuring unit 24 is connected to, for example, a vehicle speed sensor that detects the speed from the rotation speed of the tire of the vehicle 1 and a steering sensor that detects the steering angle of the steering of the vehicle 1.
- the vehicle speed sensor and the steering sensor are provided inside the vehicle 1.
- the traveling state measuring unit 24 measures the speed of the vehicle 1 at each measurement time based on the data obtained from the vehicle speed sensor.
- the traveling state measuring unit 24 measures the steering angle of the steering at each measurement time based on the data obtained from the steering sensor.
- the traveling state measuring unit 24 calculates the traveling direction of the vehicle 1 on the horizontal plane for each measurement time from the steering angle of the steering.
- the traveling state measuring unit 24 includes a traveling state data 42-1 indicating the speed of the vehicle 1 for each measurement time and a traveling direction data 42-2 indicating the traveling direction of the vehicle 1 on the horizontal plane for each measurement time. Generate data 42. The traveling state measuring unit 24 writes the generated traveling state data 42 in the storage unit 25.
- the storage unit 25 stores the GPS observation data 40, the quasi-zenith satellite observation data 41, the traveling state data 42, and the point cloud data 43 described above.
- the storage unit 25 stores the collected data 44 generated by the collected data generation unit 26 based on the data stored in the storage unit 25.
- the collected data generation unit 26 determines the position of the vehicle 1 on the horizontal plane at each measurement time based on the GPS observation data 40 stored by the storage unit 25, the vehicle speed data 42-1 and the traveling direction data 42-2. , Estimate the speed, the traveling direction on the horizontal plane, and the measurement position interval.
- the position of the vehicle 1 on the horizontal plane is, for example, a position indicated by two-dimensional coordinates indicated by latitude and longitude.
- the measurement position interval at a certain measurement time is the distance between the position of the vehicle 1 at the certain measurement time and the position of the vehicle 1 at the measurement time immediately before the certain measurement time.
- the collected data generation unit 26 has three dimensions of the laser radar device 21 based on the position of the vehicle 1 on the horizontal plane at each estimated measurement time and the positional relationship of the laser radar device 21 fixedly installed in the vehicle 1. Calculate the position in space.
- the collected data generation unit 26 sets the direction 180 ° opposite to the traveling direction of the vehicle 1 on the horizontal plane at each estimated measurement time as the direction on the horizontal plane of the laser radar device 21 at each measurement time.
- the laser radar device 21 is mounted by fixing the surface formed by the irradiated laser beam to the top of the vehicle 1 so as to be perpendicular to the traveling direction of the vehicle 1. Therefore, since the rotation axis of the laser radar device 21 is always constant with respect to the horizontal plane, the collected data generation unit 26 always sets the direction of the laser radar device 21 on the vertical plane to "0 °".
- the collected data generation unit 26 includes each of the measurement times, the position of the laser radar device 21 corresponding to each of the measurement times, the direction of the laser radar device 21 corresponding to each of the measurement times on the horizontal plane and the vertical plane, and the measurement time.
- the collected data 44 is generated by associating the measurement position interval corresponding to each of the above, the speed of the vehicle 1 corresponding to each of the measurement times, and the traveling direction of the vehicle 1 corresponding to each of the measurement times.
- the traveling direction of the vehicle 1 is a direction specified by a horizontal component and a vertical component. However, in the first embodiment, since only the traveling direction of the vehicle 1 on the horizontal plane is obtained, the vertical component is obtained. Will not be included.
- the collected data generation unit 26 writes the generated collected data 44 to the storage unit 25.
- the collected data generation unit 26 assigns a reliability index to each of the point cloud data 43 for each measurement time stored in the storage unit 25.
- the data correction unit 3 includes a travel locus data generation unit 31, a travel locus analysis unit 32, a measurement condition generation unit 33, a road traffic information acquisition unit 34, a travel locus data normality determination unit 35, and a correction processing unit 36.
- the travel locus data generation unit 31 generates travel locus data indicating the travel locus of the vehicle 1 based on the GPS observation data 40 stored in the storage unit 25 and the quasi-zenith satellite observation data 41.
- the travel locus data generation unit 31 is an aspect of the travel locus data generation unit.
- the travel locus analysis unit 32 is based on the travel locus data generated by the travel locus data generation unit 31, the position and speed of the vehicle 1 on the horizontal plane at each measurement time, the travel direction on the horizontal plane, and the measurement position. Estimate the interval.
- the traveling locus analysis unit 32 includes estimated position data indicating the estimated position of the vehicle 1 on the horizontal plane, estimated measurement position interval data indicating the estimated measurement position interval, estimated speed of the vehicle 1, and the estimated vehicle 1 for each measurement time. Generates estimated running state data including the running direction on the horizontal plane.
- the traveling locus analysis unit 32 is an aspect of the traveling locus analysis unit.
- FIG. 3 a method for estimating the position and speed of the vehicle 1 on the horizontal plane, the traveling direction on the horizontal plane, and the measurement position interval for each measurement time by the traveling locus analysis unit 32. explain.
- the curve of the double line arrow indicated by reference numeral 5 is shown by the travel locus data generated by the travel locus data generation unit 31 based on the GPS observation data 40 and the quasi-zenith satellite observation data 41. It is a running track of.
- the positions of the circles indicated by the symbols PJ -1 , PJ , PJ + 1 , and PJ + 2 are the positions of the vehicle 1 at the observation time indicated by the GPS observation data 40 and the quasi-zenith satellite observation data 41.
- the travel locus data generation unit 31 obtains a curve 5 passing through PJ -1 , PJ , PJ + 1 , and PJ + 2 as a line that approximates the travel locus of the vehicle 1, and obtains data indicating the obtained curve 5 as travel locus data. Generate as.
- the positions of the N irradiating laser beams are designated as pj (1) , pj (2) , ..., pj (i) , ..., Pj (N) . do.
- the final p j (N) corresponds to P J + 1 .
- the traveling locus analysis unit 32 considers the front-back distance between P J and P J + 1 , that is, the length between P J-1 and P J , and the length between P J + 1 and P J + 2 .
- PJ to PJ + 1 are divided into N pieces, and N-1 pieces of pj (1) , pj (2) , ..., pj (i) , ..., pj (N-1) Find the position.
- the length between PJ -1 and PJ + 1 is shorter than the length between PJ -1 and PJ + 2 and the length between PJ + 1 and PJ + 2. Therefore, in the traveling locus analysis unit 32, the distance between both ends is larger than the distance between the central parts, depending on the length between P J-1 and P J and the length between P J + 1 and P J + 2 .
- the positions of N-1 p j (1) , p j (2) , ..., p j (i) , ..., p j (N-1) are obtained by dividing them so as to be long.
- the traveling locus analysis unit 32 sets the respective positions of p j (1) , p j (2) , ..., p j (i) , ..., p j (N-1) , and P J + 1 from P J to P J + 1. Estimated position data for each of N measurement times is used, and the length between each is generated as estimated measurement position interval data for each of N measurement times.
- the traveling locus analysis unit 32 generates a vector connecting P J and p j (1) , and obtains the direction of the generated vector as the traveling direction of the vehicle 1 in p j (1) .
- the traveling locus analysis unit 32 divides the length of the generated vector by the difference between the measurement time in PJ and the measurement time in pj (1) , that is, the measurement time interval, in pj (1) . Obtained as the speed of vehicle 1.
- the traveling locus analysis unit 32 generates similar vectors for each of p j (2) , ..., p j (i) , ..., p j (N-1) , and P J + 1 , and p j (2).
- the traveling direction of the vehicle 1 and the speed of the vehicle 1 at each position are obtained.
- the traveling locus analysis unit 32 determines the combination of the traveling direction and the speed at each position of p j (2) , ..., p j (i) , ..., p j (N-1) , and P J + 1 .
- the speed of the vehicle 1 is 60 [km / hour]
- the speed per second is 1666.7 [cm / second].
- the interval between the measurement times of the laser radar device 21 is, for example, about 0.005 seconds.
- vehicle 1 moves about 8.3 [cm] ( ⁇ 1666.7 ⁇ 0.005).
- the interval between the observation times of the GPS observation data 40 and the quasi-zenith satellite observation data 41 is 1 second, so that there are 200 measurement times in 1 second.
- the accuracy of positioning when both the GPS observation data 40 and the quasi-zenith satellite observation data 41 are used is about a dozen centimeters to a few centimeters.
- the position of the vehicle 1 at each measurement time can be accurately estimated with high probability.
- the accuracy of positioning when only the GPS observation data 40 is used is at most several meters to several tens of meters.
- An error of several meters to several tens of meters is a non-negligible error compared to the observation time interval, that is, 1666.7 [cm] in which the vehicle 1 moves in one second, and the position of the vehicle 1 can be estimated accurately. It is assumed that it cannot be done.
- the travel locus analysis unit 32 compares the estimated travel state data at a certain measurement time with the travel state data 42 stored in the storage unit 25 corresponding to the measurement time, and the difference in speed is within a predetermined range. Moreover, when the difference in the traveling direction is within a predetermined range, the traveling state data 42 is used to perform a process of improving the accuracy of the estimated position data, the estimated measurement position interval data, and the estimated traveling state data.
- the predetermined range for the difference in speed and the predetermined range for the difference in the traveling direction are, for example, the speed and the traveling direction of the vehicle 1 indicated by the traveling state data 42, and the estimated traveling state data.
- the traveling state data 42 can be used for processing for improving the accuracy of the estimated position data, the estimated measurement position interval data, and the estimated running state data.
- FIG. 4 is a diagram showing a vector obtained by correcting the vector for specifying the position, speed, and traveling direction of the vehicle 1 shown in FIG. 3 by the vehicle speed data 42-1 and the traveling direction data 42-2 for each measurement time. ..
- each vector is delicately reflected in the left-right direction, reflecting the delicate accelerator operation, brake operation, and steering wheel operation. Change.
- the traveling locus analysis unit 32 generates highly accurate estimated position data and estimated measurement position by generating estimated position data, estimated measurement position interval data, and estimated traveling state data again from each of the vectors shown in FIG. Interval data and estimated running state data will be obtained.
- the measurement condition generation unit 33 is the measurement condition of the laser radar device 21 at the measurement time based on the estimated position data for each measurement time generated by the travel locus analysis unit 32, the estimated measurement position interval data, and the estimated travel state data. Generate measurement condition data indicating.
- the road traffic information acquisition unit 34 is, for example, a car navigation device, and acquires road traffic information related to the road on which the vehicle 1 is traveling.
- the travel locus data normality determination unit 35 receives a normality determination instruction signal including the measurement time and the estimated position data of the vehicle 1 at the measurement time, the road traffic information acquired from the road traffic information acquisition unit 34 and the normality.
- the vehicle 1 is the GPS satellite 10-1, 10 in the tunnel or under the elevated at the measurement time included in the normality determination instruction signal.
- -It is determined whether or not the travel locus data is normal based on whether or not the vehicle exists at a position where radio waves cannot be normally received from -2 and the quasi-zenith satellite 11.
- the correction processing unit 36 corrects the collected data 44 stored in the storage unit 25 based on the measurement condition data generated by the measurement condition generation unit 33.
- the correction processing unit 36 corrects the reliability index given to the point cloud data 43 stored in the storage unit 25.
- FIG. 5 is an enlarged view of a part of the figure shown in FIG. 18, and the same components as those in FIG. 18 are designated by the same reference numerals.
- the traveling locus 541 indicates the traveling locus of the vehicle 1.
- the traveling locus 541 is generated by the collected data generation unit 26 drawing a line passing through the position of the vehicle 1 for each observation time obtained from the GPS observation data 40, and drawing an approximate curve for the bent portion. Generated.
- the collected data generation unit 26 uses the vehicle speed data 42-1 and the traveling direction data 42-2 in addition to the GPS observation data 40 on the horizontal plane of the vehicle 1 at each measurement time. Estimate the position, speed, running direction on the horizontal plane, and measurement position interval.
- the collected data generation unit 26 uses only the GPS observation data 40 to position the vehicle 1 on the horizontal plane and on the horizontal plane for each measurement time.
- An example of estimating the traveling direction of is shown.
- the plurality of dotted lines shown along the traveling locus 541 indicate the irradiation direction of the laser beam actually irradiated by the laser radar device 21 mounted on the vehicle 1 at each measurement time. It is a line, and the corresponding measurement times t0 to t20 are attached to each of the laser irradiation lines.
- the laser irradiation lines shown by the dotted lines are at equal intervals, so that the collected data generation unit 26 uses the GPS observation data based on the difference between the observation time and the measurement time. From 40, the position of the vehicle 1 at the measurement time can be accurately estimated.
- the positions 71, 72, 73 of the vehicle 1 (hereinafter, the position 71 of the vehicle 1 is referred to as the vehicle position 71) are the laser irradiation lines 81, 82, 83 and the traveling locus 541, which are the positions where the laser light is actually irradiated. This is an example in which the collected data generation unit 26 can accurately estimate the position of the vehicle 1 because it coincides with the intersection with the above.
- the accuracy of positioning specified by the GPS observation data 40 that is, the error of the specified position is several meters to several tens of meters as described above.
- the vehicle 1 is traveling at a speed of 60 [km / hour] and the measurement time interval is 0.005 seconds as described above, the vehicle 1 is during the measurement time interval. Move about 8.3 [cm] to.
- the moving distance of about 8.3 [cm] is considerably shorter than the distance of several meters to several tens of meters.
- the collected data generation unit 26 generates a vector having a length of about several hundred to one thousand times the latest measurement position interval, starting from the estimated position of the vehicle 1.
- FIG. 5 shows an example of generating a vector having a length of three times instead of several hundred to one thousand times so that it can be illustrated and explained.
- the collected data generation unit 26 estimates the position of the vehicle 1 at the measurement time t5 corresponding to the laser irradiation line 85, for example, the vehicle position 71 at the measurement time t1 four times before the estimation and the vehicle position 71 three times before.
- the speed of the vehicle 1 at the vehicle position 72 is calculated based on the vehicle position 72 at the measurement time t2 of.
- the unit time of the speed calculated by the collected data generation unit 26 is the interval of the measurement time.
- the collected data generation unit 26 generates a vector V85 obtained by triple the calculated speed along the travel locus 541 starting from the vehicle position 72.
- the collected data generation unit 26 estimates the position which is the terminal position of the generated vector V85 as the position of the vehicle 1 at the measurement time t5, that is, the vehicle position 75. Further, the collected data generation unit 26 sets the traveling direction of the vehicle 1 at the measurement time t5 as the direction of the vector V85.
- the vehicle position 75 estimated by the collected data generation unit 26 as the position of the vehicle 1 at the measurement time t5 is the actual position.
- the position is different from the intersection of the laser irradiation line 85 and the traveling locus 541, which is the position where the laser beam is irradiated at the measurement time t5, and there is a difference indicated by the bidirectional arrow.
- the laser irradiation line corresponding to the estimated position of the vehicle 1 is shown by a alternate long and short dash line.
- the collected data generation unit 26 repeatedly generates a vector such as the above vector V85 starting from the position of the latest observation time, and estimates the position and the traveling direction of the vehicle 1 for each measurement time. Using this method, when the vehicle 1 is traveling at a constant speed and traveling straight, the collected data generation unit 26 accurately estimates the position of the vehicle 1 as in the vehicle positions 71, 72, 73. be able to. On the other hand, when the vehicle 1 starts decelerating, accurate estimation cannot be performed, and the vehicle positions 74, 75, 76 estimated at the measurement times t4, t5, t6 and the vehicle 1 actually irradiated with the laser beam. There will be a deviation from the position of.
- the laser irradiation line corresponding to the estimated position of the vehicle 1 indicated by the alternate long and short dash line is the laser irradiation line 84, 85, which indicates the actual laser irradiation direction. It will be parallel to 86.
- the traveling locus 541 bends.
- the collected data generation unit 26 estimates the vehicle position 77, which is an accurate position as the position of the vehicle 1 at the measurement time t11 corresponding to the laser irradiation line 87, and also corresponds to the laser irradiation line 88. It is assumed that the vehicle position 78, which is an accurate position, is estimated as the position of the vehicle 1 at the measurement time t12.
- the collected data generation unit 26 estimates the position of the vehicle 1 at the measurement time t15 corresponding to the laser irradiation line 89, the vehicle position 77 at the measurement time t11 four times before and the vehicle position three before the measurement time t11 according to the above procedure.
- the speed of the vehicle 1 at the vehicle position 78 is calculated based on the vehicle position 78 at the measurement time t12.
- the collected data generation unit 26 generates a vector V89 in which the magnitude of the calculated speed is tripled along the traveling locus 541.
- the collected data generation unit 26 estimates the vehicle position 79, which is the terminal position of the generated vector V89, as the position of the vehicle 1 at the measurement time t15.
- the other side including the right angle of the right triangle indicates the laser irradiation direction corresponding to the estimated vehicle position 79. It becomes. It can be seen that there is a difference between the direction of the laser irradiation line indicated by the alternate long and short dash line passing through the vehicle position 79 and the direction of the laser irradiation line 89 at the actual measurement time t15, which is indicated by the bidirectional arrow.
- the collected data 44 generated by the collected data generation unit 26 includes a position error according to the accuracy of the GPS observation data 40. If the vehicle 1 is not traveling straight, an error in the traveling direction according to the accuracy of the GPS observation data 40 will be added. Therefore, when the vehicle 1 is not traveling at a constant speed and is not traveling straight, an error is included in both the position and the traveling direction of the vehicle 1.
- FIG. 6 shows the position and speed of the vehicle 1 on the horizontal plane for each measurement time estimated by the travel locus analysis unit 32 based on the travel locus data generated by the travel locus data generation unit 31, and the travel on the horizontal plane. It is a figure which showed the direction.
- FIG. 6 is an enlarged view of a part of the figure shown in FIG. 18, similarly to FIG. 5, and the same components as those in FIG. 18 are designated by the same reference numerals. Also in FIG. 6, it is assumed that the vehicle 1 is traveling instead of the vehicle 700, and the traveling locus 541 indicates the traveling locus of the vehicle 1.
- the plurality of dotted lines shown in FIG. 6 are laser irradiation lines indicating the irradiation direction of the laser light irradiated by the laser radar device 21 at each measurement time, and have the same positions and inclinations as those in FIG.
- the travel locus data generation unit 31 generates travel locus data based on the GPS observation data 40 and the quasi-zenith satellite observation data 41. As described above, by using the GPS observation data 40 and the quasi-zenith satellite observation data 41, the positioning error becomes about a dozen centimeters to a few centimeters. Therefore, each data of the position, speed, and traveling direction of the vehicle 1 on the horizontal plane at each measurement time estimated by the traveling locus analysis unit 32 is the data estimated by the collected data generation unit 26 corresponding to each. Will be more accurate than.
- the position of the vehicle 1 for each measurement time estimated by the travel locus analysis unit 32 is indicated by a circle on the travel locus 541 in FIG. 6, and the laser radar device 21 irradiates the laser beam at the actual measurement time. It will match the position. Therefore, even when the vehicle 1 is traveling straight but not traveling at a constant speed, the traveling locus analysis unit 32 sets the position of the vehicle 1 at five consecutive measurement times as the vehicle positions 90 and 91, for example. , 92, 93, 94.
- a right triangle is assumed in which a vector connecting adjacent objects at vehicle positions 90, 91, 92, 93, and 94 is generated, and the vector generated as described above is one of two sides sandwiching a right angle. Then, the other side of the right triangle sandwiching the right angle coincides with the laser irradiation line.
- the travel locus analysis unit 32 sets, for example, the position of the vehicle 1 at five consecutive measurement times as the vehicle positions 95, 96, 97, 98, 99. presume.
- the position and traveling direction of vehicle 1 can be estimated with high accuracy by using the quasi-zenith satellite observation data 41 for estimating the position of vehicle 1, and further, the vehicle speed data 42-1 and the traveling direction can be estimated. By using the data 42-2, the accuracy of estimation can be improved.
- FIG. 7 is a flowchart showing the flow of the generation process of the collected data 44 by the collected data generation unit 26.
- the collected data generation unit 26 detects that the point cloud data 43 corresponding to the new measurement time has been written to the storage unit 25 by the laser radar device 21 (step S1).
- the collected data generation unit 26 Based on the GPS observation data 40, the collected data generation unit 26 measures the position, speed, traveling direction and measurement of the vehicle 1 on the horizontal plane at the detected measurement time by the method described with reference to FIG. Estimate the position interval.
- the collected data generation unit 26 applies the traveling state data 42 at the detected measurement time when estimating the position and speed of the vehicle 1 on the horizontal plane, the traveling direction on the horizontal plane, and the measurement position interval at the detected measurement time. It also makes corrections.
- the collected data generation unit 26 is a tertiary of the laser radar device 21 at the detected measurement time based on the estimated position of the vehicle 1 on the horizontal plane and the positional relationship of the laser radar device 21 fixedly installed in the vehicle 1. Calculate the position in the original space.
- the collected data generation unit 26 sets the direction 180 ° opposite to the estimated traveling direction of the vehicle 1 on the horizontal plane as the direction on the horizontal plane of the laser radar device 21 at the detected measurement time, and the laser at the detected measurement time.
- the direction of the radar device 21 on the vertical plane is set to "0 °".
- the collected data generation unit 26 has the detected measurement time, the position of the laser radar device 21 corresponding to the measurement time, the direction of the laser radar device 21 on the horizontal plane and on the vertical surface, the measurement position interval, the speed of the vehicle 1, and the speed of the vehicle 1. Collected data 44 is generated in association with the traveling direction of the vehicle 1, and the generated collected data 44 is written in the storage unit 25 (step S2).
- the vehicle 1 is traveling at a constant speed depending on whether or not the traveling state data 42 at the detected measurement time and the traveling state data 42 at the measurement time immediately before the measurement time match. , And it is determined whether or not the vehicle is going straight (step S3). That is, the collected data generation unit 26 matches the speed of the vehicle 1 indicated by the vehicle speed data 42-1 at the detected measurement time with the speed of the vehicle 1 indicated by the vehicle speed data 42-1 at the measurement time immediately before the measurement time. By determining whether or not to do so, it is determined whether or not the vehicle 1 is traveling at a constant speed.
- the collected data generation unit 26 has the traveling direction of the vehicle 1 indicated by the traveling direction data 42-2 at the detected measurement time and the traveling of the vehicle 1 indicated by the traveling direction data 42-2 at the measurement time immediately before the measurement time. By determining whether or not the directions match, it is determined whether or not the vehicle 1 is traveling straight. When the speeds of the two vehicles 1 are the same and the traveling directions of the two vehicles 1 are the same, the collected data generation unit 26 is traveling at a constant speed and traveling straight. (Step S3, Yes), and a confidence index "high" is given to the point group data 43 corresponding to the detected measurement time (step S4).
- the collected data generation unit 26 indicates that the vehicle 1 is not at a constant speed or goes straight. It is determined that the data is not present (step S3, No), and the confidence index “low” is given to the point group data 43 corresponding to the detected measurement time (step S5).
- the collected data generation unit 26 replaces the reliability index “low” with “not” when there is a situation for improving the reliability of the design result in the station design performed using the point cloud data 43, for example. May be given.
- the collected data generation unit 26 assigns a reliability index "low” when the speed is not constant but is traveling straight, and assigns a reliability index "not” when the speed is not constant and the vehicle is not traveling straight. You may.
- the collected data generation unit 26 generates the collected data 44 based on whether or not, for example, an instruction signal for terminating the measurement of the point cloud data 43 is received by the operation input of the user of the point cloud data collecting device 2. It is determined whether or not to end (step S6). When it is determined that the collected data generation unit 26 has received the instruction signal to end the measurement of the point cloud data 43 (step S6, Yes), the process ends.
- step S6 No when the collected data generation unit 26 determines that the instruction signal for ending the measurement of the point cloud data 43 has not been received (step S6, No), the processing from step S1 is continued.
- FIG. 8 is a flowchart showing a flow of processing for correcting the collected data 44 by the data correction unit 3.
- the traveling locus data generation unit 31 detects that the collection data 44 at the new measurement time has been recorded by the collection data generation unit 26 in the storage unit 25 (step Sa1).
- the travel locus data generation unit 31 includes GPS observation data 40 at four observation times before and after including the measurement time of the newly recorded collected data 44 (hereinafter, also referred to as “measurement time to be processed”), and quasi-zenith satellite observation.
- the data 41 and the data 41 are read from the storage unit 25.
- the travel locus data generation unit 31 generates travel locus data based on the read GPS observation data 40 and the quasi-zenith satellite observation data 41 (step Sa2).
- the travel locus data generation unit 31 outputs the generated travel locus data and the measurement time of the processing target to the travel locus analysis unit 32.
- the travel locus analysis unit 32 captures the measurement time of the processing target output by the travel locus data generation unit 31 and the travel locus data.
- the traveling locus analysis unit 32 measures the position and speed of the vehicle 1 on the horizontal plane and the traveling direction on the horizontal plane at the measurement time of the processing target based on the traveling locus data by the method shown in FIG. Estimate the position interval.
- the travel locus analysis unit 32 includes estimated position data indicating the estimated position of the vehicle 1 on the horizontal plane, estimated measurement position interval data indicating the estimated measurement position interval, and estimated speed of the vehicle 1 and traveling on the horizontal plane. Estimated running state data including directions are generated (step Sa3).
- the traveling locus analysis unit 32 reads the traveling state data 42 at the measurement time to be processed from the storage unit 25.
- the travel locus analysis unit 32 compares the read travel state data 42 with the generated estimated travel state data, and the difference in speed is within a predetermined range, and the difference in travel direction is within a predetermined range. It is determined whether or not it is (step Sa4). That is, the travel locus analysis unit 32 is within a range in which the difference between the speed of the vehicle 1 indicated by the vehicle speed data 42-1 included in the travel condition data 42 and the speed of the vehicle 1 included in the estimated travel condition data is predetermined. Difference between the traveling direction of the vehicle 1 indicated by the traveling direction data 42-2 included in the traveling state data 42 and the traveling direction of the vehicle 1 included in the estimated traveling state data on the horizontal plane. Is within a predetermined range.
- the processing target is The normality determination instruction signal including the measurement time and the generated estimated position data is output to the travel locus data normality determination unit 35.
- the travel locus data normality determination unit 35 When the travel locus data normality determination unit 35 receives the normality determination instruction signal from the travel locus analysis unit 32, the travel locus data normality determination unit 35 informs the road traffic information acquisition unit 34 of the road traffic information at the measurement time of the processing target included in the normality determination instruction signal. Request and get. Based on the acquired road traffic information and the position indicated by the estimated position data included in the normality determination instruction signal, the travel locus data normality determination unit 35 sets the vehicle 1 in a tunnel, under an elevated vehicle, or the like at the measurement time to be processed. It is determined whether or not the travel locus data is normal based on whether or not the GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11 are present at positions where radio waves cannot be normally received (step Sa5).
- the travel locus data normality determination unit 35 is the travel locus data when the vehicle 1 is present at a position where radio waves cannot be normally received from the GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11 at the measurement time to be processed. Determines that it is not normal (steps Sa5 and No), outputs an abnormality to the outside (steps Sa6), and outputs a processing end instruction signal to the travel locus data generation unit 31.
- the travel locus data generation unit 31 ends the processing when it receives the processing end instruction signal.
- the travel locus data normality determination unit 35 travels when the vehicle 1 is present at a position where radio waves can be normally received from the GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11 at the measurement time to be processed. It is determined that the locus data is normal (steps Sa5, Yes), and a correction instruction signal for which a reliability index "low” including the measurement time of the processing target is given is output to the correction processing unit 36.
- the correction processing unit 36 receives the correction instruction signal from the travel locus data normality determination unit 35, the correction processing unit 36 refers to the point cloud data 43 of the storage unit 25, and the point cloud data corresponding to the measurement time of the processing target included in the correction instruction signal.
- the confidence index of 43 is corrected to "low” (step Sa7). After that, the process proceeds to step Sa13.
- step Sa5 when the travel locus data normality determination unit 35 determines that the travel locus data is normal, the reason for assigning the reliability index "low" to the point cloud data 43 at the measurement time to be processed. There is a difference exceeding a predetermined range between the running state data 42 and the estimated running state data, and there is a possibility that the vehicle 1 slips or the like and the running state data 42 is not normal. Therefore, processing is performed. This is because the point cloud data 43 at the measurement time of the target may not be collected normally.
- step Sa4 when the travel locus analysis unit 32 determines that the difference between the two speeds is within the predetermined range and the difference between the two travel directions is within the predetermined range (step Sa4, Yes), by the method shown in FIG. 4, the running state data 42 at the measurement time to be processed is applied to the estimated position data, the estimated measurement position interval data, and the estimated running state data, and the estimated position data and the estimated running state data are obtained again.
- the estimated measurement position interval data and the estimated running state data are generated (step Sa8).
- the traveling locus analysis unit 32 reads out the collected data 44 corresponding to the measurement time immediately before the measurement time of the processing target from the storage unit 25.
- the travel locus analysis unit 32 has a measurement position interval included in the read collected data 44, a travel direction of the vehicle 1, each of which is a measurement position interval indicated by the estimated measurement position interval data, and a travel direction of the vehicle 1 indicated by the estimated travel state data. It is determined whether or not each of the above is matched (step Sa9).
- step Sa9, Yes the vehicle 1 has a constant velocity at the measurement time of the processing target. It means that you are driving at and going straight. Therefore, since it is not necessary to correct the collected data 44 at the measurement time of the processing target, the traveling locus analysis unit 32 proceeds to the process of step Sa13 without proceeding to the process of correcting the collected data 44.
- the travel locus analysis unit 32 determines that the distance between the two measurement positions does not match or the travel directions of the two vehicles 1 do not match (steps Sa9, No)
- the estimated position data generated again and the estimated position data are used.
- the estimated measurement position interval data, the estimated running state data, and the measurement time of the processing target are output to the measurement condition generation unit 33.
- the measurement condition generation unit 33 is based on the estimated position data output by the traveling locus analysis unit 32 and the positional relationship of the laser radar device 21 fixedly installed in the vehicle 1, and the laser radar device 21 at the measurement time to be processed. Calculate the position of the above in three-dimensional space.
- the measurement condition generation unit 33 sets the direction 180 ° opposite to the horizontal component direction of the vehicle 1 included in the estimated travel state data output by the travel locus analysis unit 32, and the laser radar device 21 at the measurement time to be processed.
- the horizontal component in the direction of is set to "0 °" and the vertical component in the direction of the laser radar device 21 is set to "0 °".
- the measurement condition generation unit 33 uses the calculated position of the laser radar device 21, the direction of the laser radar device 21 on the horizontal plane and the vertical surface, the measurement position interval indicated by the estimated measurement position interval data, and the estimated running state data. Data including the speed and traveling direction of the included vehicle 1 and the measurement time to be processed is generated as measurement condition data (step Sa10). The measurement condition generation unit 33 outputs the generated measurement condition data to the correction processing unit 36.
- the correction processing unit 36 takes in the measurement condition data output by the measurement condition generation unit 33.
- the correction processing unit 36 selects the collection data 44 corresponding to the measurement time of the processing target included in the measurement condition data captured from the collection data 44 stored in the storage unit 25.
- the correction processing unit 36 rewrites the data included in the selected collected data 44 with the data included in the measurement condition data, and corrects the collected data 44 (step Sa11).
- the correction processing unit 36 refers to the point cloud data 43 of the storage unit 25, and corrects the reliability index of the point cloud data 43 corresponding to the measurement time of the processing target included in the measurement condition data to “high” (step). Sa12).
- the correction processing unit 36 ends the correction of the collected data 44 based on whether or not, for example, an instruction signal for ending the measurement of the point cloud data 43 is received by the operation input of the user of the point cloud data collecting device 2. It is determined whether or not to do so (step Sa13). When it is determined that the correction processing unit 36 has received the instruction signal to end the measurement of the point cloud data 43 (step Sa13, Yes), the correction processing unit 36 outputs the processing end instruction signal to the travel locus data generation unit 31. The travel locus data generation unit 31 ends the processing when it receives the processing end instruction signal.
- step Sa13, No when the correction processing unit 36 determines that the instruction signal for ending the measurement of the point cloud data 43 has not been received (step Sa13, No), the correction processing unit 36 outputs the processing continuation instruction signal to the travel locus data generation unit 31.
- the travel locus data generation unit 31 receives the processing continuation instruction signal, the processing of step Sa1 is restarted.
- the travel locus data generation unit 31 determines the position of the vehicle 1 on the horizontal plane with higher accuracy than the data indicating the position of the vehicle 1 on the horizontal plane obtained at each observation time.
- the data shown is acquired, and based on the acquired data indicating the position of the vehicle 1 on the horizontal plane, the travel locus data indicating the travel locus of the vehicle 1 is generated.
- the traveling locus analysis unit 32 analyzes the traveling locus data and estimates the position and traveling state of the vehicle 1 at each measurement time.
- the measurement condition generation unit 33 generates measurement condition data indicating the measurement conditions of the laser radar device 21 for each measurement time based on the position and running state of the vehicle 1 for each measurement time.
- the correction processing unit 36 corrects the collected data 44 based on the measurement condition data.
- the reliability index is "low” with respect to the point cloud data 43 collected when the vehicle 1 accelerates or decelerates, turns left or right, or travels in a curved manner. Or, “None” was given. Therefore, in the station design for determining the line-of-sight and the shielding rate between the base station and the terminal station using the point cloud data 43, the point cloud data to which the reliability index "low” or “none” is given. 43 could not be used effectively.
- the quasi-zenith satellite observation data 41 is used in addition to the GPS observation data 40.
- the position of the vehicle 1 and the traveling direction on the horizontal plane can be estimated with high accuracy. ..
- the position of the laser radar device 21 included in the collected data 44 and the direction of the laser radar device 21 on the horizontal plane can be accurately corrected. Therefore, the reliability of the point cloud data 43 collected when the vehicle 1 accelerates or decelerates, turns left or right, or travels in a bent manner can be increased, so that the vehicle 1 can turn left or right or travel in a bent manner.
- the confidence index "high" can be given to the point cloud data 43 collected.
- the point cloud data 43 that can be used when designing a station can be increased.
- the traveling state measuring unit 24 acquires the steering angle of the steering for each measurement time from the steering sensor and calculates the traveling direction of the vehicle 1 on the horizontal plane. Connects to a three-dimensional gyro sensor (3D gyro sensor), a compass, etc., acquires information indicating the direction from the three-dimensional gyro sensor, the compass, etc., and determines the traveling direction of the vehicle 1 on the horizontal plane. It may be calculated.
- 3D gyro sensor 3D gyro sensor
- a compass etc.
- FIG. 9 is a block diagram showing a configuration of the point cloud data collection system ⁇ of the second embodiment.
- the point cloud data collection system ⁇ includes a vehicle 1a equipped with a point cloud data collection device 2a, a plurality of GPS satellites 10-1, 10-2 and a quasi-zenith satellite 11, and a location information service provider server device 50. ing.
- the vehicle 1a is, for example, an automobile and corresponds to the above-mentioned MMS.
- the point cloud data collecting device 2a of the second embodiment estimates the traveling direction of the vehicle 1a on the vertical surface in addition to the traveling direction of the vehicle 1a on the horizontal plane. Therefore, the point cloud data collecting device 2a is referred to as, for example, the pan-global positioning navigation satellite system (hereinafter referred to as “GNSS” (Global Navigation Satellite System)) shown in Reference 1-1 below as a method for detecting the altitude of the vehicle 1a. .. ) Is used.
- GNSS Global Navigation Satellite System
- GNSS is a positioning system that uses positioning satellites.
- the positioning satellites include, for example, GLONASS (Global Navigation Satellite System) in Russia, GALIEO in Europe, and the like, in addition to the GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11 described above.
- GLONASS Global Navigation Satellite System
- the position of the satellite radio wave receiver is specified by each distance from the three positioning satellites whose positions are known in space to the satellite radio wave receiver.
- Reference 1-1 there are the following types of positioning methods using GNSS.
- a mobile station equipped with a satellite radio receiver is installed at the observation point to be measured, and a reference station whose position is known is installed in addition to the mobile station for positioning.
- the accuracy of positioning by the RTK-GNSS positioning method is about 2 to 3 cm in the horizontal direction and about 3 to 4 cm in the vertical direction.
- the network type RTK-GNSS positioning method includes a VRS (Virtual Reference Station) method and an FKP (Flachen Korrektur Parameter) method.
- satellite radio receivers installed at multiple electronic reference points installed nationwide receive data from the positioning satellite.
- the Geospatial Information Authority of Japan's analysis equipment receives and analyzes data from each of the satellite radio receivers installed at multiple electronic reference points.
- the processing device of the location information service provider receives the analysis result from the analysis device of the Geographical Survey Institute, and generates the correction data 45 indicating the phase difference obtained from the reference point of the Geographical Survey Institute.
- the person performing the positioning installs a mobile station equipped with a satellite radio wave receiver at the observation point, and performs positioning based on the data from the positioning satellite received at the observation point and the correction data 45 received through the communication line.
- the network type RTK-GNSS positioning method is slightly less accurate than the RTK-GNSS positioning method, but unlike the RTK-GNSS positioning method, it does not require the installation of a reference station.
- the RTK-GNSS positioning method and the network type RTK-GNSS positioning method have better accuracy as the number of satellites increases, and the accuracy is better when the sky is open than the valley.
- the location information service provider server device 50 is a device corresponding to the processing device of the location information service provider that receives the analysis result from the above-mentioned analysis device of the Geographical Survey Institute, and generates correction data 45. do.
- the location information service provider server device 50 transmits the generated correction data 45 to the point cloud data collection device 2a of the vehicle 1a via, for example, a wireless communication network.
- the point cloud data collecting device 2a includes a laser radar device 21, a satellite radio wave receiving antenna 22, a radio wave receiving antenna 27, an information receiving unit 23a, a traveling state measuring unit 24a, a storage unit 25a, a collected data generation unit 26a, and data correction.
- a unit 3a is provided.
- the radio wave receiving antenna 27 receives the radio wave on which the correction data 45 is superimposed from the location information service provider server device 50 via the wireless communication network.
- the information receiving unit 23a has the following configuration in addition to the configuration provided in the information receiving unit 23.
- the information receiving unit 23a is connected to the radio wave receiving antenna 27, detects the correction data 45 superimposed on the radio wave received by the radio wave receiving antenna 27, and stores the detected correction data 45 in the storage unit 25a. Write.
- the data correction unit 3a includes a travel locus data generation unit 31a, a travel locus analysis unit 32a, a measurement condition generation unit 33a, a road traffic information acquisition unit 34, a travel locus data normality determination unit 35, and a correction processing unit 36.
- the traveling state measuring unit 24a is connected to, for example, a vehicle speed sensor for detecting the speed of the vehicle 1a, a steering sensor for detecting the steering angle of the steering, and a horizontal level.
- the traveling state measuring unit 24a measures the speed of the vehicle 1a at each measurement time based on the data obtained from the vehicle speed sensor.
- the traveling state measuring unit 24a measures the steering angle of the steering at each measurement time based on the data obtained from the steering sensor.
- the traveling state measuring unit 24a measures the inclination of the vehicle 1a at each measurement time based on the data obtained from the horizontal level.
- the traveling state measuring unit 24a calculates the traveling direction of the vehicle 1a on the horizontal plane from the steering angle of the steering at each measurement time, and calculates the traveling direction on the vertical surface from the inclination of the vehicle 1a at each measurement time.
- the traveling state measuring unit 24a is specified by the vehicle speed data 42-1 indicating the speed of the vehicle 1a at each measurement time, the traveling direction of the vehicle 1a on the horizontal plane at each measurement time, and the traveling direction on the vertical surface.
- the traveling state data 42a including the traveling direction data 42a-2 indicating the traveling direction is generated.
- the traveling state measuring unit 24a writes the generated traveling state data 42a in the storage unit 25a.
- the collected data generation unit 26a has the same configuration as the collected data generation unit 26 of the first embodiment except for the following points.
- the collected data generation unit 26 of the first embodiment referred to the traveling direction data 42-2, but the collected data generation unit 26a of the second embodiment refers to the traveling direction data 42a-2. Only the direction of the horizontal component of the traveling direction included in the traveling direction data 42a-2 is referred to.
- the storage unit 25a stores the GPS observation data 40, the quasi-zenith satellite observation data 41, the correction data 45, the traveling state data 42a, the point group data 43, and the collected data 44.
- the travel locus data generation unit 31a generates travel locus data indicating the travel locus of the vehicle 1a based on the GPS observation data 40 stored in the storage unit 25a, the quasi-zenith satellite observation data 41, and the correction data 45.
- the correction data 45 is data generated from GPS observation data 40, quasi-zenith satellite observation data 41, and the like, and the correction data 45 includes the observation time. Therefore, the travel locus data generation unit 31a generates travel locus data using the correction data 45 corresponding to the observation time of the GPS observation data 40 and the quasi-zenith satellite observation data 41.
- the travel locus data generated by the travel locus data generation unit 31a includes components in the vertical direction, unlike the travel locus data generated by the travel locus data generation unit 31 of the first embodiment.
- the travel locus analysis unit 32a Based on the travel locus data generated by the travel locus data generation unit 31a, the travel locus analysis unit 32a extends the method shown in FIG. 3 in the vertical direction in the first embodiment to the vehicle for each measurement time.
- the position of 1a, the speed, the traveling direction, and the measurement position interval are estimated.
- the position of the vehicle 1a at each measurement time includes a horizontal component and a vertical component, it is a position indicated by three-dimensional coordinates indicated by, for example, latitude, longitude, and altitude.
- the traveling direction of the vehicle 1a at each measurement time is a direction specified by a horizontal component and a vertical component.
- the travel locus analysis unit 32a includes estimated position data indicating the position of the vehicle 1a for each estimated measurement time, estimated measurement position interval data indicating the estimated measurement position interval, and speed and travel of the vehicle 1a for each estimated measurement time. Generate estimated driving condition data including direction.
- the traveling locus analysis unit 32a compares the estimated traveling state data at a certain measurement time with the traveling state data 42a stored in the storage unit 25a corresponding to the measurement time, and the difference in speed is within a predetermined range. Moreover, when the difference in the traveling direction is within a predetermined range, the traveling state data 42a is used to perform a process of improving the accuracy of the estimated position data, the estimated measurement position interval data, and the estimated traveling state data.
- the predetermined range for the difference in speed and the predetermined range for the difference in the traveling direction are, for example, the speed and the traveling direction of the vehicle 1a indicated by the traveling state data 42a, and the estimated traveling state data.
- the traveling state data 42a can be used for processing for improving the accuracy of the estimated position data, the estimated measurement position interval data, and the estimated running state data.
- the measurement condition generation unit 33a is the measurement condition of the laser radar device 21 at the measurement time based on the estimated position data for each measurement time generated by the travel locus analysis unit 32a, the estimated measurement position interval data, and the estimated travel state data. Generate measurement condition data indicating.
- FIG. 11 is a view of the vehicle 1a traveling on the uneven road 300 as viewed from the side surface.
- the double-lined arrow indicated by reference numeral 200 indicates the locus on which the vehicle 1a has traveled, and is hereinafter referred to as the travel locus 200.
- the vehicle 1a is traveling to the right as indicated by the arrow of the traveling locus 200.
- the alternate long and short dash line indicated by reference numeral 210 indicates the average altitude of the vehicle 1a, and is hereinafter referred to as the vehicle average altitude 210.
- the traveling locus 200 changes up and down depending on the unevenness of the road 300.
- the vehicle average altitude 210 it is possible to know whether the position of the vehicle 1a is higher or lower than the average altitude.
- the vehicle 1a is located at a position higher than the average altitude
- the vehicle 1a is located at a position lower than the average altitude.
- the change in the traveling direction on the vertical surface is small. For example, on a 5% uphill and downhill, the change on the vertical surface is 5m for a 100m run, but it is generally said to be a steep slope.
- FIG. 12 is a diagram showing changes in the laser irradiation direction of the laser radar device 21 of the vehicle 1a traveling on the road 300 shown in FIG. As described above, even if the road is generally called a steep slope, the change on the vertical surface is small. Therefore, in FIG. 12, the change in the traveling direction on the vertical surface is largely shown. The change in the unevenness of the road 300 is exaggerated.
- a plurality of dotted lines shown along the traveling locus 200 are laser irradiation lines indicating the irradiation direction of the laser light emitted by the laser radar device 21 mounted on the vehicle 1a at each measurement time.
- the laser irradiation lines are perpendicular to the traveling direction and are arranged in parallel at equal intervals. become.
- the angle of the laser irradiation line changes according to the inclination of the vehicle 1a, so that it is not parallel and turbulent. ..
- the position of each point of the point cloud data 43 is specified based on the collected data 44 without considering the vertical component of the traveling direction of the vehicle 1a, the direction of the laser radar device 21 is not accurate.
- the position of each point in the point cloud data 43 is also not accurate. Therefore, it is appropriate that the point cloud data 43 collected while the altitude of the vehicle 1a is changing has a reliability index of "low” or "absent", as in the case of turning left or right or bending. be.
- the travel locus data generation unit 31a generates travel locus data based on the GPS observation data 40, the quasi-zenith satellite observation data 41, and the correction data 45. As described above, by using the GPS observation data 40, the quasi-zenith satellite observation data 41, and the correction data 45, the altitude of the vehicle 1a can be estimated with a high accuracy of about 3 to 4 cm.
- the position of the vehicle 1a at each measurement time estimated by the travel locus analysis unit 32a is, for example, as shown by a circle on the travel locus 200 in FIG. 12, the laser radar device 21 emits laser light at the actual measurement time. It will match the irradiated position.
- the traveling locus analysis unit 32a estimates the positions of the vehicle 1a at four consecutive measurement times as the vehicle positions 60, 61, 62, 63.
- a vector connecting the adjacent portions at the vehicle positions 60, 61, 62, and 63 is generated, and the generated vector as described in the first embodiment is used as one of the two sides sandwiching the right angle. Assuming a right triangle, the other side of the right triangle that sandwiches the right angle coincides with the laser irradiation line.
- the traveling locus analysis unit 32a estimates the positions of the vehicle 1a at four consecutive measurement times as the vehicle positions 64, 65, 66, 67. Also in this case, after generating a vector connecting the adjacent ones at the vehicle positions 64, 65, 66, 67, the vector generated as described above is set as one of the two sides sandwiching the right angle. Assuming a right triangle, the other side of the right triangle that sandwiches the right angle coincides with the tilted laser irradiation line.
- the GPS observation data 40 and the quasi-zenith satellite observation data 41 to estimate the position of the vehicle 1a, it is possible to estimate the position and the traveling direction of the vehicle 1a in consideration of the vertical direction with high accuracy. Further, by using the vehicle speed data 42-1 and the traveling direction data 42a-2, it is possible to estimate with higher accuracy.
- FIG. 13 is a flowchart showing a flow of processing for correcting the collected data 44 by the data correction unit 3a.
- the travel locus data generation unit 31a detects that the collection data 44 at the new measurement time has been recorded by the collection data generation unit 26a in the storage unit 25a (step Sb1).
- the travel locus data generation unit 31a includes GPS observation data 40 at four observation times before and after including the measurement time of the newly recorded collected data 44 (hereinafter, also referred to as “measurement time to be processed”), and quasi-zenith satellite observation.
- the data 41 and the correction data 45 are read from the storage unit 25a.
- the travel locus data generation unit 31a generates travel locus data including a vertical component based on the read GPS observation data 40, the quasi-zenith satellite observation data 41, and the correction data 45 (step Sb2).
- the travel locus data generation unit 31a outputs the generated travel locus data and the measurement time of the processing target to the travel locus analysis unit 32a.
- the travel locus analysis unit 32a captures the measurement time of the processing target output by the travel locus data generation unit 31a and the travel locus data.
- the travel locus analysis unit 32a extends the method shown in FIG. 3 in the vertical direction, and based on the travel locus data, the position, speed, and horizontal of the vehicle 1a in the three-dimensional space at the measurement time of the processing target.
- the traveling direction including the component and the vertical component and the measurement position interval are estimated.
- the travel locus analysis unit 32a obtains estimated position data indicating the estimated position of the vehicle 1a, estimated measurement position interval data indicating the estimated measurement position interval, and estimated travel state data including the estimated speed and travel direction of the vehicle 1a. Generate (step Sb3).
- the traveling locus analysis unit 32a reads out the traveling state data 42a at the measurement time to be processed from the storage unit 25a.
- the travel locus analysis unit 32a compares the read travel state data 42a with the generated estimated travel state data, and the difference in speed is within a predetermined range, and the difference in travel direction is within a predetermined range. (Step Sb4). That is, the traveling locus analysis unit 32a is within a range in which the difference between the speed of the vehicle 1a indicated by the vehicle speed data 42-1 included in the traveling state data 42a and the speed of the vehicle 1a included in the estimated traveling state data is predetermined.
- the difference between the traveling direction of the vehicle 1a indicated by the traveling direction data 42a-2 included in the traveling state data 42a and the traveling direction of the vehicle 1a included in the estimated traveling state data is predetermined. Determine if it is within range.
- the processing target is The normality determination instruction signal including the measurement time and the generated estimated position data is output to the travel locus data normality determination unit 35.
- steps Sb5, Sb6, and Sb7 is the same as that of steps Sa5, Sa6, and Sa7 shown in FIG. 8, and the traveling locus data normality determination unit 35, the road traffic information acquisition unit 34, and the correction processing unit 36 perform the same processing.
- step Sb4 when the travel locus analysis unit 32a determines that the difference between the two speeds is within the predetermined range and the difference between the two travel directions is within the predetermined range (steps Sb4, Yes), the figure.
- the method shown in 4 is extended in the vertical direction, and the running state data 42a at the measurement time to be processed is applied to the estimated position data, the estimated measurement position interval data, and the estimated running state data, and the estimated position is again estimated.
- the data, the estimated measurement position interval data, and the estimated running state data are generated (step Sb8).
- the traveling locus analysis unit 32a reads out the collected data 44 corresponding to the measurement time immediately before the measurement time of the processing target from the storage unit 25a.
- the measurement position interval included in the read collected data 44 and the travel direction of the vehicle 1a are each the measurement position interval indicated by the estimated measurement position interval data and the travel direction of the vehicle 1a indicated by the estimated travel state data. It is determined whether or not each of the above is matched (step Sb9).
- step Sb9, Yes When the travel locus analysis unit 32a determines that the distance between the two measurement positions matches and the travel directions of the two vehicles 1a match (steps Sb9, Yes), the vehicle 1a travels at a constant speed at the measurement time to be processed. And you are going straight. Therefore, it is not necessary to correct the collected data 44 at the measurement time of the processing target. Therefore, the traveling locus analysis unit 32a does not proceed to the process of correcting the collected data 44, but proceeds to the process of step Sb13.
- the travel locus analysis unit 32a determines that the distance between the two measurement positions does not match or the travel directions of the two vehicles 1a do not match (steps Sb9, No)
- the estimated position data generated again and the estimated position data are used.
- the estimated measurement position interval data, the estimated running state data, and the measurement time of the processing target are output to the measurement condition generation unit 33a.
- the measurement condition generation unit 33a is based on the estimated position data output by the traveling locus analysis unit 32a and the positional relationship of the laser radar device 21 fixedly installed in the vehicle 1a, and the laser radar device 21 at the measurement time of the processing target. Calculate the position of the above in three-dimensional space.
- the measurement condition generation unit 33a uses the direction 180 ° opposite to the horizontal component direction of the vehicle 1a included in the estimated travel state data output by the travel locus analysis unit 32a as the horizontal component in the direction of the laser radar device 21.
- the direction 180 ° opposite to the direction of the vertical component in the traveling direction of the vehicle 1a is defined as the vertical component in the direction of the laser radar device 21.
- the measurement condition generation unit 33a obtains the direction of the horizontal component and the direction of the vertical component of the laser radar device 21 as described above.
- the measurement condition generation unit 33a uses the calculated position of the laser radar device 21, the direction of the laser radar device 21 on the horizontal plane and the vertical surface, the measurement position interval indicated by the estimated measurement position interval data, and the estimated running state data. Data including the speed and traveling direction of the included vehicle 1a and the measurement time to be processed is generated as measurement condition data (step Sb10). The measurement condition generation unit 33a outputs the generated measurement condition data to the correction processing unit 36.
- the correction processing unit 36 takes in the measurement condition data output by the measurement condition generation unit 33a.
- the correction processing unit 36 selects the collection data 44 corresponding to the measurement time of the processing target included in the measurement condition data captured from the collection data 44 stored in the storage unit 25a.
- the correction processing unit 36 rewrites the data included in the selected collected data 44 with the data included in the measurement condition data, and corrects the collected data 44 (step Sb11).
- the correction processing unit 36 refers to the point cloud data 43 of the storage unit 25a, and corrects the reliability index of the point cloud data 43 corresponding to the measurement time of the processing target included in the measurement condition data to “high” (step). Sb12).
- step Sb13 is the same as that of step Sa13 shown in FIG. 8, and the correction processing unit 36 performs the same processing.
- the travel locus data generation unit 31a acquires data indicating the position of the vehicle 1a on the vertical surface obtained at each observation time, and acquires the data indicating the position of the vehicle 1a on the vertical surface. Based on the data indicating the position of, the traveling locus data indicating the traveling locus of the vehicle 1a is generated.
- the travel locus analysis unit 32a analyzes the travel locus data and estimates the position and travel state of the vehicle 1a at each measurement time.
- the measurement condition generation unit 33a generates measurement condition data indicating the measurement conditions of the laser radar device 21 for each measurement time based on the position and running state of the vehicle 1a for each measurement time.
- the correction processing unit 36 corrects the collected data 44 based on the measurement condition data.
- the vehicle 1a When the vehicle 1a travels with the altitude of the vehicle 1a fluctuating up and down, an error is included in the position and direction of the laser radar device 21 included in the collected data 44 generated by the collected data generation unit 26, but the error is included. An appropriate reliability index was not given to the point cloud data 43 corresponding to the collected data 44. Therefore, the point cloud data 43 having a low degree of reliability may be used in the station design.
- the position of the vehicle 1a and the horizontal plane even when the vehicle 1a travels while the altitude of the vehicle 1a fluctuates up and down. And the traveling direction on the vertical surface can be estimated with high accuracy.
- the position of the laser radar device 21 included in the collected data 44 and the horizontal and vertical directions of the laser radar device can be accurately corrected. Therefore, the reliability of the point cloud data 43 collected when the vehicle 1a travels with the altitude of the vehicle 1a fluctuating up and down can be increased, so that the vehicle 1a travels with the altitude of the vehicle 1a fluctuating up and down. In this case, the confidence index "high" can be given to the point cloud data 43 collected. Therefore, by estimating the position and running state of the vehicle in the place where the laser irradiation line is disturbed with higher accuracy than before, it is possible to use the point cloud data whose reliability is lowered due to the disturbance of the laser irradiation line. For example, it is possible to increase the reliability of the point cloud data 43 that can be used when designing the station.
- the traveling state measuring unit 24a measures the steering angle of the steering at each measurement time based on the data obtained from the steering sensor, and measures based on the data obtained from the horizontal level.
- the present invention is not limited to the embodiment.
- the traveling state measuring unit 24a acquires data obtained from the three-dimensional gyro sensor instead of the steering sensor and the horizontal level, and based on the acquired data, determines the traveling direction of the vehicle 1a on the horizontal plane and on the vertical surface. It may be calculated.
- FIG. 14 is a block diagram showing a configuration of the point cloud data collection system ⁇ according to the third embodiment.
- the point cloud data collection system ⁇ includes a vehicle 1b equipped with a point cloud data collection device 2b, a plurality of GPS satellites 10-1, 10-2 and a quasi-zenith satellite 11, and a location information service provider server device 50. ing.
- the vehicle 1b is, for example, an automobile and corresponds to the above-mentioned MMS.
- the point cloud data collecting device 2b includes a laser radar device 21, a satellite radio wave receiving antenna 22, a radio wave receiving antenna 27, an information receiving unit 23a, a traveling state measuring unit 24a, a storage unit 25a, a collected data generation unit 26b, and data correction.
- a part 3b is provided.
- the laser radar device 21 is installed at a constant angle indicated by reference numeral 100 with respect to the top of the vehicle 1b.
- the constant angle indicated by the reference numeral 100 is referred to as an inclination angle 100. Therefore, the rotation axis of the laser radar device 21 is also tilted at an angle of inclination of 100, and the direction of the laser radar device 21 is the direction indicated by the arrow of reference numeral 4b.
- Japanese Patent Application Laid-Open No. 2017-156179 describes that "the device is arranged so that the angle of the scan line oscillated by the laser scanner is oblique with respect to the vertical direction" (paragraph [0018]). By inclining the angle of the scan line in this way, “the state of the equipment is accurately detected without slowing down the traveling speed of the inspection vehicle or increasing the number of irradiation points per second of the laser scanner. It is stated that the effect of "can be done” (paragraph [0019]) can be obtained.
- the laser radar device 21 is tilted at an tilt angle of 100 in order to obtain the effect shown in Japanese Patent Application Laid-Open No. 2017-156179.
- the irradiation direction of the laser beam to be irradiated is also tilted at an inclination angle of 100. Therefore, it is necessary to generate the collected data 44 in consideration of the inclination angle 100.
- the altitude of the vehicle 1b fluctuates up and down, it is necessary to correct the collected data 44 in consideration of the inclination angle 100.
- the collected data generation unit 26b has the same configuration as the collected data generation unit 26a of the second embodiment except for the following points. Similar to the collected data generation unit 26 of the first embodiment, the collected data generation unit 26a of the second embodiment assumes that the rotation axis of the laser radar device 21 is always constant with respect to the horizontal plane, and the laser radar device. The collected data 44 is generated with the direction of 21 on the vertical plane always set to "0 °". On the other hand, the collected data generation unit 26b of the third embodiment always generates the collected data 44 with the direction of the laser radar device 21 on the vertical plane as the tilted direction by the tilt angle of 100.
- the data correction unit 3b includes a travel locus data generation unit 31a, a travel locus analysis unit 32a, a measurement condition generation unit 33b, a road traffic information acquisition unit 34, a travel locus data normality determination unit 35, and a correction processing unit 36.
- the measurement condition generation unit 33b is a laser radar at the measurement time based on the estimated position data for each measurement time, the estimated measurement position interval data, the estimated travel state data, and the inclination angle 100 generated by the travel locus analysis unit 32a. Generates measurement condition data indicating the measurement conditions of the device 21.
- FIG. 15 is a diagram showing changes in the laser irradiation line when the vehicle 1b of the third embodiment travels on the road 300 shown in FIG. 11 of the second embodiment. Since the vehicle 1a of the second embodiment and the vehicle 1b of the third embodiment have the same shape, the average vehicle altitude is the same and the traveling locus is also the same. Therefore, the traveling locus 200 and the vehicle average altitude 210 are shown with the same reference numerals as those in FIG.
- a plurality of dotted lines shown along the traveling locus 200 are laser irradiation lines indicating the irradiation direction of the laser light emitted by the laser radar device 21 mounted on the vehicle 1b at each measurement time.
- the laser radar device 21 is tilted at an inclination angle of 100. Therefore, all the laser irradiation lines are also inclined at an inclination angle of 100.
- the position of the vehicle 1b for each measurement time estimated by the travel locus analysis unit 32a is, for example, a laser at the actual measurement time as shown by a circle on the travel locus 200 in FIG. It coincides with the position where the radar device 21 irradiates the laser beam.
- the traveling locus analysis unit 32a estimates the positions of the vehicle 1a at four consecutive measurement times as the vehicle positions 60, 61, 62, 63.
- a vector connecting the adjacent portions at the vehicle positions 60, 61, 62, and 63 is generated, and the generated vector as described in the first embodiment is used as one of the two sides sandwiching the right angle. Assume a right triangle.
- the laser radar device 21 is tilted at an angle of inclination of 100, tilting the other side of the right triangle sandwiching the right angle at an angle of tilt of 100 coincides with the laser irradiation line. become.
- the traveling locus analysis unit 32a estimates the positions of the vehicle 1b at four consecutive measurement times as the vehicle positions 64, 65, 66, 67. Also in this case, after generating a vector connecting the adjacent ones at the vehicle positions 64, 65, 66, 67, the vector generated as described above is set as one of the two sides sandwiching the right angle. Assume a right triangle. If the other side of the right triangle sandwiching the right angle is tilted at an tilt angle of 100, it coincides with the laser irradiation line.
- the measurement condition generation unit 33b is based on the travel direction of the vehicle 1b included in the estimated travel state data generated by the travel locus analysis unit 32a, and takes into consideration the inclination angle 100 which is the inclination of the laser radar device 21 and the laser radar device 21. Calculate the horizontal and vertical components in the direction of. By using the calculated horizontal component and vertical component in the direction of the laser radar device 21, it is possible to accurately specify the position of each point of the point cloud data 43 in the three-dimensional space.
- the collected data generation unit 26b performs the same processing as the collected data generation unit 26 of the first embodiment to generate the collected data 44. However, the collected data generation unit 26b generates the collected data 44 with the direction on the vertical surface of the direction of the laser radar device 21 always set as the tilted direction by the tilt angle of 100.
- the process of correcting the collected data 44 in the third embodiment is the same as that of the second embodiment except for the process of step Sb10 among the processes of the second embodiment shown in FIG. ..
- the measurement condition generation unit 33b is based on the estimated position data output by the traveling locus analysis unit 32a and the positional relationship of the laser radar device 21 fixedly installed in the vehicle 1b, and the laser radar device 21 at the measurement time of the processing target. Calculate the position of the above in three-dimensional space.
- the measurement condition generation unit 33b sets the direction 180 ° opposite to the direction of the horizontal component in the travel direction of the vehicle 1b included in the estimated travel state data output by the travel locus analysis unit 32a as the direction on the horizontal plane of the laser radar device 21.
- the direction obtained by adding the inclination angle 100 to the direction 180 ° opposite to the direction of the vertical component in the traveling direction of the vehicle 1b is defined as the vertical component in the direction of the laser radar device 21. That is, when the traveling direction of the vehicle 1b is indicated by a vector, the vector obtained by tilting the inverse vector of the vector in the vertical direction by the inclination angle of 100 indicates the direction of the laser radar device 21. Therefore, the measurement condition generation unit 33b obtains the direction of the horizontal component and the direction of the vertical component of the laser radar device 21 as described above.
- the measurement condition generation unit 33b uses the calculated position of the laser radar device 21, the direction of the laser radar device 21 on the horizontal plane and the vertical surface, the measurement position interval indicated by the estimated measurement position interval data, and the estimated running state data. Data including the speed and traveling direction of the included vehicle 1b and the measurement time to be processed is generated as measurement condition data.
- the vertical component in the direction of the laser radar device 21 changes in a complicated manner. It will be.
- the configuration of the third embodiment it is possible to calculate an accurate vertical component in the direction of the laser radar device 21 in consideration of the inclination of the laser radar device 21. Thereby, the vertical component in the direction of the laser radar device 21 included in the collected data 44 can be accurately corrected.
- the reliability of the point cloud data 43 collected when the vehicle 1b travels in which the altitude of the vehicle 1b fluctuates up and down can be increased, and the reliability index "high" is given to the point cloud data 43. be able to. Therefore, by estimating the position and running state of the vehicle in the place where the laser irradiation line is disturbed with higher accuracy than before, it is possible to use the point cloud data whose reliability is lowered due to the disturbance of the laser irradiation line. For example, it is possible to increase the reliability of the point cloud data 43 that can be used when designing the station.
- the traveling locus analysis unit 32a detects the altitudes of the vehicles 1a and 1b by using the network type RTK-GNSS positioning method, but other methods are used. You may.
- the optical lattice clock shown in References 2-1, 2, 2 and 2-3 may be used.
- An optical lattice clock is an atomic clock in which atoms are placed one by one in an optical lattice, which is a large number of regions smaller than the wavelength of light created by interfering with laser light, and another laser light is applied to measure the resonance frequency.
- time is delayed where gravity is strong, that is, at low altitudes.
- the travel locus data generation units 31, 31a when the travel locus data generation units 31, 31a generate travel locus data based on the quasi-zenith satellite observation data 41, for example, MADOCA (Multi-GNSS Advanced Demonstration tool for)
- a correction algorithm for correcting the positioning data of the quasi-zenith satellite observation data 41 such as Orbit and Clock Analysis) (Reference 3-1) and the QZS quasi-static method (Reference 3-2) may be used.
- the network type RTK-GNSS positioning method described in the second and third embodiments may be applied to the point cloud data collection system ⁇ in the first embodiment.
- the travel locus data generation units 31, 31a should use a correction algorithm for correcting the positioning data of the quasi-zenith satellite observation data 41 such as the positioning process of the network type RTK-GPS positioning method (Reference 3-3). You may do it.
- the correction algorithm for correcting these positioning data the estimation accuracy of the positions, speeds, and traveling directions of the vehicles 1, 1a, 1b performed by the traveling locus data generation units 31, 31a is improved.
- point cloud data 43 which is three-dimensional data (3D data)
- point cloud data processing software Reference 3-4 that performs general-purpose processing, wall noise removal processing (reference).
- Documents 3-5 and the like are known. Therefore, the point cloud data 43 can be corrected with higher accuracy by applying the correction method for removing the noise of the point cloud data 43 after generating the traveling locus data with high accuracy.
- Fig. 1 shows the definition of the road maintenance system, point cloud data processing software (general-purpose processing).
- the GPS satellites 10-1, 10-2 and the quasi-zenith satellite 11 are not used in the first embodiment described above, and the GPS satellites 10-1, 10-2 and the quasi-zenith satellite 11 are used in the second and third embodiments.
- the location information service provider server device 50 may not be used, and instead, the camera shake detection function in the camera shake correction by a digital camera or a video camera may be used (for example, References 4-1 and 4-2, 4). See -3, 4-4).
- the vehicles 1, 1a and 1b include, for example, an image pickup unit such as a video camera and a video analysis unit that analyzes an image obtained from the image pickup unit.
- the image analysis unit detects from the image obtained from the image pickup unit that the trajectory of the vehicles 1, 1a, 1b is bent or fluctuates up and down, it responds to small displacements, for example, camera shake. It is possible to detect displacement information such as vibration, rotation, and movement amount.
- the analysis speed of the video analysis unit can be arbitrarily adjusted, and the time interval of the analysis of the video analysis unit is shorter than the observation time interval of 1 second in the first to third embodiments. For example, since it is possible to match the measurement time interval of the laser radar device 21, it is possible to detect the displacement information with high accuracy. By using the detected displacement information for the correction of the collected data 44, it is possible to specify the detailed horizontal and vertical displacement amounts of the laser radar device 21 and the like.
- the reliability of the point cloud data can be increased, and the point cloud data with the increased reliability can be utilized in the station design.
- the camera shake detection function may be added to the configuration of the first to third embodiments. With the camera shake detection function, it is possible to obtain displacement information at intervals shorter than the observation time as described above, and the observation time. It can be used as information that complements the interval between the above, and it becomes possible to estimate the movement of the vehicles 1, 1a, 1b during the observation time with higher accuracy.
- vibration is suppressed in order to prevent the influence of displacement when traveling in a bent manner or traveling up and down.
- a configuration provided on a pedestal such as a hexapod or a gimbal may be applied.
- Hexapods, gimbals, etc. are equipped with correction control technology that suppresses vibration based on camera images and sensor information that detects acceleration and tilt, and maintains the level of the camera (for example, References 4-2, 4-5). , 4-6).
- the vibration is suppressed. Therefore, since the direction of the rotation axis of the laser radar device 21 can be maintained in a constant direction, the accuracy of specifying the position of each point in the point cloud data can be improved. In this configuration, the direction of the rotation axis of the laser radar device 21 is maintained in a constant direction by the hexapod, gimbal, etc., so that the traveling directions of the vehicles 1, 1a, 1b and the direction of the laser radar device 21 Displacement occurs between them.
- the tilt exceeds the adjustment amount adjusted by the hexapod, gimbal, etc., or when the tilt is continuously adjusted, for example, when the tilt adjustment amount is small in a state close to horizontal.
- the laser radar device 21 cannot be maintained horizontally. In that case, the correction of the collected data according to the configurations of the first to third embodiments is utilized. Become.
- the "PI H-900KSCO" hexapod has a maximum motion range of 200 mm (X, Y, Z axis direction) and 66 ° (pitch, yaw, roll) while supporting a load of up to 130 pounds (about 59 kg). It is provided at speeds of 80 mm / s and 30 ° / s, respectively.
- steps Sa8 and Sb8 shown in FIGS. 8 and 13 the running state data 42 and 42a are applied to the estimated position data, the estimated measurement position interval data and the estimated running state data. Therefore, the estimated position data, the estimated measurement position interval data, and the estimated running state data are generated again, but the configuration of the present invention is not limited to the embodiment.
- the estimated position data, the estimated measurement position interval data and the estimated traveling state data are generated based on the traveling locus data and the traveling state data 42 and 42a, and the processing of steps Sa8 and Sb8 is performed. You may not have it.
- the processing for generating the estimated position data, the estimated measurement position interval data, and the estimated running state data is performed once, the processing amount can be reduced.
- the difference between the estimated running state data to be compared and the running state data is reduced. Therefore, in steps Sa4 and Sb4, the traveling locus analysis units 32 and 32a may often determine "Yes". Therefore, from the viewpoint of the accuracy of the estimated position data, the estimated measurement position interval data, and the estimated running state data finally obtained, the process of steps Sa8 and Sb8 is not collectively performed as the process of steps Sa3 and Sb3. 8 and the process shown in FIG. 13 are superior.
- the estimated position data, the estimated measurement position interval data, and the estimated traveling state data may be generated only from the traveling locus data, and the steps Sa8 and Sb8 may not be performed.
- the collected data 44 includes the measurement time, the position of the laser radar device 21, the direction including the horizontal component and the vertical component of the laser radar device 21, and the measurement position interval.
- the speed of the vehicles 1, 1a, 1b and the traveling direction of the vehicles 1, 1a, 1b are included, but the configuration of the present invention is not limited to the embodiment. Since it is sufficient that the position of each point in the point group data 43 in the three-dimensional space can be specified, in the first embodiment, the collected data 44 includes at least the measurement time, the position of the laser radar device 21, and the laser radar device 21.
- the direction of the horizontal component may be included, in which case the travel locus analysis unit 32 of the first embodiment estimates the position of the vehicle 1 on the horizontal plane at each measurement time.
- the traveling locus analysis unit 32 estimates only the traveling direction of the vehicle 1 on the horizontal plane at each measurement time as the traveling state of the vehicle 1.
- the measurement condition generation unit 33 may generate measurement condition data including the measurement time, the position of the laser radar device 21, and the direction of the horizontal component of the laser radar device 21.
- the collected data 44 may include at least the measurement time, the position of the laser radar device 21, and the directions of the horizontal and vertical components of the laser radar device 21.
- the traveling locus analysis unit 32a of the second and third embodiments first estimates the position of the vehicle 1a at each measurement time.
- the traveling locus analysis unit 32a estimates only the traveling direction of the vehicle 1a on the horizontal plane and on the vertical surface at each measurement time as the traveling state of the vehicle 1a.
- the measurement condition generation units 33a and 33b may generate measurement condition data including the measurement time, the position of the laser radar device 21, and the directions of the horizontal component and the vertical component of the laser radar device 21.
- the data correction units 3, 3a, 3b in the point cloud data collection devices 2, 2a, 2b of the first to third embodiments may be configured as a single device, the data correction device.
- the vehicle 1 traveling on the road has been described as an example, but the vehicle 1 is not limited to the vehicle 1, and a moving body such as a drone may be used. When configured in this way, a moving object such as a drone is provided with a point cloud data collecting device 2.
- the data correction units 3, 3a, 3b in the above-described embodiment may be realized by a computer.
- a program for realizing this function may be recorded on a computer-readable recording medium, and the program recorded on the recording medium may be read by a computer system and executed.
- the term "computer system” as used herein includes hardware such as an OS and peripheral devices.
- the "computer-readable recording medium” refers to a portable medium such as a flexible disk, a magneto-optical disk, a ROM, or a CD-ROM, and a storage device such as a hard disk built in a computer system.
- a "computer-readable recording medium” is a communication line for transmitting a program via a network such as the Internet or a communication line such as a telephone line, and dynamically holds the program for a short period of time. It may also include a program that holds a program for a certain period of time, such as a volatile memory inside a computer system that is a server or a client in that case. Further, the above program may be for realizing a part of the above-mentioned functions, and may be further realized for realizing the above-mentioned functions in combination with a program already recorded in the computer system. It may be realized by using a programmable logic device such as FPGA (Field Programmable Gate Array).
- FPGA Field Programmable Gate Array
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Traffic Control Systems (AREA)
- Optical Radar Systems And Details Thereof (AREA)
- Navigation (AREA)
Abstract
In the present invention: horizontal plane position data that is more accurate than horizontal plane position data indicating the position of a moving body on a horizontal plane obtained at each observation time is acquired, or vertical plane position data indicating the position of the moving body on a vertical plane is acquired; movement trajectory data indicating the movement trajectory of the moving body is generated on the basis of the acquired highly accurate horizontal plane position data or the acquired vertical plane position data; the movement trajectory data is analyzed and the position and the movement state of the moving body for each measurement time is estimated; measurement condition data indicating the measurement condition for a laser radar device for each of the measurement times is generated on the basis of the position and the movement state of the moving body for each of the measurement times; and collected data is corrected on the basis of the measurement condition data.
Description
本発明は、点群データを測定した際の測定条件に関するデータを補正するデータ補正方法及びデータ補正装置に関する。
The present invention relates to a data correction method and a data correction device for correcting data related to measurement conditions when measuring point cloud data.
図16は、通信ネットワーク機器全般の仕様オープン化推進を図るコンソーシアムであるTIP(Telecom InfraProjcet)(主要メンバ:Facebook, Deutsche Telecom, Intel, NOKIAなど)において、mmWave Networksが提案するユースケース(例えば、非特許文献1~3参照)を参考に一部を修正して模式化した図である。mmWave Networksは、TIPのプロジェクトグループの1つであり,アンライセンス帯のミリ波無線を使用して、光ファイバの敷設より速く、かつ安価なネットワーク構築を目指している。
Figure 16 shows a use case (for example, non-use case) proposed by mmWave Networks in TIP (Telecom InfraProjcet) (main members: Facebook, Deutsche Telecom, Intel, NOKIA, etc.), which is a consortium that promotes open specifications of communication network equipment in general. It is a diagram which has been partially modified and schematicized with reference to Patent Documents 1 to 3). mmWave Networks is one of the TIP project groups, aiming to build networks faster and cheaper than laying optical fibers using unlicensed millimeter-wave radio.
図16に示すビル800,801及び住宅810,811,812などの建物において、建物のそれぞれの壁面に設置された端末局装置(以下「端末局」という。)840~844及び電柱821~826に設置された基地局装置(以下「基地局」という。)830~834は、mmWave DN(Distribution Node)と呼ばれる装置である。
In buildings such as buildings 800, 801 and houses 810, 811, 812 shown in FIG. 16, terminal station devices (hereinafter referred to as "terminal stations") 840 to 844 and electric poles 821 to 826 installed on the respective wall surfaces of the building. The installed base station devices (hereinafter referred to as "base stations") 830 to 834 are devices called mmWave DN (Distribution Node).
基地局830~834は、光ファイバ900,901により局舎(Fiber PoP(Point of Presence))850,851に備えられた通信装置と接続されている。この通信装置は、プロバイダーの通信ネットワークに接続されている。端末局840~844と、基地局830~834との間(以下「両局間」ともいう。)では、mmWave Link、すなわちミリ波無線が行われる。図16では、ミリ波無線のリンクを一点破線で示している。
The base stations 830 to 834 are connected to the communication device provided in the station building (Fiber PoP (Point of Presence)) 850, 851 by optical fibers 900, 901. This communication device is connected to the communication network of the provider. Between the terminal stations 840 to 844 and the base stations 830 to 834 (hereinafter, also referred to as "between both stations"), mmWaveLink, that is, millimeter wave radio is performed. In FIG. 16, the millimeter-wave radio link is shown by a dashed line.
基地局830~834を電柱821~826に設置し、端末局840~844を建物の壁面に設置し、両局間をミリ波無線によって通信する形態において、基地局830~834および端末局840~844を設置する候補になる位置を選定することを置局設計(以下「置局」ともいう。)という。
Base stations 830 to 834 are installed on utility poles 821 to 826, terminal stations 840 to 844 are installed on the wall of a building, and base stations 830 to 834 and terminal stations 840 to communicate in a form in which both stations are communicated by millimeter wave radio. Selecting a candidate position for installing the 844 is called station design (hereinafter also referred to as "station design").
図17は、ミリ波局の置局設計に用いる点群データを収集するMMS(Mobile Mapping System)の概略構成と、MMSが収集するデータの種類と、点群データを利用する置局支援ツールにより表示した画面500を示した図である。MMSとは、例えば、レーザレーダ702と、GPS(Global Positioning System)からの電波を受信するアンテナ703と、計測装置701とを備える車両700である。車両700の走行中に、レーザレーダ702が、測定時刻ごとにレーザ光を周囲に照射する。レーザレーダ702は、周囲に存在する建物等の測定対象物から反射光が戻ってくるまでの時間を計測し、計測した時間に基づいて測定対象物までの距離を算出する。計測装置701は、測定時刻ごとの測定対象物までの距離と、レーザ光の照射方向とを記録することにより点群データを生成する。
FIG. 17 shows the schematic configuration of the MMS (Mobile Mapping System) that collects the point cloud data used for the station placement design of the millimeter wave station, the types of data collected by the MMS, and the station placement support tool that uses the point cloud data. It is a figure which showed the displayed screen 500. The MMS is, for example, a vehicle 700 including a laser radar 702, an antenna 703 that receives radio waves from a GPS (Global Positioning System), and a measuring device 701. While the vehicle 700 is traveling, the laser radar 702 irradiates the surroundings with laser light at each measurement time. The laser radar 702 measures the time until the reflected light returns from the measurement target such as a building existing in the surroundings, and calculates the distance to the measurement target based on the measured time. The measuring device 701 generates point cloud data by recording the distance to the object to be measured at each measurement time and the irradiation direction of the laser beam.
計測装置701は、複数のGPS衛星600-1,600-2から観測時刻ごとに電波を受信する。計測装置701は、受信した電波に重畳されているデータに基づいて観測時刻ごとの車両700の位置を検出する。計測装置701は、検出した観測時刻ごとの車両700の位置の履歴から走行軌跡データ711を生成する。
The measuring device 701 receives radio waves from a plurality of GPS satellites 600-1 and 600-2 at each observation time. The measuring device 701 detects the position of the vehicle 700 for each observation time based on the data superimposed on the received radio wave. The measuring device 701 generates the traveling locus data 711 from the history of the position of the vehicle 700 for each detected observation time.
測定時刻の間隔よりも、観測時刻の間隔の方が長いため、測定時刻と、観測時刻とが一致することは少ない。そのため、まず計測装置701は、生成した走行軌跡データ711から測定時刻ごとの車両700の位置と、速度と、走行方向とを推定する。次に、計測装置701は、推定した車両700の位置から三次元空間におけるレーザレーダ702の照射位置を算出する。そして、計測装置701は、車両700の走行方向からレーザレーダ702が向いている方向を算出する。検出したレーザレーダ702の照射位置と、レーザレーダ702が向いている方向と、点群データとに基づいて、点群データに含まれる個々の点の三次元空間での座標を特定することができる。
Since the observation time interval is longer than the measurement time interval, it is unlikely that the measurement time and the observation time will match. Therefore, first, the measuring device 701 estimates the position, speed, and traveling direction of the vehicle 700 for each measurement time from the generated travel locus data 711. Next, the measuring device 701 calculates the irradiation position of the laser radar 702 in the three-dimensional space from the estimated position of the vehicle 700. Then, the measuring device 701 calculates the direction in which the laser radar 702 is facing from the traveling direction of the vehicle 700. Based on the detected irradiation position of the laser radar 702, the direction in which the laser radar 702 is facing, and the point cloud data, the coordinates of each point included in the point cloud data in the three-dimensional space can be specified. ..
計測装置701は、推定した測定時刻ごとの車両700の速度及び走行方向に基づいて、車両700が等速で走行しており、かつ直進していると判定した場合、当該測定時刻の点群データに対して、信頼度合いが高いことを示す信頼指標「高い」を付与し、点群データ(タイプA)712として分類する。これに対して、計測装置701は、推定した測定時刻ごとの車両700の速度及び走行方向により、車両700が等速で走行していないか、または、直進していないと判定した場合、当該測定時刻の点群データに対して、信頼度合いが低いことを示す信頼指標「低い」を付与し、点群データ(タイプB)713として分類する。
When the measuring device 701 determines that the vehicle 700 is traveling at a constant speed and is traveling straight based on the estimated speed and traveling direction of the vehicle 700 at each measurement time, the point group data at the measurement time is determined. A reliability index "high" indicating that the degree of reliability is high is given to the data, and the data is classified as point group data (type A) 712. On the other hand, when the measuring device 701 determines that the vehicle 700 is not traveling at a constant speed or is not traveling straight based on the estimated speed and traveling direction of the vehicle 700 at each measurement time, the measurement is performed. A reliability index "low" indicating that the degree of reliability is low is given to the point group data at the time, and the point group data (type B) 713 is classified.
車両700が等速で走行していない場合とは、例えば、加速や減速をしている場合であり、車両700が直進していない場合とは、例えば、右左折を含む屈曲した走行をしている場合である。信頼指標「低い」を付与する理由は、加速や減速、または、右左折を含む屈曲した走行をしている場合、車両700の位置と、速度と、走行方向の推定精度が低くなるためである。なお、信頼指標「低い」ではなく、点群データに信頼性が無く利用することができない場合には、信頼指標「無い」を付与することもある。
When the vehicle 700 is not traveling at a constant speed, for example, it is accelerating or decelerating, and when the vehicle 700 is not traveling straight, for example, it is traveling in a curved manner including a right / left turn. If there is. The reason why the reliability index "low" is given is that the position, speed, and estimation accuracy of the traveling direction of the vehicle 700 are lowered when the vehicle is accelerating, decelerating, or traveling in a curved manner including right / left turn. .. If the point cloud data is not reliable and cannot be used instead of the reliability index "low", the reliability index "not" may be given.
ここで、信頼指標とは、置局支援ツールにおいて点群データを利用する際に、利用の優先度を示す指標である。例えば、「無い」が付与されている点群データについては利用せず、「低い」が付与されている点群データを利用する際には、同一の位置を示す「高い」が付与されている他の点群データが存在しない場合に利用し、「高い」が付与されている点群データを優先して利用するような処理が行われる。
Here, the reliability index is an index showing the priority of use when using the point cloud data in the station support tool. For example, the point cloud data to which "none" is given is not used, and when the point cloud data to which "low" is given is used, "high" indicating the same position is given. It is used when other point cloud data does not exist, and processing is performed so that the point cloud data to which "high" is given is preferentially used.
置局支援ツールは、点群データを利用して、画面500に示す基地局501を設置する位置と、端末局511~514の各々を設置する位置との間の見通しの有無を検出する。例えば、置局支援ツールは、基地局501の位置から端末局511~514の各々を設置する位置との間に見通し検出線を設定し、見通し検出線上に、建物の形状を示す点群データが存在するか否かにより見通しの有無を検出する。
The station station support tool uses the point cloud data to detect the presence or absence of a line-of-sight between the position where the base station 501 shown on the screen 500 is installed and the position where each of the terminal stations 511 to 514 is installed. For example, the station support tool sets a line-of-sight detection line between the position of the base station 501 and the position where each of the terminal stations 511 to 514 is installed, and point cloud data indicating the shape of the building is displayed on the line-of-sight detection line. The presence or absence of a line of sight is detected depending on whether or not it exists.
置局支援ツールは、画面500に、地図データを表示する。例えば、符号521,522が示す実線で囲まれる領域は、地図データに示される建物等が存在する区画であり、区画の間の空白が道路である。置局支援ツールは、走行軌跡データ711に基づいて、地図データ上に車両700の走行軌跡540を表示する。走行軌跡540に沿って、例えば、符号531,532で示す実線の矢印に沿った一定の幅の領域(以下「領域A」という。)が点群データ(タイプA)712が存在する箇所になる。走行軌跡540に沿って、例えば、符号533,534で示す点線に沿った一定の幅の領域(以下「領域B」という。)が点群データ(タイプB)713が存在する箇所になる。
The station support tool displays map data on the screen 500. For example, the area surrounded by the solid line indicated by the reference numerals 521 and 522 is a section in which a building or the like shown in the map data exists, and the blank space between the sections is a road. The station station support tool displays the travel locus 540 of the vehicle 700 on the map data based on the travel locus data 711. Along the travel locus 540, for example, a region having a certain width along the solid arrow indicated by reference numerals 531,532 (hereinafter referred to as “region A”) is a place where the point cloud data (type A) 712 exists. .. Along the travel locus 540, for example, a region having a certain width along the dotted line indicated by reference numeral 533, 534 (hereinafter referred to as “region B”) is a place where the point cloud data (type B) 713 exists.
画面500には、複数の領域Aの模様の箇所と、複数の領域Bの模様の箇所とが示されている。領域Aの模様の箇所では、走行軌跡データ711が示す軌跡が直線である。これに対して、領域Bの模様の箇所では、走行軌跡データ711が示す軌跡が屈曲していることが分かる。
The screen 500 shows a portion of the pattern of the plurality of areas A and a portion of the pattern of the plurality of areas B. In the pattern portion of the region A, the locus indicated by the traveling locus data 711 is a straight line. On the other hand, it can be seen that the locus indicated by the traveling locus data 711 is bent at the portion of the pattern in the region B.
図17に示した点群データ(タイプB)713として分類された点群データに対して信頼指標「低い」または「無い」を付与する理由は、上記したように、加速や減速、または、右左折を含む屈曲した走行をしている場合、車両700の位置と、速度と、走行方向の推定精度が低くなるためである。この理由の具体例を、図18及び図19に示す。
As described above, the reason for assigning the confidence index "low" or "none" to the point cloud data classified as the point cloud data (type B) 713 shown in FIG. 17 is acceleration, deceleration, or right. This is because the position, speed, and estimation accuracy of the traveling direction of the vehicle 700 are lowered when the vehicle is traveling in a curved manner including a left turn. Specific examples of this reason are shown in FIGS. 18 and 19.
図18は、直線の片側二車線の道路の一方の方向の道路の付近である道路550と、歩道570とを上空から見た図である。なお、符号552で示すラインは、対向車線との境界を示すセンターラインである。
FIG. 18 is a view of the road 550 and the sidewalk 570, which are in the vicinity of the road in one direction of the straight two-lane road on one side, from the sky. The line indicated by reference numeral 552 is a center line indicating a boundary with an oncoming lane.
符号541で示す二重線の矢印は、MMSである車両700が走行した軌跡であり、以下、走行軌跡541という。車両700は、走行軌跡541の矢印が示す右方向に走行している。道路550には、歩道570に寄せて車両750が停車している。車両700では、走行レーン561を走行している途中で、停車している車両750を避けるために、走行レーン561と追越レーン562を区切るライン551を超えて、一時的に追越レーン562を走行し、その後、走行レーン561に戻る運転操作が行われている。
The double-lined arrow indicated by the reference numeral 541 is a locus on which the vehicle 700, which is an MMS, has traveled, and is hereinafter referred to as a travel locus 541. The vehicle 700 is traveling in the right direction indicated by the arrow of the traveling locus 541. On the road 550, the vehicle 750 is stopped near the sidewalk 570. In the vehicle 700, in order to avoid the stopped vehicle 750 while traveling in the traveling lane 561, the overtaking lane 562 temporarily crosses the line 551 that separates the traveling lane 561 and the overtaking lane 562. A driving operation is performed in which the vehicle travels and then returns to the traveling lane 561.
このような運転操作が行われているため、車両700の走行軌跡541は、2か所において屈曲した状態になっている。走行軌跡541に沿って示している複数の点線は、車両700に搭載されたレーザレーダ702が、測定時刻ごとに照射したレーザ光の照射方向を示したレーザ照射ラインである。車両700が、走行レーン561及び追越レーン562を一定の速度で、直線に走行している場合、すなわち、等速直進している場合には、レーザ照射ラインは、走行方向に対して垂直になり、等間隔で平行な規則的な並びになる。
Since such a driving operation is performed, the traveling locus 541 of the vehicle 700 is in a bent state at two places. The plurality of dotted lines shown along the traveling locus 541 are laser irradiation lines indicating the irradiation direction of the laser light emitted by the laser radar 702 mounted on the vehicle 700 at each measurement time. When the vehicle 700 is traveling in a straight line at a constant speed in the traveling lane 561 and the overtaking lane 562, that is, when the vehicle is traveling straight at a constant speed, the laser irradiation line is perpendicular to the traveling direction. It becomes a regular arrangement parallel to each other at equal intervals.
これに対して、車両700が走行レーン561から追越レーン562に移動し、追越レーン562から走行レーン561に戻る符号401,402によって示される区間においては、レーザ照射ラインは、平行ではなく乱れが生じることになり、更に等速でない場合、等間隔でもなくなる。
On the other hand, in the section indicated by the reference numerals 401, 402 in which the vehicle 700 moves from the traveling lane 561 to the overtaking lane 562 and returns from the overtaking lane 562 to the traveling lane 561, the laser irradiation lines are not parallel but disturbed. Will occur, and if the speed is not constant, it will not be evenly spaced.
図19は、片側一車線の道路が交差した交差点の部分において、MMSである車両700が走行した走行軌跡542を示した図である。図18と同様に図19においても測定時刻ごとのレーザ照射ラインを点線で示している。符号580-1,580-2で示すラインは、センターラインであり、符号581-1~581-4で示すラインは、車道と路側帯の境界を示すラインである。車両700では、走行軌跡542の矢印が示すように、図19の下方から上方に走行し、交差点において右折する前にセンターライン580-1側に近寄り、その後、交差点を右折して右方向に直進する運転操作が行われている。
FIG. 19 is a diagram showing a travel locus 542 in which a vehicle 700, which is an MMS, travels at an intersection where roads with one lane on each side intersect. Similar to FIG. 18, in FIG. 19, the laser irradiation line for each measurement time is shown by a dotted line. The lines indicated by reference numerals 580-1 and 580-2 are center lines, and the lines indicated by reference numerals 581-1 to 581-4 are lines indicating the boundary between the roadway and the roadside zone. In the vehicle 700, as indicated by the arrow of the traveling locus 542, the vehicle travels upward from the lower part of FIG. 19, approaches the center line 580-1 side before turning right at the intersection, and then turns right at the intersection and goes straight to the right. The driving operation is being performed.
このような運転操作が行われているため、車両700の走行軌跡542は、センターライン580-1側に近寄る区間403の間及び交差点を右折する区間404においてレーザ照射ラインは、平行ではなく乱れが生じて不規則な状態になり、更に等速でない場合、等間隔にもならない。右折した後は、車両700は、一定の速度で直進しているので、レーザ照射ラインは、走行方向に対して垂直になり、等間隔で平行な規則的な並びになる。
Due to such a driving operation, the traveling locus 542 of the vehicle 700 is not parallel but turbulent in the section 403 approaching the center line 580-1 side and in the section 404 turning right at the intersection. If it occurs and becomes irregular, and if it is not constant velocity, it will not be evenly spaced. After making a right turn, the vehicle 700 is traveling straight at a constant speed, so that the laser irradiation lines are perpendicular to the traveling direction and are arranged in a regular arrangement parallel to each other at equal intervals.
図18及び図19に示したように、走行レーンの変更や、交差点での右折や左折など、直進しない場合、レーザ照射ラインは、平行でなくなり、更に等速でない場合、等間隔にもならない。このように、レーザ照射ラインが不規則に乱れると、点群データに含まれる個々の点が存在する空間の形状やサイズを推定するのが困難、または、推定ができなくなる。そのため、このようにレーザ照射ラインが不規則に乱れた際の点群データについては、信頼度合いが低下するため、信頼指標「低い」か、または、信頼指標「無い」を付与することになる。
As shown in FIGS. 18 and 19, the laser irradiation lines are not parallel when the traveling lane is changed, or when the vehicle does not go straight, such as when turning right or left at an intersection, and when the speed is not constant, the laser irradiation lines are not evenly spaced. When the laser irradiation line is irregularly disturbed in this way, it is difficult or impossible to estimate the shape and size of the space in which the individual points included in the point cloud data exist. Therefore, for the point cloud data when the laser irradiation line is irregularly disturbed in this way, the reliability level is lowered, so that the reliability index "low" or the reliability index "none" is given.
このようなレーザ照射ラインが乱れる現象は、図18及び図19に示した水平面に限られず、例えば、車両700が、平地から坂道を上ったり、坂道から平地に戻ったり、凹凸のあるような道路を走行したりする場合にも発生する。
Such a phenomenon that the laser irradiation line is disturbed is not limited to the horizontal plane shown in FIGS. 18 and 19, and for example, the vehicle 700 climbs a slope from a flat ground, returns from a slope to a flat ground, or has irregularities. It also occurs when driving on the road.
上記事情に鑑み、本発明は、レーザ照射ラインの乱れによって信頼度合いが低下した点群データを利用可能にすることができる技術の提供を目的としている。
In view of the above circumstances, an object of the present invention is to provide a technique capable of making available point cloud data whose reliability is lowered due to disturbance of a laser irradiation line.
本発明の一態様は、移動体に搭載されたレーザレーダ装置が、測定時刻ごとにレーザ光を照射することにより測定対象物までの距離を計測して点群データを生成する際に前記点群データに対応付けて生成される収集データであって観測時刻ごとに得られる前記移動体の水平面上での位置を示す水平面位置データから推定される前記レーザレーダ装置の測定条件を示す収集データを補正するデータ補正方法であって、前記観測時刻ごとに得られる前記水平面位置データよりも高精度の水平面位置データを取得するか、または、前記移動体の鉛直面上での位置を示す鉛直面位置データを取得し、取得した前記高精度の水平面位置データ、または、前記鉛直面位置データに基づいて、前記移動体の移動軌跡を示す移動軌跡データを生成する移動軌跡データ生成データ生成ステップと、前記移動軌跡データを解析して、前記測定時刻ごとの前記移動体の位置及び移動状態を推定する移動軌跡解析ステップと、前記測定時刻ごとの前記移動体の位置及び移動状態に基づいて、前記測定時刻ごとの前記レーザレーダ装置の測定条件を示す測定条件データを生成する測定条件生成ステップと、前記測定条件データに基づいて、前記収集データを補正する補正処理ステップと、を含むデータ補正方法である。
One aspect of the present invention is the point group when the laser radar device mounted on the moving body measures the distance to the object to be measured by irradiating the laser light at each measurement time and generates point group data. The collected data generated in association with the data and indicating the measurement conditions of the laser radar device estimated from the horizontal plane position data indicating the position of the moving object on the horizontal plane obtained at each observation time is corrected. This is a data correction method for acquiring horizontal plane position data with higher accuracy than the horizontal plane position data obtained at each observation time, or vertical plane position data indicating the position of the moving body on the vertical plane. The movement trajectory data generation data generation step and the movement For each measurement time, based on the movement locus analysis step that analyzes the locus data and estimates the position and movement state of the moving body at each measurement time, and the position and movement state of the moving body at each measurement time. It is a data correction method including a measurement condition generation step for generating measurement condition data indicating the measurement conditions of the laser radar device, and a correction processing step for correcting the collected data based on the measurement condition data.
本発明の一態様は、移動体に搭載されたレーザレーダ装置が、測定時刻ごとにレーザ光を照射することにより測定対象物までの距離を計測して点群データを生成する際に前記点群データに対応付けて生成される収集データであって観測時刻ごとに得られる前記移動体の水平面上での位置を示す水平面位置データから推定される前記レーザレーダ装置の測定条件を示す収集データを補正するデータ補正装置であって、前記観測時刻ごとに得られる前記水平面位置データよりも高精度の水平面位置データを取得するか、または、前記移動体の鉛直面上での位置を示す鉛直面位置データを取得し、取得した前記高精度の水平面位置データ、または、前記鉛直面位置データに基づいて、前記移動体の移動軌跡を示す移動軌跡データを生成する移動軌跡データ生成部と、前記移動軌跡データを解析して、前記測定時刻ごとの前記移動体の位置及び移動状態を推定する移動軌跡解析部と、前記測定時刻ごとの前記移動体の位置及び移動状態に基づいて、前記測定時刻ごとの前記レーザレーダ装置の測定条件を示す測定条件データを生成する測定条件生成部と、前記測定条件データに基づいて、前記収集データを補正する補正処理部と、を備えるデータ補正装置である。
One aspect of the present invention is the point group when the laser radar device mounted on the moving body measures the distance to the object to be measured by irradiating the laser light at each measurement time and generates point group data. The collected data generated in association with the data and indicating the measurement conditions of the laser radar device estimated from the horizontal plane position data indicating the position of the moving object on the horizontal plane obtained at each observation time is corrected. This is a data correction device that acquires horizontal plane position data with higher accuracy than the horizontal plane position data obtained at each observation time, or vertical plane position data indicating the position of the moving body on the vertical plane. The movement locus data generation unit that generates the movement locus data indicating the movement locus of the moving body based on the acquired high-precision horizontal plane position data or the vertical plane position data, and the movement locus data. The movement locus analysis unit that estimates the position and the moving state of the moving body at each measurement time, and the movement locus analysis unit that estimates the position and the moving state of the moving body at each measurement time, and the said at each measurement time based on the position and the moving state of the moving body at each measurement time. It is a data correction device including a measurement condition generation unit that generates measurement condition data indicating measurement conditions of a laser radar device, and a correction processing unit that corrects the collected data based on the measurement condition data.
本発明により、レーザ照射ラインの乱れによって信頼度合いが低下した点群データを利用可能にすることができる。
According to the present invention, it is possible to make available point cloud data whose reliability is lowered due to the disturbance of the laser irradiation line.
(第1の実施形態)
以下、本発明の実施形態について図面を参照して説明する。図1は、第1の実施形態における点群データ収集システムαの構成を示すブロック図である。点群データ収集システムαは、点群データ収集装置2を備えた車両1と、複数のGPS衛星10-1,10-2及び準天頂衛星11とを備えている。車両1は、例えば、自動車のような移動体であり、上記したMMSに相当する。 (First Embodiment)
Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing a configuration of a point cloud data collection system α according to the first embodiment. The point cloud data collection system α includes avehicle 1 equipped with a point cloud data collection device 2, a plurality of GPS satellites 10-1, 10-2, and a quasi-zenith satellite 11. The vehicle 1 is, for example, a moving body such as an automobile, and corresponds to the above-mentioned MMS.
以下、本発明の実施形態について図面を参照して説明する。図1は、第1の実施形態における点群データ収集システムαの構成を示すブロック図である。点群データ収集システムαは、点群データ収集装置2を備えた車両1と、複数のGPS衛星10-1,10-2及び準天頂衛星11とを備えている。車両1は、例えば、自動車のような移動体であり、上記したMMSに相当する。 (First Embodiment)
Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing a configuration of a point cloud data collection system α according to the first embodiment. The point cloud data collection system α includes a
図1では、2台のGPS衛星10-1,10-2を一例として示しているが、実際には、2台を超える数が運用されている。図1では、1台の準天頂衛星11を一例として示しているが、将来的には、複数の準天頂衛星11が運用される予定である。車両1が走行している位置に応じて見通しの状態が変化するため、車両1の走行中に電波を受信可能なGPS衛星10-1,10-2及び準天頂衛星11の数は変化する。
In FIG. 1, two GPS satellites 10-1 and 10-2 are shown as an example, but in reality, more than two GPS satellites are in operation. In FIG. 1, one quasi-zenith satellite 11 is shown as an example, but in the future, a plurality of quasi-zenith satellites 11 are scheduled to be operated. Since the line-of-sight state changes depending on the position where the vehicle 1 is traveling, the number of GPS satellites 10-1, 10-2 and the quasi-zenith satellite 11 that can receive radio waves while the vehicle 1 is traveling changes.
第1の実施形態では、GPS衛星10-1,10-2から受信する電波に重畳されているデータに加えて、準天頂衛星11から受信する電波に重畳されているデータを利用する。ここで、準天頂衛星11の概要について説明する。近年、準天頂衛星11(以下「QZS」(Quasi-Zenith Satellite)ともいう。)を主体として構成したQZSS(Quasi-Zenith Satellite System)を利用することにより、GPSを利用した場合よりも高い精度で位置を検出する試みがなされている。
In the first embodiment, in addition to the data superimposed on the radio waves received from the GPS satellites 10-1 and 10-2, the data superimposed on the radio waves received from the quasi-zenith satellite 11 is used. Here, the outline of the quasi-zenith satellite 11 will be described. In recent years, by using the QZSS (Quasi-Zenith Satellite System), which is mainly composed of the Quasi-Zenith Satellite 11 (hereinafter also referred to as "QZS" (Quasi-Zenith Satellite)), the accuracy is higher than when GPS is used. Attempts have been made to detect the position.
例えば、非特許文献4の7ページには、GPS補完機能効果の実験システム構成の例が示されている。この実験システムでは、移動測位器であるMMSに準天頂衛星11に対応する受信機を搭載し、準天頂衛星11とGPS衛星10-1,10-2の受信ログとともに、リファレンスとなるMMSの走行軌跡を収集している。非特許文献4では、実験システムによりGPS衛星10-1,10-2に準天頂衛星11からの情報を加えた測位演算を実施することで「補完」機能を実現したこと、準天頂衛星11からの情報が追加されたことによる都市部での移動体測位性能の改善効果の検証が示されている。
For example, page 7 of Non-Patent Document 4 shows an example of an experimental system configuration for a GPS complementary function effect. In this experimental system, a receiver corresponding to the quasi-zenith satellite 11 is mounted on the MMS, which is a mobile positioning device, and the reference MMS travels along with the reception logs of the quasi-zenith satellite 11 and GPS satellites 10-1 and 10-2. Collecting trajectories. In Non-Patent Document 4, the "complementary" function was realized by performing the positioning calculation by adding the information from the quasi-zenith satellite 11 to the GPS satellites 10-1 and 10-2 by the experimental system, from the quasi-zenith satellite 11. The verification of the improvement effect of the mobile body positioning performance in the urban area by the addition of the information of is shown.
非特許文献5の16ページには、MMSに測位端末を搭載し、林道にてリアルタイム移動体測位して、利用実証用センチメータ級測位補強を実験した例が示されており、当該実験において、FIX率79%、測位精度2.4cmの結果が得られ、結果が良好であることが示されている。
On page 16 of Non-Patent Document 5, an example is shown in which a positioning terminal is mounted on an MMS, real-time mobile positioning is performed on a forest road, and a centimeter-class positioning reinforcement for use verification is conducted. Results with a FIX rate of 79% and a positioning accuracy of 2.4 cm were obtained, indicating that the results are good.
非特許文献6の6ページの図6に示された「都市部における精度評価」によれば、走行軌跡の誤差が(1)GPSのみによる測位で1.28mであった地点において(2)QZS+GPSによる測位では0.21mに改善したことが示されている。非特許文献6の6ページの表6の「QZSによる測位性能の向上」によれば、GPSのみによる測位と比較した場合、QZSを加えることにより測位率の改善度1.7倍、3D(Three-Dimensions)の精度が169cmから45cmに増加することが示されている。
According to the "accuracy evaluation in urban areas" shown in FIG. 6 on page 6 of Non-Patent Document 6, at the point where the error of the traveling locus was (1) 1.28 m in the positioning by GPS alone, (2) QZS + GPS. It is shown that the positioning by is improved to 0.21 m. According to "Improvement of positioning performance by QZS" in Table 6 on page 6 of Non-Patent Document 6, the degree of improvement of positioning rate by adding QZS is 1.7 times and 3D (Three) when compared with positioning by GPS alone. -Dimensions) accuracy has been shown to increase from 169 cm to 45 cm.
GPS衛星10-1,10-2のみによる測位の精度は、精々数メートル~数十メートルである。これに対して、GPS衛星10-1,10-2と準天頂衛星11とを用いた場合には、非特許文献5に示される林道を走行する良い環境では、2.4cmの精度が得られており、非特許文献6に示される都市部でのビルの谷間となる道路を走行する悪い環境であっても、0.21mの精度が得られていることから測位の精度は、おおよそ十数センチメートル~数センチメートルに向上することになる。
The accuracy of positioning using only GPS satellites 10-1 and 10-2 is at most several meters to several tens of meters. On the other hand, when the GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11 are used, an accuracy of 2.4 cm can be obtained in a good environment for traveling on a forest road shown in Non-Patent Document 5. Even in a bad environment of driving on a road in a valley of buildings in an urban area shown in Non-Patent Document 6, the accuracy of positioning is about ten and several because the accuracy of 0.21 m is obtained. It will improve from centimeters to several centimeters.
図1に戻り、点群データ収集装置2は、レーザレーダ装置21、衛星電波受信用アンテナ22、情報受信部23、走行状態計測部24、記憶部25、収集データ生成部26及びデータ補正部3を備える。
Returning to FIG. 1, the point cloud data collecting device 2 includes a laser radar device 21, a satellite radio wave receiving antenna 22, an information receiving unit 23, a traveling state measuring unit 24, a storage unit 25, a collected data generation unit 26, and a data correction unit 3. To prepare for.
レーザレーダ装置21は、例えば、回転軸を中心にレーザ光の照射穴を360°回転させてレーザ光を照射可能になっており、照射されたレーザ光が形成する面と、回転軸とが垂直に交わるように構成されている。以下、レーザレーダ装置21の回転軸が向いている方向をレーザレーダ装置21の方向という。レーザレーダ装置21は、照射されたレーザ光が形成する面が、車両1の走行方向に対して、垂直になるように車両1の天部に固定して搭載される。したがって、図1に示すように、レーザレーダ装置21の方向は、符号4の矢印で示す方向となり、車両1の走行方向と180°逆の向きになる。
The laser radar device 21 can irradiate the laser beam by rotating the irradiation hole of the laser beam 360 ° around the rotation axis, for example, and the surface formed by the irradiated laser beam and the rotation axis are perpendicular to each other. It is configured to intersect with. Hereinafter, the direction in which the rotation axis of the laser radar device 21 faces is referred to as the direction of the laser radar device 21. The laser radar device 21 is fixedly mounted on the top of the vehicle 1 so that the surface formed by the irradiated laser beam is perpendicular to the traveling direction of the vehicle 1. Therefore, as shown in FIG. 1, the direction of the laser radar device 21 is the direction indicated by the arrow of reference numeral 4, and is 180 ° opposite to the traveling direction of the vehicle 1.
レーザレーダ装置21は、測定時刻ごとにレーザ光を周囲に照射する。レーザレーダ装置21は、周囲に存在する建物等の測定対象物から反射光が戻ってくるまでの時間を計測し、計測した時間に基づいて測定対象物までの距離を算出する。なお、測定時刻の間隔は、一定の時間であり、例えば、0.005秒程度の時間である。レーザレーダ装置21は、当該測定時刻の間隔の間に、例えば、200[Hz]程度の回転速度で回転する。レーザレーダ装置21は、測定時刻ごとの測定対象物までの距離と、レーザ光の照射方向とを対応付けて点群データ43を生成し、生成した点群データ43を記憶部25に書き込む。ここで、レーザ光の照射穴が、例えば、レーザレーダ装置21の方向に向かって、時計回りで回転する場合、レーザ光の照射角度の「0°」を上空に向かう方向、すなわち真上の方向とすると、レーザ光の照射角度は、時計回りで角度が増加し、図1の紙面の表面から裏面に向かう方向、すなわち車両1の走行方向に対して左の方向が「90°」になり、地面に向かう方向、すなわち真下の方向が「180°」となり、図1の裏面から表面に向かう方向、すなわち車両1の走行方向に対して右の方向が「270°」になる。現在の高精度なレーザレーダ装置21は、1秒間に約100万点程度(100万点/秒)の計測位置を計測することができる。なお、説明を簡単にするため、本実施形態では、レーザレーダ装置内21は、1秒間に72万点(72万/秒(≒200[Hz]×360[°]÷0.1[°]))の計測位置を計測することができるものとする。
The laser radar device 21 irradiates the surroundings with laser light at each measurement time. The laser radar device 21 measures the time until the reflected light returns from the measurement target such as a building existing in the surroundings, and calculates the distance to the measurement target based on the measured time. The interval of the measurement time is a constant time, for example, about 0.005 seconds. The laser radar device 21 rotates at a rotation speed of, for example, about 200 [Hz] during the interval of the measurement time. The laser radar device 21 generates point cloud data 43 in association with the distance to the object to be measured at each measurement time and the irradiation direction of the laser beam, and writes the generated point cloud data 43 in the storage unit 25. Here, when the irradiation hole of the laser beam rotates clockwise, for example, in the direction of the laser radar device 21, the direction in which the irradiation angle of the laser beam "0 °" is directed toward the sky, that is, the direction directly above. Then, the irradiation angle of the laser beam increases clockwise, and the direction from the front surface to the back surface of FIG. 1, that is, the left direction with respect to the traveling direction of the vehicle 1 becomes "90 °". The direction toward the ground, that is, the direction directly below is "180 °", and the direction from the back surface to the front surface of FIG. 1, that is, the direction to the right of the traveling direction of the vehicle 1 is "270 °". The current high-precision laser radar device 21 can measure measurement positions of about 1 million points (1 million points / second) per second. For the sake of simplicity, in the present embodiment, the laser radar device 21 has 720,000 points per second (720,000 / sec (≈200 [Hz] × 360 [°] ÷ 0.1 [°]]. )) It shall be possible to measure the measurement position.
衛星電波受信用アンテナ22は、GPS衛星10-1,10-2及び準天頂衛星11からの電波を受信する。情報受信部23は、GPS衛星10-1,10-2及び準天頂衛星11の受信機や測位端末に相当する。情報受信部23は、観測時刻ごとに、衛星電波受信用アンテナ22がGPS衛星10-1,10-2から受信した電波に重畳されているデータを検出し、検出したデータから観測時刻における車両1の位置を算出し、算出した車両1の位置と観測時刻とを関連付けてGPS観測データ40として記憶部25に書き込む。情報受信部23は、観測時刻ごとに、衛星電波受信用アンテナ22が準天頂衛星11から受信した電波に重畳されているデータを検出し、検出したデータから観測時刻における車両1の位置を算出し、算出した車両1の位置と観測時刻とを関連付けて準天頂衛星観測データ41として記憶部25に書き込む。GPS衛星10-1,10-2及び準天頂衛星11から電波を受信する観測時刻の間隔は、一定の時間であり、例えば、1秒である。
The satellite radio wave receiving antenna 22 receives radio waves from GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11. The information receiving unit 23 corresponds to a receiver or a positioning terminal of the GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11. The information receiving unit 23 detects the data superimposed on the radio waves received from the GPS satellites 10-1 and 10-2 by the satellite radio wave receiving antenna 22 at each observation time, and the vehicle 1 at the observation time from the detected data. The position of the GPS observation data 40 is calculated, and the calculated position of the vehicle 1 is associated with the observation time and written in the storage unit 25 as GPS observation data 40. The information receiving unit 23 detects the data superimposed on the radio waves received from the quasi-zenith satellite 11 by the satellite radio wave receiving antenna 22 at each observation time, and calculates the position of the vehicle 1 at the observation time from the detected data. , The calculated position of the vehicle 1 and the observation time are associated with each other and written in the storage unit 25 as quasi-zenith satellite observation data 41. The interval of the observation time for receiving radio waves from the GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11 is a fixed time, for example, 1 second.
走行状態計測部24は、例えば、車両1のタイヤの回転数から速度を検出する車速センサと、車両1のステアリングの操舵角を検出するステアリングセンサとに接続する。車速センサとステアリングセンサは、車両1の内部に備えられている。走行状態計測部24は、車速センサから得られるデータに基づいて、測定時刻ごとの車両1の速度を計測する。走行状態計測部24は、ステアリングセンサから得られるデータに基づいて測定時刻ごとのステアリングの操舵角を計測する。走行状態計測部24は、ステアリングの操舵角から測定時刻ごとの車両1の水平面上での走行方向を算出する。
The traveling state measuring unit 24 is connected to, for example, a vehicle speed sensor that detects the speed from the rotation speed of the tire of the vehicle 1 and a steering sensor that detects the steering angle of the steering of the vehicle 1. The vehicle speed sensor and the steering sensor are provided inside the vehicle 1. The traveling state measuring unit 24 measures the speed of the vehicle 1 at each measurement time based on the data obtained from the vehicle speed sensor. The traveling state measuring unit 24 measures the steering angle of the steering at each measurement time based on the data obtained from the steering sensor. The traveling state measuring unit 24 calculates the traveling direction of the vehicle 1 on the horizontal plane for each measurement time from the steering angle of the steering.
走行状態計測部24は、測定時刻ごとの車両1の速度を示す車速データ42-1と、測定時刻ごとの車両1の水平面上での走行方向を示す走行方向データ42-2とを含む走行状態データ42を生成する。走行状態計測部24は、生成した走行状態データ42を記憶部25に書き込む。
The traveling state measuring unit 24 includes a traveling state data 42-1 indicating the speed of the vehicle 1 for each measurement time and a traveling direction data 42-2 indicating the traveling direction of the vehicle 1 on the horizontal plane for each measurement time. Generate data 42. The traveling state measuring unit 24 writes the generated traveling state data 42 in the storage unit 25.
記憶部25は、図2に示すように、上記したGPS観測データ40、準天頂衛星観測データ41、走行状態データ42及び点群データ43を記憶する。記憶部25は、収集データ生成部26が、記憶部25が記憶するデータに基づいて生成する収集データ44を記憶する。
As shown in FIG. 2, the storage unit 25 stores the GPS observation data 40, the quasi-zenith satellite observation data 41, the traveling state data 42, and the point cloud data 43 described above. The storage unit 25 stores the collected data 44 generated by the collected data generation unit 26 based on the data stored in the storage unit 25.
収集データ生成部26は、記憶部25が記憶するGPS観測データ40と、車速データ42-1と、走行方向データ42-2とに基づいて、測定時刻ごとの車両1の水平面上での位置と、速度と、水平面上での走行方向と、測定位置間隔とを推定する。ここで、車両1の水平面上での位置とは、例えば、緯度、経度で示される二次元座標で示される位置ある。ある測定時刻における測定位置間隔とは、当該ある測定時刻の車両1の位置と、当該ある測定時刻の直前の測定時刻の車両1の位置との間の距離である。
The collected data generation unit 26 determines the position of the vehicle 1 on the horizontal plane at each measurement time based on the GPS observation data 40 stored by the storage unit 25, the vehicle speed data 42-1 and the traveling direction data 42-2. , Estimate the speed, the traveling direction on the horizontal plane, and the measurement position interval. Here, the position of the vehicle 1 on the horizontal plane is, for example, a position indicated by two-dimensional coordinates indicated by latitude and longitude. The measurement position interval at a certain measurement time is the distance between the position of the vehicle 1 at the certain measurement time and the position of the vehicle 1 at the measurement time immediately before the certain measurement time.
収集データ生成部26は、推定した測定時刻ごとの車両1の水平面上での位置と、車両1において固定設置されているレーザレーダ装置21の位置関係とに基づいて、レーザレーダ装置21の三次元空間における位置を算出する。
The collected data generation unit 26 has three dimensions of the laser radar device 21 based on the position of the vehicle 1 on the horizontal plane at each estimated measurement time and the positional relationship of the laser radar device 21 fixedly installed in the vehicle 1. Calculate the position in space.
収集データ生成部26は、推定した測定時刻ごとの車両1の水平面上での走行方向の180°逆の向きを測定時刻ごとのレーザレーダ装置21の水平面上での方向とする。上記したように、照射されたレーザ光が形成する面が、車両1の走行方向に対して、垂直になるように車両1の天部に固定してレーザレーダ装置21が搭載されている。そのため、レーザレーダ装置21の回転軸が、常に水平面に対して一定になるので、収集データ生成部26は、レーザレーダ装置21の鉛直面上での方向を常に「0°」とする。
The collected data generation unit 26 sets the direction 180 ° opposite to the traveling direction of the vehicle 1 on the horizontal plane at each estimated measurement time as the direction on the horizontal plane of the laser radar device 21 at each measurement time. As described above, the laser radar device 21 is mounted by fixing the surface formed by the irradiated laser beam to the top of the vehicle 1 so as to be perpendicular to the traveling direction of the vehicle 1. Therefore, since the rotation axis of the laser radar device 21 is always constant with respect to the horizontal plane, the collected data generation unit 26 always sets the direction of the laser radar device 21 on the vertical plane to "0 °".
収集データ生成部26は、測定時刻の各々と、測定時刻の各々に対応するレーザレーダ装置21の位置、測定時刻の各々に対応するレーザレーダ装置21の水平面及び鉛直面上での方向、測定時刻の各々に対応する測定位置間隔、測定時刻の各々に対応する車両1の速度及び測定時刻の各々に対応する車両1の走行方向を対応付けて収集データ44を生成する。なお、車両1の走行方向は、水平成分と、鉛直成分とによって特定される方向であるが、第1の実施形態では、車両1の水平面上での走行方向のみを求めているため、鉛直成分は含まれないことになる。
The collected data generation unit 26 includes each of the measurement times, the position of the laser radar device 21 corresponding to each of the measurement times, the direction of the laser radar device 21 corresponding to each of the measurement times on the horizontal plane and the vertical plane, and the measurement time. The collected data 44 is generated by associating the measurement position interval corresponding to each of the above, the speed of the vehicle 1 corresponding to each of the measurement times, and the traveling direction of the vehicle 1 corresponding to each of the measurement times. The traveling direction of the vehicle 1 is a direction specified by a horizontal component and a vertical component. However, in the first embodiment, since only the traveling direction of the vehicle 1 on the horizontal plane is obtained, the vertical component is obtained. Will not be included.
収集データ生成部26は、生成した収集データ44を記憶部25に書き込む。収集データ生成部26は、記憶部25が記憶する測定時刻ごとの点群データ43の各々に対して信頼指標を付与する。
The collected data generation unit 26 writes the generated collected data 44 to the storage unit 25. The collected data generation unit 26 assigns a reliability index to each of the point cloud data 43 for each measurement time stored in the storage unit 25.
データ補正部3は、走行軌跡データ生成部31、走行軌跡解析部32、測定条件生成部33、道路交通情報取得部34、走行軌跡データ正常判定部35及び補正処理部36を備える。走行軌跡データ生成部31は、記憶部25が記憶するGPS観測データ40と、準天頂衛星観測データ41とに基づいて、車両1の走行軌跡を示す走行軌跡データを生成する。走行軌跡データ生成部31は、移動軌跡データ生成部の一態様である。
The data correction unit 3 includes a travel locus data generation unit 31, a travel locus analysis unit 32, a measurement condition generation unit 33, a road traffic information acquisition unit 34, a travel locus data normality determination unit 35, and a correction processing unit 36. The travel locus data generation unit 31 generates travel locus data indicating the travel locus of the vehicle 1 based on the GPS observation data 40 stored in the storage unit 25 and the quasi-zenith satellite observation data 41. The travel locus data generation unit 31 is an aspect of the travel locus data generation unit.
走行軌跡解析部32は、走行軌跡データ生成部31が生成した走行軌跡データに基づいて、測定時刻ごとの車両1の水平面上での位置と、速度と、水平面上での走行方向と、測定位置間隔とを推定する。走行軌跡解析部32は、測定時刻ごとに、推定した車両1の水平面上での位置を示す推定位置データと、推定した測定位置間隔を示す推定測定位置間隔データと、推定した車両1の速度及び水平面上での走行方向を含む推定走行状態データとを生成する。走行軌跡解析部32は、移動軌跡解析部の一態様である。
The travel locus analysis unit 32 is based on the travel locus data generated by the travel locus data generation unit 31, the position and speed of the vehicle 1 on the horizontal plane at each measurement time, the travel direction on the horizontal plane, and the measurement position. Estimate the interval. The traveling locus analysis unit 32 includes estimated position data indicating the estimated position of the vehicle 1 on the horizontal plane, estimated measurement position interval data indicating the estimated measurement position interval, estimated speed of the vehicle 1, and the estimated vehicle 1 for each measurement time. Generates estimated running state data including the running direction on the horizontal plane. The traveling locus analysis unit 32 is an aspect of the traveling locus analysis unit.
ここで、図3を参照しつつ、走行軌跡解析部32による測定時刻ごとの車両1の水平面上での位置と、速度と、水平面上での走行方向と、測定位置間隔とを推定する手法について説明する。図3において、符号5で示す二重線の矢印の曲線が、走行軌跡データ生成部31がGPS観測データ40と、準天頂衛星観測データ41とに基づいて生成した走行軌跡データによって示される車両1の走行軌跡である。
Here, with reference to FIG. 3, a method for estimating the position and speed of the vehicle 1 on the horizontal plane, the traveling direction on the horizontal plane, and the measurement position interval for each measurement time by the traveling locus analysis unit 32. explain. In FIG. 3, the curve of the double line arrow indicated by reference numeral 5 is shown by the travel locus data generated by the travel locus data generation unit 31 based on the GPS observation data 40 and the quasi-zenith satellite observation data 41. It is a running track of.
符号PJ-1,PJ,PJ+1,PJ+2により示す丸印の位置は、GPS観測データ40及び準天頂衛星観測データ41によって示される観測時刻における車両1の位置である。走行軌跡データ生成部31は、車両1の走行軌跡を近似する線として、PJ-1,PJ,PJ+1,PJ+2を通る曲線5を求め、求めた曲線5を示すデータを走行軌跡データとして生成する。
The positions of the circles indicated by the symbols PJ -1 , PJ , PJ + 1 , and PJ + 2 are the positions of the vehicle 1 at the observation time indicated by the GPS observation data 40 and the quasi-zenith satellite observation data 41. The travel locus data generation unit 31 obtains a curve 5 passing through PJ -1 , PJ , PJ + 1 , and PJ + 2 as a line that approximates the travel locus of the vehicle 1, and obtains data indicating the obtained curve 5 as travel locus data. Generate as.
ここで、PJを出発してPJ+1に至るまでの間で、N回の測定時刻が存在したとする。なお、図3は、N=5の例である。N個の測定時刻の各々において、レーザ光を照射するN個の各々の位置を、pj(1),pj(2),…,pj(i),…,pj(N)とする。最後のpj(N)は、PJ+1に一致する。
Here, it is assumed that there are N measurement times from PJ to PJ + 1 . Note that FIG. 3 is an example of N = 5. At each of the N measurement times, the positions of the N irradiating laser beams are designated as pj (1) , pj (2) , ..., pj (i) , ..., Pj (N) . do. The final p j (N) corresponds to P J + 1 .
このとき、残りのN-1個のpj(1),pj(2),…,pj(i),…,pj(N―1)の位置は、PJからPJ+1の間で等間隔に並ぶとは限らない。そのため、走行軌跡解析部32は、PJからPJ+1の間の前後の間隔、すなわち、PJ-1からPJの間の長さと、PJ+1からPJ+2の間の長さとを考慮して、PJからPJ+1の間をN個に区切って、N-1個のpj(1),pj(2),…,pj(i),…,pj(N―1)の位置を求める。
At this time, the positions of the remaining N-1 p j (1) , p j (2) , ..., p j (i) , ..., P j (N-1) are between P J and P J + 1 . It is not always evenly spaced. Therefore, the traveling locus analysis unit 32 considers the front-back distance between P J and P J + 1 , that is, the length between P J-1 and P J , and the length between P J + 1 and P J + 2 . , PJ to PJ + 1 are divided into N pieces, and N-1 pieces of pj (1) , pj (2) , ..., pj (i) , ..., pj (N-1) Find the position.
図3に示す例の場合、PJ-1からPJの間の長さ及び、PJ+1からPJ+2の間の長さに比べて、PJからPJ+1の間の長さは短い。そのため、走行軌跡解析部32は、PJ-1からPJの間の長さ及び、PJ+1からPJ+2の間の長さに応じて、中央の部分の間隔よりも両端の部分の間隔が長くなるように区切って、N-1個のpj(1),pj(2),…,pj(i),…,pj(N―1)の位置を求める。走行軌跡解析部32は、pj(1),pj(2),…,pj(i),…,pj(N―1),PJ+1の各々の位置を、PJからPJ+1の間におけるN個の測定時刻ごとの推定位置データとし、各々の間の長さをN個の測定時刻ごとの推定測定位置間隔データとして生成する。
In the case of the example shown in FIG. 3, the length between PJ -1 and PJ + 1 is shorter than the length between PJ -1 and PJ + 2 and the length between PJ + 1 and PJ + 2. Therefore, in the traveling locus analysis unit 32, the distance between both ends is larger than the distance between the central parts, depending on the length between P J-1 and P J and the length between P J + 1 and P J + 2 . The positions of N-1 p j (1) , p j (2) , ..., p j (i) , ..., p j (N-1) are obtained by dividing them so as to be long. The traveling locus analysis unit 32 sets the respective positions of p j (1) , p j (2) , ..., p j (i) , ..., p j (N-1) , and P J + 1 from P J to P J + 1. Estimated position data for each of N measurement times is used, and the length between each is generated as estimated measurement position interval data for each of N measurement times.
走行軌跡解析部32は、PJとpj(1)とを結ぶベクトルを生成し、生成したベクトルの方向をpj(1)における車両1の走行方向として求める。走行軌跡解析部32は、生成したベクトルの長さを、PJにおける測定時刻と、pj(1)における測定時刻の差、すなわち測定の時間間隔で除算した値を、pj(1)における車両1の速度として求める。走行軌跡解析部32は、pj(2),…,pj(i),…,pj(N―1),PJ+1の各々に対して同様のベクトルを生成し、pj(2),…,pj(i),…,pj(N―1),PJ+1の各々の位置における車両1の走行方向と、車両1の速度とを求める。走行軌跡解析部32は、pj(2),…,pj(i),…,pj(N―1),PJ+1の各々の位置における走行方向と、速度との組み合わせを、PJからPJ+1の間におけるN個の測定時刻ごとの推定走行状態データとする。
The traveling locus analysis unit 32 generates a vector connecting P J and p j (1) , and obtains the direction of the generated vector as the traveling direction of the vehicle 1 in p j (1) . The traveling locus analysis unit 32 divides the length of the generated vector by the difference between the measurement time in PJ and the measurement time in pj (1) , that is, the measurement time interval, in pj (1) . Obtained as the speed of vehicle 1. The traveling locus analysis unit 32 generates similar vectors for each of p j (2) , ..., p j (i) , ..., p j (N-1) , and P J + 1 , and p j (2). , ..., p j (i) , ..., p j (N-1) , P J + 1 The traveling direction of the vehicle 1 and the speed of the vehicle 1 at each position are obtained. The traveling locus analysis unit 32 determines the combination of the traveling direction and the speed at each position of p j (2) , ..., p j (i) , ..., p j (N-1) , and P J + 1 . To the estimated running state data for each of N measurement times between PJ + 1 .
例えば、車両1の時速を60[km/時間]とすると、秒速は、1666.7[cm/秒]になる。レーザレーダ装置21の測定時刻の間隔は、上記したように、例えば、0.005秒程度である。0.005秒の間に、車両1は、約8.3[cm](≒1666.7×0.005)移動する。上記したように、GPS観測データ40及び準天頂衛星観測データ41の観測時刻の間隔は、1秒であるため、1秒間の間に200個の測定時刻が存在することになる。上記したように、GPS観測データ40及び準天頂衛星観測データ41の両方を利用した場合の測位の精度は、おおよそ十数センチメートル~数センチメートルである。したがって、0.005秒間隔で約8.3[cm]変化する移動であれば、高い確率で測定時刻ごとの車両1の位置を正確に推定することができる。これに対して、GPS観測データ40のみを利用する場合の測位の精度は、精々数メートル~数十メートルである。数メートル~数十メートルという誤差は、観測時刻の間隔、すなわち1秒間に車両1が移動する1666.7[cm]に比べると無視できない誤差であり、正確に車両1の位置を推定することができない場合も想定される。
For example, assuming that the speed of the vehicle 1 is 60 [km / hour], the speed per second is 1666.7 [cm / second]. As described above, the interval between the measurement times of the laser radar device 21 is, for example, about 0.005 seconds. During 0.005 seconds, vehicle 1 moves about 8.3 [cm] (≈1666.7 × 0.005). As described above, the interval between the observation times of the GPS observation data 40 and the quasi-zenith satellite observation data 41 is 1 second, so that there are 200 measurement times in 1 second. As described above, the accuracy of positioning when both the GPS observation data 40 and the quasi-zenith satellite observation data 41 are used is about a dozen centimeters to a few centimeters. Therefore, if the movement changes by about 8.3 [cm] at intervals of 0.005 seconds, the position of the vehicle 1 at each measurement time can be accurately estimated with high probability. On the other hand, the accuracy of positioning when only the GPS observation data 40 is used is at most several meters to several tens of meters. An error of several meters to several tens of meters is a non-negligible error compared to the observation time interval, that is, 1666.7 [cm] in which the vehicle 1 moves in one second, and the position of the vehicle 1 can be estimated accurately. It is assumed that it cannot be done.
走行軌跡解析部32は、ある測定時刻の推定走行状態データと、記憶部25が記憶する当該測定時刻に対応する走行状態データ42とを対比し、速度の相違が予め定められる範囲内であり、かつ、走行方向の相違が予め定められる範囲内である場合、走行状態データ42を利用して、推定位置データ、推定測定位置間隔データ及び推定走行状態データの精度を高める処理を行う。
The travel locus analysis unit 32 compares the estimated travel state data at a certain measurement time with the travel state data 42 stored in the storage unit 25 corresponding to the measurement time, and the difference in speed is within a predetermined range. Moreover, when the difference in the traveling direction is within a predetermined range, the traveling state data 42 is used to perform a process of improving the accuracy of the estimated position data, the estimated measurement position interval data, and the estimated traveling state data.
ここで、速度の相違についての予め定められる範囲内及び走行方向の相違についての予め定められる範囲内とは、例えば、走行状態データ42が示す車両1の速度及び走行方向が、推定走行状態データが示す車両1の速度及び走行方向と大きく異なっていない範囲内であって、走行状態データ42が、推定位置データ、推定測定位置間隔データ及び推定走行状態データの精度を高める処理に利用できる程度の範囲内である。
Here, the predetermined range for the difference in speed and the predetermined range for the difference in the traveling direction are, for example, the speed and the traveling direction of the vehicle 1 indicated by the traveling state data 42, and the estimated traveling state data. Within a range not significantly different from the speed and traveling direction of the vehicle 1 shown, the traveling state data 42 can be used for processing for improving the accuracy of the estimated position data, the estimated measurement position interval data, and the estimated running state data. Inside.
図4は、図3において示した車両1の位置、速度及び走行方向を特定するベクトルを、測定時刻ごとの車速データ42-1と走行方向データ42-2によって補正したベクトルを示した図である。図4に示すように、測定時刻ごとの車速データ42-1と走行方向データ42-2により、個々のベクトルは、細やかなアクセル操作、ブレーキ操作、ハンドル操作を反映して、左右方向に微妙に変化する。走行軌跡解析部32は、図4に示すベクトルの各々から改めて推定位置データと、推定測定位置間隔データと、推定走行状態データとを生成することにより、精度の高い推定位置データと、推定測定位置間隔データと、推定走行状態データとが得られることになる。
FIG. 4 is a diagram showing a vector obtained by correcting the vector for specifying the position, speed, and traveling direction of the vehicle 1 shown in FIG. 3 by the vehicle speed data 42-1 and the traveling direction data 42-2 for each measurement time. .. As shown in FIG. 4, according to the vehicle speed data 42-1 and the traveling direction data 42-2 for each measurement time, each vector is delicately reflected in the left-right direction, reflecting the delicate accelerator operation, brake operation, and steering wheel operation. Change. The traveling locus analysis unit 32 generates highly accurate estimated position data and estimated measurement position by generating estimated position data, estimated measurement position interval data, and estimated traveling state data again from each of the vectors shown in FIG. Interval data and estimated running state data will be obtained.
測定条件生成部33は、走行軌跡解析部32が生成した測定時刻ごとの推定位置データと、推定測定位置間隔データと、推定走行状態データとに基づいて、測定時刻におけるレーザレーダ装置21の測定条件を示す測定条件データを生成する。
The measurement condition generation unit 33 is the measurement condition of the laser radar device 21 at the measurement time based on the estimated position data for each measurement time generated by the travel locus analysis unit 32, the estimated measurement position interval data, and the estimated travel state data. Generate measurement condition data indicating.
道路交通情報取得部34は、例えば、カーナビゲーション装置であり、車両1が走行している道路に関する道路交通情報を取得する。走行軌跡データ正常判定部35は、測定時刻と、当該測定時刻における車両1の推定位置データとを含む正常判定指示信号を受けた場合、道路交通情報取得部34から取得する道路交通情報と、正常判定指示信号に含まれる測定時刻における車両1の推定位置データとに基づいて、正常判定指示信号に含まれている測定時刻において車両1が、トンネル内や高架下などのGPS衛星10-1,10-2及び準天頂衛星11から正常に電波が受信できない位置に存在していたか否かにより、走行軌跡データが正常であるか否かを判定する。
The road traffic information acquisition unit 34 is, for example, a car navigation device, and acquires road traffic information related to the road on which the vehicle 1 is traveling. When the travel locus data normality determination unit 35 receives a normality determination instruction signal including the measurement time and the estimated position data of the vehicle 1 at the measurement time, the road traffic information acquired from the road traffic information acquisition unit 34 and the normality. Based on the estimated position data of the vehicle 1 at the measurement time included in the determination instruction signal, the vehicle 1 is the GPS satellite 10-1, 10 in the tunnel or under the elevated at the measurement time included in the normality determination instruction signal. -It is determined whether or not the travel locus data is normal based on whether or not the vehicle exists at a position where radio waves cannot be normally received from -2 and the quasi-zenith satellite 11.
補正処理部36は、測定条件生成部33が生成した測定条件データに基づいて、記憶部25が記憶する収集データ44を補正する。補正処理部36は、記憶部25が記憶する点群データ43に付与されている信頼指標を補正する。
The correction processing unit 36 corrects the collected data 44 stored in the storage unit 25 based on the measurement condition data generated by the measurement condition generation unit 33. The correction processing unit 36 corrects the reliability index given to the point cloud data 43 stored in the storage unit 25.
(収集データに含まれる誤差)
次に、図5を参照しつつ、収集データ生成部26が生成する収集データ44に含まれる誤差について説明する。図5は、図18に示した図の一部を拡大した図であり、図18と同一の構成については、同一の符号を付している。なお、図5では、車両700に替えて車両1が走行しており、走行軌跡541は、車両1の走行軌跡を示しているものとする。走行軌跡541は、収集データ生成部26がGPS観測データ40から得られる観測時刻ごとの車両1の位置を通過する線を描くことにより生成され、屈曲している部分については近似曲線を描くことにより生成される。 (Error included in the collected data)
Next, with reference to FIG. 5, the error included in the collecteddata 44 generated by the collected data generation unit 26 will be described. FIG. 5 is an enlarged view of a part of the figure shown in FIG. 18, and the same components as those in FIG. 18 are designated by the same reference numerals. In FIG. 5, it is assumed that the vehicle 1 is traveling instead of the vehicle 700, and the traveling locus 541 indicates the traveling locus of the vehicle 1. The traveling locus 541 is generated by the collected data generation unit 26 drawing a line passing through the position of the vehicle 1 for each observation time obtained from the GPS observation data 40, and drawing an approximate curve for the bent portion. Generated.
次に、図5を参照しつつ、収集データ生成部26が生成する収集データ44に含まれる誤差について説明する。図5は、図18に示した図の一部を拡大した図であり、図18と同一の構成については、同一の符号を付している。なお、図5では、車両700に替えて車両1が走行しており、走行軌跡541は、車両1の走行軌跡を示しているものとする。走行軌跡541は、収集データ生成部26がGPS観測データ40から得られる観測時刻ごとの車両1の位置を通過する線を描くことにより生成され、屈曲している部分については近似曲線を描くことにより生成される。 (Error included in the collected data)
Next, with reference to FIG. 5, the error included in the collected
実際には、GPS衛星10-1、10-2からの電波を常に受信することができない。そのため、上記したように、収集データ生成部26は、GPS観測データ40に加えて、車速データ42-1と、走行方向データ42-2とを用いて、測定時刻ごとの車両1の水平面上での位置、速度、水平面上での走行方向及び測定位置間隔を推定する。
Actually, radio waves from GPS satellites 10-1 and 10-2 cannot always be received. Therefore, as described above, the collected data generation unit 26 uses the vehicle speed data 42-1 and the traveling direction data 42-2 in addition to the GPS observation data 40 on the horizontal plane of the vehicle 1 at each measurement time. Estimate the position, speed, running direction on the horizontal plane, and measurement position interval.
ただし、図5では、収集データ44に含まれる誤差を分かり易く説明するために、収集データ生成部26は、GPS観測データ40のみから測定時刻ごとの車両1の水平面上での位置及び水平面上での走行方向を推定した例を示している。また、図5において、走行軌跡541に沿って示している複数の点線は、車両1に搭載されたレーザレーダ装置21が、実際に測定時刻ごとに照射したレーザ光の照射方向を示したレーザ照射ラインであり、レーザ照射ラインの各々に対して対応する測定時刻t0~t20を付して示している。
However, in FIG. 5, in order to explain the error included in the collected data 44 in an easy-to-understand manner, the collected data generation unit 26 uses only the GPS observation data 40 to position the vehicle 1 on the horizontal plane and on the horizontal plane for each measurement time. An example of estimating the traveling direction of is shown. Further, in FIG. 5, the plurality of dotted lines shown along the traveling locus 541 indicate the irradiation direction of the laser beam actually irradiated by the laser radar device 21 mounted on the vehicle 1 at each measurement time. It is a line, and the corresponding measurement times t0 to t20 are attached to each of the laser irradiation lines.
車両1が等速で走行し、かつ直進している場合、点線で示すレーザ照射ラインは等間隔になるため、収集データ生成部26は、観測時刻と測定時刻の差に基づいて、GPS観測データ40から測定時刻における車両1の位置を正確に推定することができる。車両1の位置71,72,73(以下、車両1の位置71を車両位置71のようにいう)は、実際にレーザ光を照射した位置であるレーザ照射ライン81,82,83と走行軌跡541との交点に一致しており、収集データ生成部26が、正確に車両1の位置を推定できている例である。
When the vehicle 1 is traveling at a constant speed and traveling straight, the laser irradiation lines shown by the dotted lines are at equal intervals, so that the collected data generation unit 26 uses the GPS observation data based on the difference between the observation time and the measurement time. From 40, the position of the vehicle 1 at the measurement time can be accurately estimated. The positions 71, 72, 73 of the vehicle 1 (hereinafter, the position 71 of the vehicle 1 is referred to as the vehicle position 71) are the laser irradiation lines 81, 82, 83 and the traveling locus 541, which are the positions where the laser light is actually irradiated. This is an example in which the collected data generation unit 26 can accurately estimate the position of the vehicle 1 because it coincides with the intersection with the above.
GPS観測データ40によって特定する測位の精度、すなわち、特定する位置の誤差は、上記したように、数メートル~数十メートルになる。これに対して、車両1が時速60[km/時間]で走行している場合、上記したように、測定時刻の間隔が0.005秒であるときには、車両1は、測定時刻の間隔の間に約8.3[cm]移動する。約8.3[cm]という移動距離は、数メートル~数十メートルという距離に比べると、かなり短い距離である。この距離の違いを考慮して、収集データ生成部26は、直近の測定位置間隔の数百~千倍程度の長さのベクトルを、推定済みの車両1の位置を起点として生成する。ただし、図5は、図示して説明できるようにするため、数百~千倍ではなく、3倍の長さのベクトルを生成する例を示している。
The accuracy of positioning specified by the GPS observation data 40, that is, the error of the specified position is several meters to several tens of meters as described above. On the other hand, when the vehicle 1 is traveling at a speed of 60 [km / hour] and the measurement time interval is 0.005 seconds as described above, the vehicle 1 is during the measurement time interval. Move about 8.3 [cm] to. The moving distance of about 8.3 [cm] is considerably shorter than the distance of several meters to several tens of meters. In consideration of this difference in distance, the collected data generation unit 26 generates a vector having a length of about several hundred to one thousand times the latest measurement position interval, starting from the estimated position of the vehicle 1. However, FIG. 5 shows an example of generating a vector having a length of three times instead of several hundred to one thousand times so that it can be illustrated and explained.
収集データ生成部26は、例えば、レーザ照射ライン85に対応する測定時刻t5における車両1の位置を推定する際、既に推定している4つ前の測定時刻t1の車両位置71と、3つ前の測定時刻t2の車両位置72とに基づいて、車両位置72における車両1の速度を算出する。なお、収集データ生成部26が算出する速度の単位時間は、測定時刻の間隔である。収集データ生成部26は、算出した速度の大きさを3倍にしたベクトルV85を、車両位置72を起点として走行軌跡541に沿って生成する。収集データ生成部26は、生成したベクトルV85の終端位置である位置を、測定時刻t5における車両1の位置、すなわち車両位置75として推定する。また、収集データ生成部26は、測定時刻t5における車両1の走行方向をベクトルV85の方向とする。
When the collected data generation unit 26 estimates the position of the vehicle 1 at the measurement time t5 corresponding to the laser irradiation line 85, for example, the vehicle position 71 at the measurement time t1 four times before the estimation and the vehicle position 71 three times before. The speed of the vehicle 1 at the vehicle position 72 is calculated based on the vehicle position 72 at the measurement time t2 of. The unit time of the speed calculated by the collected data generation unit 26 is the interval of the measurement time. The collected data generation unit 26 generates a vector V85 obtained by triple the calculated speed along the travel locus 541 starting from the vehicle position 72. The collected data generation unit 26 estimates the position which is the terminal position of the generated vector V85 as the position of the vehicle 1 at the measurement time t5, that is, the vehicle position 75. Further, the collected data generation unit 26 sets the traveling direction of the vehicle 1 at the measurement time t5 as the direction of the vector V85.
車両1は、レーザ照射ライン84に対応する測定時刻t4の付近から、速度を減速し始めているため、収集データ生成部26が測定時刻t5の車両1の位置として推定した車両位置75は、実際の測定時刻t5でレーザ光を照射した位置であるレーザ照射ライン85と走行軌跡541との交点とは異なる位置になっており、両方向矢印で示す差がある。ベクトルV85を、直角を挟む2辺のうちの一方の辺とする直角三角形を仮定すると、直角三角形の直角を含む他方の辺が、推定した車両位置75に対応するレーザ照射方向を示すレーザ照射ラインとなる。図5では、推定した車両1の位置に対応するレーザ照射ラインを一点鎖線で示している。
Since the vehicle 1 starts decelerating from the vicinity of the measurement time t4 corresponding to the laser irradiation line 84, the vehicle position 75 estimated by the collected data generation unit 26 as the position of the vehicle 1 at the measurement time t5 is the actual position. The position is different from the intersection of the laser irradiation line 85 and the traveling locus 541, which is the position where the laser beam is irradiated at the measurement time t5, and there is a difference indicated by the bidirectional arrow. Assuming a right triangle with the vector V85 as one of the two sides of the right angle, the other side of the right triangle, including the right angle, indicates the laser irradiation direction corresponding to the estimated vehicle position 75. It becomes. In FIG. 5, the laser irradiation line corresponding to the estimated position of the vehicle 1 is shown by a alternate long and short dash line.
収集データ生成部26は、直近の観測時刻の位置を起点として、繰り返し上記のベクトルV85のようなベクトルを生成して、測定時刻ごとの車両1の位置と走行方向を推定する。この手法を用いると、車両1が等速で走行しており、かつ直進している場合、収集データ生成部26は、車両位置71,72,73のように正確に車両1の位置を推定することができる。これに対して、車両1が減速し始めると正確な推定を行うことができなくなり、測定時刻t4,t5,t6において推定する車両位置74,75,76と、実際にレーザ光を照射した車両1の位置との間にずれが生じることになる。ただし、車両1が減速しているが直進している間は、一点鎖線で示す推定した車両1の位置に対応するレーザの照射ラインは、実際のレーザ照射方向を示すレーザ照射ライン84,85,86とは平行になる。
The collected data generation unit 26 repeatedly generates a vector such as the above vector V85 starting from the position of the latest observation time, and estimates the position and the traveling direction of the vehicle 1 for each measurement time. Using this method, when the vehicle 1 is traveling at a constant speed and traveling straight, the collected data generation unit 26 accurately estimates the position of the vehicle 1 as in the vehicle positions 71, 72, 73. be able to. On the other hand, when the vehicle 1 starts decelerating, accurate estimation cannot be performed, and the vehicle positions 74, 75, 76 estimated at the measurement times t4, t5, t6 and the vehicle 1 actually irradiated with the laser beam. There will be a deviation from the position of. However, while the vehicle 1 is decelerating but traveling straight, the laser irradiation line corresponding to the estimated position of the vehicle 1 indicated by the alternate long and short dash line is the laser irradiation line 84, 85, which indicates the actual laser irradiation direction. It will be parallel to 86.
車両1が車両750を回避するために、走行レーン561から追越レーン562に移動すると、走行軌跡541が屈曲することになる。ここで、仮に、収集データ生成部26が、レーザ照射ライン87に対応する測定時刻t11における車両1の位置として、正確な位置である車両位置77を推定し、また、レーザ照射ライン88に対応する測定時刻t12における車両1の位置として、正確な位置である車両位置78を推定したとする。
When the vehicle 1 moves from the traveling lane 561 to the overtaking lane 562 in order to avoid the vehicle 750, the traveling locus 541 bends. Here, tentatively, the collected data generation unit 26 estimates the vehicle position 77, which is an accurate position as the position of the vehicle 1 at the measurement time t11 corresponding to the laser irradiation line 87, and also corresponds to the laser irradiation line 88. It is assumed that the vehicle position 78, which is an accurate position, is estimated as the position of the vehicle 1 at the measurement time t12.
収集データ生成部26は、レーザ照射ライン89に対応する測定時刻t15における車両1の位置を推定する際、上記した手順にしたがって、4つ前の測定時刻t11の車両位置77と、3つ前の測定時刻t12の車両位置78とに基づいて、車両位置78における車両1の速度を算出する。収集データ生成部26は、算出した速度の大きさを3倍にしたベクトルV89を走行軌跡541に沿って生成する。収集データ生成部26は、生成したベクトルV89の終端位置である車両位置79を、測定時刻t15における車両1の位置として推定する。ベクトルV89を、直角を挟む2辺のうちの一方の辺とする直角三角形を仮定すると、直角三角形の直角を含む他方の辺が、推定した車両位置79に対応するレーザ照射方向を示すレーザ照射ラインとなる。車両位置79を通る一点鎖線で示したレーザ照射ラインの方向と、実際の測定時刻t15のレーザ照射ライン89の方向とには両方向矢印で示す違いが生じていることが分かる。
When the collected data generation unit 26 estimates the position of the vehicle 1 at the measurement time t15 corresponding to the laser irradiation line 89, the vehicle position 77 at the measurement time t11 four times before and the vehicle position three before the measurement time t11 according to the above procedure. The speed of the vehicle 1 at the vehicle position 78 is calculated based on the vehicle position 78 at the measurement time t12. The collected data generation unit 26 generates a vector V89 in which the magnitude of the calculated speed is tripled along the traveling locus 541. The collected data generation unit 26 estimates the vehicle position 79, which is the terminal position of the generated vector V89, as the position of the vehicle 1 at the measurement time t15. Assuming a right triangle in which the vector V89 is one of two sides sandwiching a right angle, the other side including the right angle of the right triangle indicates the laser irradiation direction corresponding to the estimated vehicle position 79. It becomes. It can be seen that there is a difference between the direction of the laser irradiation line indicated by the alternate long and short dash line passing through the vehicle position 79 and the direction of the laser irradiation line 89 at the actual measurement time t15, which is indicated by the bidirectional arrow.
すなわち、車両1が等速で走行していない場合には、収集データ生成部26が生成する収集データ44にはGPS観測データ40の精度に応じた位置の誤差が含まれていることになる。車両1が直進していない場合には、GPS観測データ40の精度に応じた走行方向の誤差が加わることになる。したがって、車両1が等速で走行しておらず、かつ直進していない場合、車両1の位置と走行方向の両方に誤差が含まれていることになる。
That is, when the vehicle 1 is not traveling at a constant speed, the collected data 44 generated by the collected data generation unit 26 includes a position error according to the accuracy of the GPS observation data 40. If the vehicle 1 is not traveling straight, an error in the traveling direction according to the accuracy of the GPS observation data 40 will be added. Therefore, when the vehicle 1 is not traveling at a constant speed and is not traveling straight, an error is included in both the position and the traveling direction of the vehicle 1.
(準天頂衛星観測データを用いた場合の精度)
図6は、走行軌跡データ生成部31が生成した走行軌跡データに基づいて、走行軌跡解析部32が推定した測定時刻ごとの車両1の水平面上での位置と、速度と、水平面上での走行方向とを示した図である。 (Accuracy when using quasi-zenith satellite observation data)
FIG. 6 shows the position and speed of thevehicle 1 on the horizontal plane for each measurement time estimated by the travel locus analysis unit 32 based on the travel locus data generated by the travel locus data generation unit 31, and the travel on the horizontal plane. It is a figure which showed the direction.
図6は、走行軌跡データ生成部31が生成した走行軌跡データに基づいて、走行軌跡解析部32が推定した測定時刻ごとの車両1の水平面上での位置と、速度と、水平面上での走行方向とを示した図である。 (Accuracy when using quasi-zenith satellite observation data)
FIG. 6 shows the position and speed of the
図6は、図5と同様に、図18に示した図の一部を拡大した図であり、図18と同一の構成については、同一の符号を付している。なお、図6においても、車両700に替えて車両1が走行しており、走行軌跡541は、車両1の走行軌跡を示しているものとする。図6に示す複数の点線は、レーザレーダ装置21が、測定時刻ごとに照射したレーザ光の照射方向を示したレーザ照射ラインであり、図5と同一の位置及び傾きになっている。
FIG. 6 is an enlarged view of a part of the figure shown in FIG. 18, similarly to FIG. 5, and the same components as those in FIG. 18 are designated by the same reference numerals. Also in FIG. 6, it is assumed that the vehicle 1 is traveling instead of the vehicle 700, and the traveling locus 541 indicates the traveling locus of the vehicle 1. The plurality of dotted lines shown in FIG. 6 are laser irradiation lines indicating the irradiation direction of the laser light irradiated by the laser radar device 21 at each measurement time, and have the same positions and inclinations as those in FIG.
走行軌跡データ生成部31は、GPS観測データ40と、準天頂衛星観測データ41とに基づいて走行軌跡データを生成する。上記したように、GPS観測データ40と、準天頂衛星観測データ41とを利用することで、測位誤差は、おおよそ十数センチメートル~数センチメートルになる。したがって、走行軌跡解析部32が推定する測定時刻ごとの車両1の水平面上での位置、速度及び水平面上での走行方向の各々のデータは、各々に対応する収集データ生成部26が推定するデータよりも高い精度になる。
The travel locus data generation unit 31 generates travel locus data based on the GPS observation data 40 and the quasi-zenith satellite observation data 41. As described above, by using the GPS observation data 40 and the quasi-zenith satellite observation data 41, the positioning error becomes about a dozen centimeters to a few centimeters. Therefore, each data of the position, speed, and traveling direction of the vehicle 1 on the horizontal plane at each measurement time estimated by the traveling locus analysis unit 32 is the data estimated by the collected data generation unit 26 corresponding to each. Will be more accurate than.
そのため、走行軌跡解析部32が推定した測定時刻ごとの車両1の位置は、図6の走行軌跡541上に丸印で示すように、実際の測定時刻においてレーザレーダ装置21がレーザ光を照射した位置に一致することになる。したがって、車両1が直進しているが、等速で走行していない場合であっても、走行軌跡解析部32は、例えば、連続する5つの測定時刻の車両1の位置を車両位置90,91,92,93,94として推定する。車両位置90,91,92,93,94において隣接する各々の間を結ぶベクトルを生成し、上記のように生成したベクトルを、直角を挟む2辺のうちの一方の辺とする直角三角形を仮定すると、直角三角形の直角を挟む他方の辺とレーザ照射ラインとが一致することになる。
Therefore, the position of the vehicle 1 for each measurement time estimated by the travel locus analysis unit 32 is indicated by a circle on the travel locus 541 in FIG. 6, and the laser radar device 21 irradiates the laser beam at the actual measurement time. It will match the position. Therefore, even when the vehicle 1 is traveling straight but not traveling at a constant speed, the traveling locus analysis unit 32 sets the position of the vehicle 1 at five consecutive measurement times as the vehicle positions 90 and 91, for example. , 92, 93, 94. A right triangle is assumed in which a vector connecting adjacent objects at vehicle positions 90, 91, 92, 93, and 94 is generated, and the vector generated as described above is one of two sides sandwiching a right angle. Then, the other side of the right triangle sandwiching the right angle coincides with the laser irradiation line.
車両1が車両750を回避して走行軌跡541が屈曲した場合、走行軌跡解析部32は、例えば、連続する5つの測定時刻の車両1の位置を車両位置95,96,97,98,99として推定する。車両位置95,96,97,98,99において隣接する各々の間を結ぶベクトルを生成した上で、上記のように生成したベクトルを、直角を挟む2辺のうちの一方の辺とする直角三角形を仮定すると、直角三角形の直角を挟む他方の辺と、傾いたレーザ照射ラインとが一致することになる。
When the vehicle 1 avoids the vehicle 750 and the travel locus 541 bends, the travel locus analysis unit 32 sets, for example, the position of the vehicle 1 at five consecutive measurement times as the vehicle positions 95, 96, 97, 98, 99. presume. A right triangle with the vector generated as described above as one of the two sides sandwiching the right angle after generating a vector connecting the adjacent ones at the vehicle positions 95, 96, 97, 98, 99. Assuming that, the other side of the right triangle sandwiching the right angle coincides with the inclined laser irradiation line.
したがって、車両1の位置の推定に準天頂衛星観測データ41を用いることで、車両1の位置と走行方向を高い精度で推定可能であることが分かり、更に、車速データ42-1と、走行方向データ42-2とを用いることで、推定の精度を高めることができることになる。
Therefore, it is found that the position and traveling direction of vehicle 1 can be estimated with high accuracy by using the quasi-zenith satellite observation data 41 for estimating the position of vehicle 1, and further, the vehicle speed data 42-1 and the traveling direction can be estimated. By using the data 42-2, the accuracy of estimation can be improved.
(収集データ生成部による処理)
図7は、収集データ生成部26による収集データ44の生成処理の流れを示すフローチャートである。収集データ生成部26は、記憶部25にレーザレーダ装置21によって、新たな測定時刻に対応する点群データ43が書き込まれたことを検出する(ステップS1)。 (Processing by the collected data generator)
FIG. 7 is a flowchart showing the flow of the generation process of the collecteddata 44 by the collected data generation unit 26. The collected data generation unit 26 detects that the point cloud data 43 corresponding to the new measurement time has been written to the storage unit 25 by the laser radar device 21 (step S1).
図7は、収集データ生成部26による収集データ44の生成処理の流れを示すフローチャートである。収集データ生成部26は、記憶部25にレーザレーダ装置21によって、新たな測定時刻に対応する点群データ43が書き込まれたことを検出する(ステップS1)。 (Processing by the collected data generator)
FIG. 7 is a flowchart showing the flow of the generation process of the collected
収集データ生成部26は、GPS観測データ40に基づいて、図5を参照して説明した手法により、検出した測定時刻における車両1の水平面上での位置、速度、水平面上での走行方向及び測定位置間隔を推定する。収集データ生成部26は、検出した測定時刻における車両1の水平面上での位置、速度、水平面上での走行方向、及び測定位置間隔を推定する際、検出した測定時刻の走行状態データ42を適用した補正も行う。収集データ生成部26は、推定した車両1の水平面上での位置と、車両1において固定設置されているレーザレーダ装置21の位置関係とに基づいて、検出した測定時刻におけるレーザレーダ装置21の三次元空間における位置を算出する。
Based on the GPS observation data 40, the collected data generation unit 26 measures the position, speed, traveling direction and measurement of the vehicle 1 on the horizontal plane at the detected measurement time by the method described with reference to FIG. Estimate the position interval. The collected data generation unit 26 applies the traveling state data 42 at the detected measurement time when estimating the position and speed of the vehicle 1 on the horizontal plane, the traveling direction on the horizontal plane, and the measurement position interval at the detected measurement time. It also makes corrections. The collected data generation unit 26 is a tertiary of the laser radar device 21 at the detected measurement time based on the estimated position of the vehicle 1 on the horizontal plane and the positional relationship of the laser radar device 21 fixedly installed in the vehicle 1. Calculate the position in the original space.
収集データ生成部26は、推定した車両1の水平面上での走行方向の180°逆向きの方向を、検出した測定時刻におけるレーザレーダ装置21の水平面上での方向とし、検出した測定時刻におけるレーザレーダ装置21の鉛直面上での方向を「0°」とする。
The collected data generation unit 26 sets the direction 180 ° opposite to the estimated traveling direction of the vehicle 1 on the horizontal plane as the direction on the horizontal plane of the laser radar device 21 at the detected measurement time, and the laser at the detected measurement time. The direction of the radar device 21 on the vertical plane is set to "0 °".
収集データ生成部26は、検出した測定時刻と、当該測定時刻に対応するレーザレーダ装置21の位置、レーザレーダ装置21の水平面上及び鉛直面上での方向、測定位置間隔、車両1の速度及び車両1の走行方向を対応付けて収集データ44を生成し、生成した収集データ44を記憶部25に書き込む(ステップS2)。
The collected data generation unit 26 has the detected measurement time, the position of the laser radar device 21 corresponding to the measurement time, the direction of the laser radar device 21 on the horizontal plane and on the vertical surface, the measurement position interval, the speed of the vehicle 1, and the speed of the vehicle 1. Collected data 44 is generated in association with the traveling direction of the vehicle 1, and the generated collected data 44 is written in the storage unit 25 (step S2).
収集データ生成部26は、検出した測定時刻の走行状態データ42と、当該測定時刻の直前の測定時刻の走行状態データ42とが一致するか否かにより、車両1が等速で走行しており、かつ直進しているか否かを判定する(ステップS3)。すなわち、収集データ生成部26は、検出した測定時刻の車速データ42-1が示す車両1の速度と、当該測定時刻の直前の測定時刻の車速データ42-1が示す車両1の速度とが一致するか否かを判定することにより、車両1が等速で走行しているか否かを判定する。また、収集データ生成部26は、検出した測定時刻の走行方向データ42-2が示す車両1の走行方向と、当該測定時刻の直前の測定時刻の走行方向データ42-2が示す車両1の走行方向とが一致するか否かを判定することにより、車両1が直進しているか否かを判定する。収集データ生成部26は、2つの車両1の速度が一致しており、かつ2つの車両1の走行方向が一致している場合、車両1が等速で走行しており、かつ直進していると判定し(ステップS3、Yes)、検出した測定時刻に対応する点群データ43に対して信頼指標「高い」を付与する(ステップS4)。
In the collected data generation unit 26, the vehicle 1 is traveling at a constant speed depending on whether or not the traveling state data 42 at the detected measurement time and the traveling state data 42 at the measurement time immediately before the measurement time match. , And it is determined whether or not the vehicle is going straight (step S3). That is, the collected data generation unit 26 matches the speed of the vehicle 1 indicated by the vehicle speed data 42-1 at the detected measurement time with the speed of the vehicle 1 indicated by the vehicle speed data 42-1 at the measurement time immediately before the measurement time. By determining whether or not to do so, it is determined whether or not the vehicle 1 is traveling at a constant speed. Further, the collected data generation unit 26 has the traveling direction of the vehicle 1 indicated by the traveling direction data 42-2 at the detected measurement time and the traveling of the vehicle 1 indicated by the traveling direction data 42-2 at the measurement time immediately before the measurement time. By determining whether or not the directions match, it is determined whether or not the vehicle 1 is traveling straight. When the speeds of the two vehicles 1 are the same and the traveling directions of the two vehicles 1 are the same, the collected data generation unit 26 is traveling at a constant speed and traveling straight. (Step S3, Yes), and a confidence index "high" is given to the point group data 43 corresponding to the detected measurement time (step S4).
一方、収集データ生成部26は、2つの車両1の速度が一致していないか、または、2つの車両1の走行方向が一致していない場合、車両1が等速でないか、または、直進していないと判定し(ステップS3、No)、検出した測定時刻に対応する点群データ43に対して信頼指標「低い」を付与する(ステップS5)。なお、収集データ生成部26は、例えば、点群データ43を利用して行う置局設計において、設計結果の信頼性を向上させる事情などがある場合、信頼指標「低い」に替えて「無い」を付与してもよい。収集データ生成部26は、等速でないが直進している場合に、信頼指標「低い」を付与し、等速でなく、かつ直進していない場合に、信頼指標「無い」を付与するようにしてもよい。
On the other hand, when the speeds of the two vehicles 1 do not match or the traveling directions of the two vehicles 1 do not match, the collected data generation unit 26 indicates that the vehicle 1 is not at a constant speed or goes straight. It is determined that the data is not present (step S3, No), and the confidence index “low” is given to the point group data 43 corresponding to the detected measurement time (step S5). The collected data generation unit 26 replaces the reliability index “low” with “not” when there is a situation for improving the reliability of the design result in the station design performed using the point cloud data 43, for example. May be given. The collected data generation unit 26 assigns a reliability index "low" when the speed is not constant but is traveling straight, and assigns a reliability index "not" when the speed is not constant and the vehicle is not traveling straight. You may.
収集データ生成部26は、例えば、点群データ収集装置2の利用者の操作入力により、点群データ43の測定を終了する指示信号を受けているか否かに基づいて、収集データ44の生成を終了するか否かを判定する(ステップS6)。収集データ生成部26は、点群データ43の測定を終了する指示信号を受けていると判定した場合(ステップS6、Yes)、処理を終了する。
The collected data generation unit 26 generates the collected data 44 based on whether or not, for example, an instruction signal for terminating the measurement of the point cloud data 43 is received by the operation input of the user of the point cloud data collecting device 2. It is determined whether or not to end (step S6). When it is determined that the collected data generation unit 26 has received the instruction signal to end the measurement of the point cloud data 43 (step S6, Yes), the process ends.
一方、収集データ生成部26は、点群データ43の測定を終了する指示信号を受けていないと判定した場合(ステップS6、No)、ステップS1からの処理を継続する。
On the other hand, when the collected data generation unit 26 determines that the instruction signal for ending the measurement of the point cloud data 43 has not been received (step S6, No), the processing from step S1 is continued.
(準天頂衛星観測データを用いる場合の処理)
図8は、データ補正部3による収集データ44を補正する処理の流れを示すフローチャートである。
走行軌跡データ生成部31は、記憶部25において新たな測定時刻の収集データ44が収集データ生成部26によって記録されたことを検出する(ステップSa1)。走行軌跡データ生成部31は、新たに記録された収集データ44の測定時刻(以下「処理対象の測定時刻」ともいう。)を含む前後4つの観測時刻におけるGPS観測データ40と、準天頂衛星観測データ41とを記憶部25から読み出す。走行軌跡データ生成部31は、読み出したGPS観測データ40と、準天頂衛星観測データ41とに基づいて、走行軌跡データを生成する(ステップSa2)。走行軌跡データ生成部31は、生成した走行軌跡データと、処理対象の測定時刻とを走行軌跡解析部32に出力する。 (Processing when using quasi-zenith satellite observation data)
FIG. 8 is a flowchart showing a flow of processing for correcting the collecteddata 44 by the data correction unit 3.
The traveling locusdata generation unit 31 detects that the collection data 44 at the new measurement time has been recorded by the collection data generation unit 26 in the storage unit 25 (step Sa1). The travel locus data generation unit 31 includes GPS observation data 40 at four observation times before and after including the measurement time of the newly recorded collected data 44 (hereinafter, also referred to as “measurement time to be processed”), and quasi-zenith satellite observation. The data 41 and the data 41 are read from the storage unit 25. The travel locus data generation unit 31 generates travel locus data based on the read GPS observation data 40 and the quasi-zenith satellite observation data 41 (step Sa2). The travel locus data generation unit 31 outputs the generated travel locus data and the measurement time of the processing target to the travel locus analysis unit 32.
図8は、データ補正部3による収集データ44を補正する処理の流れを示すフローチャートである。
走行軌跡データ生成部31は、記憶部25において新たな測定時刻の収集データ44が収集データ生成部26によって記録されたことを検出する(ステップSa1)。走行軌跡データ生成部31は、新たに記録された収集データ44の測定時刻(以下「処理対象の測定時刻」ともいう。)を含む前後4つの観測時刻におけるGPS観測データ40と、準天頂衛星観測データ41とを記憶部25から読み出す。走行軌跡データ生成部31は、読み出したGPS観測データ40と、準天頂衛星観測データ41とに基づいて、走行軌跡データを生成する(ステップSa2)。走行軌跡データ生成部31は、生成した走行軌跡データと、処理対象の測定時刻とを走行軌跡解析部32に出力する。 (Processing when using quasi-zenith satellite observation data)
FIG. 8 is a flowchart showing a flow of processing for correcting the collected
The traveling locus
走行軌跡解析部32は、走行軌跡データ生成部31が出力する処理対象の測定時刻と、走行軌跡データとを取り込む。走行軌跡解析部32は、図3に示した手法により、走行軌跡データに基づいて、処理対象の測定時刻における車両1の水平面上での位置と、速度と、水平面上での走行方向と、測定位置間隔とを推定する。走行軌跡解析部32は、推定した車両1の水平面上での位置を示す推定位置データと、推定した測定位置間隔を示す推定測定位置間隔データと、推定した車両1の速度及び水平面上での走行方向を含む推定走行状態データとを生成する(ステップSa3)。
The travel locus analysis unit 32 captures the measurement time of the processing target output by the travel locus data generation unit 31 and the travel locus data. The traveling locus analysis unit 32 measures the position and speed of the vehicle 1 on the horizontal plane and the traveling direction on the horizontal plane at the measurement time of the processing target based on the traveling locus data by the method shown in FIG. Estimate the position interval. The travel locus analysis unit 32 includes estimated position data indicating the estimated position of the vehicle 1 on the horizontal plane, estimated measurement position interval data indicating the estimated measurement position interval, and estimated speed of the vehicle 1 and traveling on the horizontal plane. Estimated running state data including directions are generated (step Sa3).
走行軌跡解析部32は、記憶部25から処理対象の測定時刻の走行状態データ42を読み出す。走行軌跡解析部32は、読み出した走行状態データ42と、生成した推定走行状態データとを対比し、速度の相違が予め定められる範囲内であり、かつ、走行方向の相違が予め定められる範囲内であるか否かを判定する(ステップSa4)。すなわち、走行軌跡解析部32は、走行状態データ42に含まれる車速データ42-1が示す車両1の速度と、推定走行状態データに含まれる車両1の速度との相違が予め定められる範囲内であるか否かを判定するとともに、走行状態データ42に含まれる走行方向データ42-2が示す車両1の走行方向と、推定走行状態データに含まれる車両1の水平面上での走行方向との相違が予め定められる範囲内であるか否かを判定する。
The traveling locus analysis unit 32 reads the traveling state data 42 at the measurement time to be processed from the storage unit 25. The travel locus analysis unit 32 compares the read travel state data 42 with the generated estimated travel state data, and the difference in speed is within a predetermined range, and the difference in travel direction is within a predetermined range. It is determined whether or not it is (step Sa4). That is, the travel locus analysis unit 32 is within a range in which the difference between the speed of the vehicle 1 indicated by the vehicle speed data 42-1 included in the travel condition data 42 and the speed of the vehicle 1 included in the estimated travel condition data is predetermined. Difference between the traveling direction of the vehicle 1 indicated by the traveling direction data 42-2 included in the traveling state data 42 and the traveling direction of the vehicle 1 included in the estimated traveling state data on the horizontal plane. Is within a predetermined range.
走行軌跡解析部32は、2つの速度の相違が予め定められる範囲内でないか、または、2つの走行方向の相違が予め定められる範囲内でないと判定した場合(ステップSa4、No)、処理対象の測定時刻と、生成した推定位置データとを含む正常判定指示信号を走行軌跡データ正常判定部35に出力する。
When the travel locus analysis unit 32 determines that the difference between the two speeds is not within the predetermined range or the difference between the two travel directions is not within the predetermined range (steps Sa4, No), the processing target is The normality determination instruction signal including the measurement time and the generated estimated position data is output to the travel locus data normality determination unit 35.
走行軌跡データ正常判定部35は、走行軌跡解析部32から正常判定指示信号を受けると、道路交通情報取得部34に対して、正常判定指示信号に含まれる処理対象の測定時刻における道路交通情報を要求して取得する。走行軌跡データ正常判定部35は、取得した道路交通情報と、正常判定指示信号に含まれる推定位置データが示す位置とに基づいて、処理対象の測定時刻において車両1が、トンネル内や高架下などのGPS衛星10-1,10-2及び準天頂衛星11から正常に電波が受信できない位置に存在していたか否かにより、走行軌跡データが正常であるか否かを判定する(ステップSa5)。
When the travel locus data normality determination unit 35 receives the normality determination instruction signal from the travel locus analysis unit 32, the travel locus data normality determination unit 35 informs the road traffic information acquisition unit 34 of the road traffic information at the measurement time of the processing target included in the normality determination instruction signal. Request and get. Based on the acquired road traffic information and the position indicated by the estimated position data included in the normality determination instruction signal, the travel locus data normality determination unit 35 sets the vehicle 1 in a tunnel, under an elevated vehicle, or the like at the measurement time to be processed. It is determined whether or not the travel locus data is normal based on whether or not the GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11 are present at positions where radio waves cannot be normally received (step Sa5).
走行軌跡データ正常判定部35は、処理対象の測定時刻において車両1がGPS衛星10-1,10-2及び準天頂衛星11から正常に電波が受信できない位置に存在していた場合、走行軌跡データは正常でないと判定し(ステップSa5、No)、外部に異常を出力して(ステップSa6)、走行軌跡データ生成部31に処理終了指示信号を出力する。走行軌跡データ生成部31は、処理終了指示信号を受けると処理を終了する。
The travel locus data normality determination unit 35 is the travel locus data when the vehicle 1 is present at a position where radio waves cannot be normally received from the GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11 at the measurement time to be processed. Determines that it is not normal (steps Sa5 and No), outputs an abnormality to the outside (steps Sa6), and outputs a processing end instruction signal to the travel locus data generation unit 31. The travel locus data generation unit 31 ends the processing when it receives the processing end instruction signal.
一方、走行軌跡データ正常判定部35は、処理対象の測定時刻において車両1がGPS衛星10-1,10-2及び準天頂衛星11から正常に電波が受信できる位置に存在していた場合、走行軌跡データは正常であると判定し(ステップSa5、Yes)、補正処理部36に対して、処理対象の測定時刻を含む信頼指標「低い」を付与する補正指示信号を出力する。補正処理部36は、走行軌跡データ正常判定部35から補正指示信号を受けると、記憶部25の点群データ43を参照し、補正指示信号に含まれる処理対象の測定時刻に対応する点群データ43の信頼指標を「低い」に補正する(ステップSa7)。その後、処理は、ステップSa13に進められる。
On the other hand, the travel locus data normality determination unit 35 travels when the vehicle 1 is present at a position where radio waves can be normally received from the GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11 at the measurement time to be processed. It is determined that the locus data is normal (steps Sa5, Yes), and a correction instruction signal for which a reliability index "low" including the measurement time of the processing target is given is output to the correction processing unit 36. When the correction processing unit 36 receives the correction instruction signal from the travel locus data normality determination unit 35, the correction processing unit 36 refers to the point cloud data 43 of the storage unit 25, and the point cloud data corresponding to the measurement time of the processing target included in the correction instruction signal. The confidence index of 43 is corrected to "low" (step Sa7). After that, the process proceeds to step Sa13.
ここで、ステップSa5において、走行軌跡データ正常判定部35が、走行軌跡データは正常であると判定した場合、処理対象の測定時刻の点群データ43に対して信頼指標「低い」を付与する理由は、走行状態データ42と、推定走行状態データとの間に予め定められる範囲を超える相違が存在し、車両1がスリップ等して走行状態データ42が正常でない可能性があり、そのために、処理対象の測定時刻の点群データ43も正常に収集されていない可能性があるからである。
Here, in step Sa5, when the travel locus data normality determination unit 35 determines that the travel locus data is normal, the reason for assigning the reliability index "low" to the point cloud data 43 at the measurement time to be processed. There is a difference exceeding a predetermined range between the running state data 42 and the estimated running state data, and there is a possibility that the vehicle 1 slips or the like and the running state data 42 is not normal. Therefore, processing is performed. This is because the point cloud data 43 at the measurement time of the target may not be collected normally.
一方、ステップSa4において、走行軌跡解析部32は、2つの速度の相違が予め定められる範囲内であり、かつ2つの走行方向の相違が予め定められる範囲内であると判定した場合(ステップSa4、Yes)、図4に示した手法により、推定位置データ、推定測定位置間隔データ及び推定走行状態データに対して、処理対象の測定時刻の走行状態データ42を適用して、改めて推定位置データと、推定測定位置間隔データと、推定走行状態データとを生成する(ステップSa8)。
On the other hand, in step Sa4, when the travel locus analysis unit 32 determines that the difference between the two speeds is within the predetermined range and the difference between the two travel directions is within the predetermined range (step Sa4, Yes), by the method shown in FIG. 4, the running state data 42 at the measurement time to be processed is applied to the estimated position data, the estimated measurement position interval data, and the estimated running state data, and the estimated position data and the estimated running state data are obtained again. The estimated measurement position interval data and the estimated running state data are generated (step Sa8).
走行軌跡解析部32は、記憶部25から処理対象の測定時刻の直前の測定時刻に対応する収集データ44を読み出す。走行軌跡解析部32は、読み出した収集データ44に含まれる測定位置間隔、車両1の走行方向の各々が、推定測定位置間隔データが示す測定位置間隔、推定走行状態データが示す車両1の走行方向の各々に一致するか否かを判定する(ステップSa9)。
The traveling locus analysis unit 32 reads out the collected data 44 corresponding to the measurement time immediately before the measurement time of the processing target from the storage unit 25. The travel locus analysis unit 32 has a measurement position interval included in the read collected data 44, a travel direction of the vehicle 1, each of which is a measurement position interval indicated by the estimated measurement position interval data, and a travel direction of the vehicle 1 indicated by the estimated travel state data. It is determined whether or not each of the above is matched (step Sa9).
走行軌跡解析部32が、2つの測定位置間隔が一致し、かつ2つの車両1の走行方向が一致すると判定した場合(ステップSa9、Yes)、車両1は、処理対象の測定時刻において、等速で走行しており、かつ直進していることになる。そのため、処理対象の測定時刻の収集データ44を補正する必要がないので、走行軌跡解析部32は、収集データ44を補正する処理に進めずに、ステップSa13に処理を進める。
When the travel locus analysis unit 32 determines that the distance between the two measurement positions matches and the travel directions of the two vehicles 1 match (steps Sa9, Yes), the vehicle 1 has a constant velocity at the measurement time of the processing target. It means that you are driving at and going straight. Therefore, since it is not necessary to correct the collected data 44 at the measurement time of the processing target, the traveling locus analysis unit 32 proceeds to the process of step Sa13 without proceeding to the process of correcting the collected data 44.
一方、走行軌跡解析部32は、2つの測定位置間隔が一致しないか、または、2つの車両1の走行方向が一致しないと判定した場合(ステップSa9、No)、改めて生成した推定位置データと、推定測定位置間隔データと、推定走行状態データと、処理対象の測定時刻とを測定条件生成部33に出力する。
On the other hand, when the travel locus analysis unit 32 determines that the distance between the two measurement positions does not match or the travel directions of the two vehicles 1 do not match (steps Sa9, No), the estimated position data generated again and the estimated position data are used. The estimated measurement position interval data, the estimated running state data, and the measurement time of the processing target are output to the measurement condition generation unit 33.
測定条件生成部33は、走行軌跡解析部32が出力した推定位置データと、車両1において固定設置されているレーザレーダ装置21の位置関係とに基づいて、処理対象の測定時刻におけるレーザレーダ装置21の三次元空間における位置を算出する。測定条件生成部33は、走行軌跡解析部32が出力する推定走行状態データに含まれる車両1の走行方向の水平成分の方向の180°逆向きの方向を処理対象の測定時刻におけるレーザレーダ装置21の方向の水平成分とし、レーザレーダ装置21の方向の鉛直成分を「0°」とする。
The measurement condition generation unit 33 is based on the estimated position data output by the traveling locus analysis unit 32 and the positional relationship of the laser radar device 21 fixedly installed in the vehicle 1, and the laser radar device 21 at the measurement time to be processed. Calculate the position of the above in three-dimensional space. The measurement condition generation unit 33 sets the direction 180 ° opposite to the horizontal component direction of the vehicle 1 included in the estimated travel state data output by the travel locus analysis unit 32, and the laser radar device 21 at the measurement time to be processed. The horizontal component in the direction of is set to "0 °" and the vertical component in the direction of the laser radar device 21 is set to "0 °".
測定条件生成部33は、算出したレーザレーダ装置21の位置と、レーザレーダ装置21の水平面上及び鉛直面上での方向と、推定測定位置間隔データが示す測定位置間隔と、推定走行状態データに含まれる車両1の速度及び走行方向と、処理対象の測定時刻とを含むデータを測定条件データとして生成する(ステップSa10)。測定条件生成部33は、生成した測定条件データを補正処理部36に出力する。
The measurement condition generation unit 33 uses the calculated position of the laser radar device 21, the direction of the laser radar device 21 on the horizontal plane and the vertical surface, the measurement position interval indicated by the estimated measurement position interval data, and the estimated running state data. Data including the speed and traveling direction of the included vehicle 1 and the measurement time to be processed is generated as measurement condition data (step Sa10). The measurement condition generation unit 33 outputs the generated measurement condition data to the correction processing unit 36.
補正処理部36は、測定条件生成部33が出力する測定条件データを取り込む。補正処理部36は、記憶部25が記憶する収集データ44の中から取り込んだ測定条件データに含まれている処理対象の測定時刻に対応する収集データ44を選択する。補正処理部36は、選択した収集データ44に含まれているデータを、測定条件データに含まれているデータに書き替えて、収集データ44を補正する(ステップSa11)。補正処理部36は、記憶部25の点群データ43を参照し、測定条件データに含まれている処理対象の測定時刻に対応する点群データ43の信頼指標を「高い」に補正する(ステップSa12)。
The correction processing unit 36 takes in the measurement condition data output by the measurement condition generation unit 33. The correction processing unit 36 selects the collection data 44 corresponding to the measurement time of the processing target included in the measurement condition data captured from the collection data 44 stored in the storage unit 25. The correction processing unit 36 rewrites the data included in the selected collected data 44 with the data included in the measurement condition data, and corrects the collected data 44 (step Sa11). The correction processing unit 36 refers to the point cloud data 43 of the storage unit 25, and corrects the reliability index of the point cloud data 43 corresponding to the measurement time of the processing target included in the measurement condition data to “high” (step). Sa12).
補正処理部36は、例えば、点群データ収集装置2の利用者の操作入力により、点群データ43の測定を終了する指示信号を受けているか否かに基づいて、収集データ44の補正を終了するか否かを判定する(ステップSa13)。補正処理部36は、点群データ43の測定を終了する指示信号を受けていると判定した場合(ステップSa13、Yes)、処理終了指示信号を走行軌跡データ生成部31に出力する。走行軌跡データ生成部31は、処理終了指示信号を受けると処理を終了する。
The correction processing unit 36 ends the correction of the collected data 44 based on whether or not, for example, an instruction signal for ending the measurement of the point cloud data 43 is received by the operation input of the user of the point cloud data collecting device 2. It is determined whether or not to do so (step Sa13). When it is determined that the correction processing unit 36 has received the instruction signal to end the measurement of the point cloud data 43 (step Sa13, Yes), the correction processing unit 36 outputs the processing end instruction signal to the travel locus data generation unit 31. The travel locus data generation unit 31 ends the processing when it receives the processing end instruction signal.
一方、補正処理部36は、点群データ43の測定を終了する指示信号を受けていないと判定した場合(ステップSa13、No)、走行軌跡データ生成部31に処理継続指示信号を出力する。走行軌跡データ生成部31は、処理継続指示信号を受けるとステップSa1の処理を再び開始する。
On the other hand, when the correction processing unit 36 determines that the instruction signal for ending the measurement of the point cloud data 43 has not been received (step Sa13, No), the correction processing unit 36 outputs the processing continuation instruction signal to the travel locus data generation unit 31. When the travel locus data generation unit 31 receives the processing continuation instruction signal, the processing of step Sa1 is restarted.
上記の第1の実施形態の構成において、走行軌跡データ生成部31は、観測時刻ごとに得られる車両1の水平面上での位置を示すデータよりも高精度の車両1の水平面上での位置を示すデータを取得し、取得した高精度の車両1の水平面上での位置を示すデータに基づいて、車両1の走行軌跡を示す走行軌跡データを生成する。走行軌跡解析部32は、走行軌跡データを解析して、測定時刻ごとの車両1の位置及び走行状態を推定する。測定条件生成部33は、測定時刻ごとの車両1の位置及び走行状態に基づいて、測定時刻ごとのレーザレーダ装置21の測定条件を示す測定条件データを生成する。補正処理部36は、測定条件データに基づいて、収集データ44を補正する。
In the configuration of the first embodiment described above, the travel locus data generation unit 31 determines the position of the vehicle 1 on the horizontal plane with higher accuracy than the data indicating the position of the vehicle 1 on the horizontal plane obtained at each observation time. The data shown is acquired, and based on the acquired data indicating the position of the vehicle 1 on the horizontal plane, the travel locus data indicating the travel locus of the vehicle 1 is generated. The traveling locus analysis unit 32 analyzes the traveling locus data and estimates the position and traveling state of the vehicle 1 at each measurement time. The measurement condition generation unit 33 generates measurement condition data indicating the measurement conditions of the laser radar device 21 for each measurement time based on the position and running state of the vehicle 1 for each measurement time. The correction processing unit 36 corrects the collected data 44 based on the measurement condition data.
収集データ生成部26が生成した収集データ44では、車両1が加速や減速をしたり、右左折や屈曲した走行をしたりした場合に収集された点群データ43に対して信頼指標「低い」、または、「無い」を付与していた。そのため、点群データ43を用いて、基地局と端末局の間を見通し判定や遮蔽率の判定を行う置局設計において、信頼指標「低い」、または、「無い」が付与された点群データ43を有効に活用することができていなかった。これに対して、第1の実施形態では、GPS観測データ40に加えて準天頂衛星観測データ41を利用する。これにより、車両1が加速や減速をしたり、右左折や屈曲した走行をしたりした場合であっても、車両1の位置と、水平面上での走行方向とを高い精度で推定することできる。それにより、収集データ44に含まれるレーザレーダ装置21の位置と、レーザレーダ装置21の水平面上での方向とを正確に補正することができる。そのため、車両1が加速や減速をしたり、右左折や屈曲した走行をしたりした場合に収集された点群データ43の信頼度合いを高めることができるので、右左折や屈曲した走行をしたりした場合に収集された点群データ43に対して信頼指標「高い」を付与することができる。したがって、レーザ照射ラインが乱れる箇所における車両の位置及び走行状態を従来よりも高精度に推定することにより、レーザ照射ラインの乱れによって信頼度合いが低下した点群データを利用可能にすることができ、例えば、置局設計を行う際に利用することができる点群データ43を増やすことができる。
In the collected data 44 generated by the collected data generation unit 26, the reliability index is "low" with respect to the point cloud data 43 collected when the vehicle 1 accelerates or decelerates, turns left or right, or travels in a curved manner. Or, "None" was given. Therefore, in the station design for determining the line-of-sight and the shielding rate between the base station and the terminal station using the point cloud data 43, the point cloud data to which the reliability index "low" or "none" is given. 43 could not be used effectively. On the other hand, in the first embodiment, the quasi-zenith satellite observation data 41 is used in addition to the GPS observation data 40. As a result, even when the vehicle 1 accelerates or decelerates, turns left or right, or travels in a bent manner, the position of the vehicle 1 and the traveling direction on the horizontal plane can be estimated with high accuracy. .. Thereby, the position of the laser radar device 21 included in the collected data 44 and the direction of the laser radar device 21 on the horizontal plane can be accurately corrected. Therefore, the reliability of the point cloud data 43 collected when the vehicle 1 accelerates or decelerates, turns left or right, or travels in a bent manner can be increased, so that the vehicle 1 can turn left or right or travel in a bent manner. In this case, the confidence index "high" can be given to the point cloud data 43 collected. Therefore, by estimating the position and running state of the vehicle at the place where the laser irradiation line is disturbed with higher accuracy than before, it is possible to use the point cloud data whose reliability is lowered due to the disturbance of the laser irradiation line. For example, the point cloud data 43 that can be used when designing a station can be increased.
なお、上記の第1の実施形態では、走行状態計測部24は、ステアリングセンサから測定時刻ごとのステアリングの操舵角を取得して、車両1の水平面上での走行方向を算出するようにしているが、三次元ジャイロセンサ(3Dジャイロセンサ)や方位磁針(コンパス)などに接続し、三次元ジャイロセンサや方位磁針などから方向を示す情報を取得して、車両1の水平面上での走行方向を算出するようにしてもよい。
In the first embodiment described above, the traveling state measuring unit 24 acquires the steering angle of the steering for each measurement time from the steering sensor and calculates the traveling direction of the vehicle 1 on the horizontal plane. Connects to a three-dimensional gyro sensor (3D gyro sensor), a compass, etc., acquires information indicating the direction from the three-dimensional gyro sensor, the compass, etc., and determines the traveling direction of the vehicle 1 on the horizontal plane. It may be calculated.
(第2の実施形態)
図9は、第2の実施形態の点群データ収集システムβの構成を示すブロック図である。第2の実施形態の点群データ収集システムβにおいて、第1の実施形態における点群データ収集システムαと同一の構成については、同一の符号を付し、以下、異なる構成について説明する。点群データ収集システムβは、点群データ収集装置2aを備えた車両1aと、複数のGPS衛星10-1,10-2及び準天頂衛星11と、位置情報サービス事業者サーバ装置50とを備えている。車両1aは、例えば、自動車であり、上記したMMSに相当する。 (Second embodiment)
FIG. 9 is a block diagram showing a configuration of the point cloud data collection system β of the second embodiment. In the point cloud data collection system β of the second embodiment, the same configurations as the point cloud data collection system α of the first embodiment are designated by the same reference numerals, and different configurations will be described below. The point cloud data collection system β includes avehicle 1a equipped with a point cloud data collection device 2a, a plurality of GPS satellites 10-1, 10-2 and a quasi-zenith satellite 11, and a location information service provider server device 50. ing. The vehicle 1a is, for example, an automobile and corresponds to the above-mentioned MMS.
図9は、第2の実施形態の点群データ収集システムβの構成を示すブロック図である。第2の実施形態の点群データ収集システムβにおいて、第1の実施形態における点群データ収集システムαと同一の構成については、同一の符号を付し、以下、異なる構成について説明する。点群データ収集システムβは、点群データ収集装置2aを備えた車両1aと、複数のGPS衛星10-1,10-2及び準天頂衛星11と、位置情報サービス事業者サーバ装置50とを備えている。車両1aは、例えば、自動車であり、上記したMMSに相当する。 (Second embodiment)
FIG. 9 is a block diagram showing a configuration of the point cloud data collection system β of the second embodiment. In the point cloud data collection system β of the second embodiment, the same configurations as the point cloud data collection system α of the first embodiment are designated by the same reference numerals, and different configurations will be described below. The point cloud data collection system β includes a
第2の実施形態の点群データ収集装置2aは、車両1aの水平面上での走行方向に加えて、車両1aの鉛直面上での走行方向を推定する。そのため、点群データ収集装置2aは、車両1aの標高を検出する手法として、例えば、以下の参考文献1-1に示す汎地球測位航法衛星システム(以下「GNSS」(Global Navigation Satellite System))という。)を用いた手法を利用する。
The point cloud data collecting device 2a of the second embodiment estimates the traveling direction of the vehicle 1a on the vertical surface in addition to the traveling direction of the vehicle 1a on the horizontal plane. Therefore, the point cloud data collecting device 2a is referred to as, for example, the pan-global positioning navigation satellite system (hereinafter referred to as “GNSS” (Global Navigation Satellite System)) shown in Reference 1-1 below as a method for detecting the altitude of the vehicle 1a. .. ) Is used.
[参考文献1-1:“情報化施工を実現する技術,汎地球測位航法衛星システム(GNSS)”,国土交通省 九州地方整備局,[令和2年7月12日検索],インターネット(URL: http://www.qsr.mlit.go.jp/ict/technology/jitsugen_3.html)]
[Reference 1-1: "Technology to realize computerized construction, Pan-Earth Positioning Navigation Satellite System (GNSS)", Ministry of Land, Infrastructure, Transport and Tourism, Kyushu Regional Development Bureau, [Search on July 12, 2nd year of Reiwa], Internet (URL) : Http://www.qsr.mlit.go.jp/ict/technology/jitsugen_3.html)]
GNSSとは、測位衛星を用いた測位システムである。ここで、測位衛星とは、例えば、上記したGPS衛星10-1,10-2や準天頂衛星11の他に、ロシアのGLONASS(Global Navigation Satellite System)、欧州のGALILEOなどがある。原理としては、空間で位置の分かる3点の測位衛星から衛星電波受信機までの各距離により、衛星電波受信機の位置を特定する。GNSSを利用した測位方式には、参考文献1-1に示されるように、以下のような種類がある。
GNSS is a positioning system that uses positioning satellites. Here, the positioning satellites include, for example, GLONASS (Global Navigation Satellite System) in Russia, GALIEO in Europe, and the like, in addition to the GPS satellites 10-1 and 10-2 and the quasi-zenith satellite 11 described above. In principle, the position of the satellite radio wave receiver is specified by each distance from the three positioning satellites whose positions are known in space to the satellite radio wave receiver. As shown in Reference 1-1, there are the following types of positioning methods using GNSS.
例えば、RTK(Real Time Kinematic)-GNSS測位方式では、衛星電波受信機を備えた移動局を測定したい観測点に設置し、移動局の他に位置の分かる基準局を設置して測位する。RTK-GNSS測位方式による測位の精度は、水平方向において2~3cmであり、鉛直方向において3~4cm程度である。
For example, in the RTK (Real Time Kinematic) -GNSS positioning method, a mobile station equipped with a satellite radio receiver is installed at the observation point to be measured, and a reference station whose position is known is installed in addition to the mobile station for positioning. The accuracy of positioning by the RTK-GNSS positioning method is about 2 to 3 cm in the horizontal direction and about 3 to 4 cm in the vertical direction.
これに対して、参考文献1-1に示されているネットワーク型RTK-GNSS測位方式がある。ネットワーク型RTK-GNSS測位方式には、VRS(Virtual Reference Station)方式と、FKP(Flachen Korrektur Parameter)方式とがある。
On the other hand, there is a network type RTK-GNSS positioning method shown in Reference 1-1. The network type RTK-GNSS positioning method includes a VRS (Virtual Reference Station) method and an FKP (Flachen Korrektur Parameter) method.
ネットワーク型RTK-GNSS測位方式では、全国に設置された複数の電子基準点に設置された衛星電波受信機が測位衛星からのデータを受信する。国土地理院の解析装置が、複数の電子基準点に設置された衛星電波受信機の各々からデータを受信して解析する。位置情報サービス事業者の処理装置が、国土地理院の解析装置から解析結果を受信し、国土地理院の基準点から求めた位相差を示す補正データ45を生成する。測位を行う人は、衛星電波受信機を備えた移動局を観測点に設置し、観測点において受信した測位衛星からのデータと、通信回線を通じて受信する補正データ45とに基づいて測位を行う。ネットワーク型RTK-GNSS測位方式は、RTK-GNSS測位方式に比べると精度は若干落ちるが、RTK-GNSS測位方式のように基準局の設置が不要である。なお、RTK-GNSS測位方式及びネットワーク型RTK-GNSS測位方式は、衛星数が多いほど良い精度となり、谷間より上空が開けている方が良い精度となる。
In the network type RTK-GNSS positioning method, satellite radio receivers installed at multiple electronic reference points installed nationwide receive data from the positioning satellite. The Geospatial Information Authority of Japan's analysis equipment receives and analyzes data from each of the satellite radio receivers installed at multiple electronic reference points. The processing device of the location information service provider receives the analysis result from the analysis device of the Geographical Survey Institute, and generates the correction data 45 indicating the phase difference obtained from the reference point of the Geographical Survey Institute. The person performing the positioning installs a mobile station equipped with a satellite radio wave receiver at the observation point, and performs positioning based on the data from the positioning satellite received at the observation point and the correction data 45 received through the communication line. The network type RTK-GNSS positioning method is slightly less accurate than the RTK-GNSS positioning method, but unlike the RTK-GNSS positioning method, it does not require the installation of a reference station. The RTK-GNSS positioning method and the network type RTK-GNSS positioning method have better accuracy as the number of satellites increases, and the accuracy is better when the sky is open than the valley.
第2の実施形態では、ネットワーク型RTK-GNSS測位方式を利用する例について示すが、基準局を設置できるのであれば、RTK-GNSS測位方式を利用してもよい。
In the second embodiment, an example of using the network type RTK-GNSS positioning method is shown, but if a reference station can be installed, the RTK-GNSS positioning method may be used.
図9に戻り、位置情報サービス事業者サーバ装置50とは、上記した国土地理院の解析装置から解析結果を受信する位置情報サービス事業者の処理装置に相当する装置であり、補正データ45を生成する。位置情報サービス事業者サーバ装置50は、生成した補正データ45を、例えば、無線通信ネットワークを介して車両1aの点群データ収集装置2aに送信する。
Returning to FIG. 9, the location information service provider server device 50 is a device corresponding to the processing device of the location information service provider that receives the analysis result from the above-mentioned analysis device of the Geographical Survey Institute, and generates correction data 45. do. The location information service provider server device 50 transmits the generated correction data 45 to the point cloud data collection device 2a of the vehicle 1a via, for example, a wireless communication network.
点群データ収集装置2aは、レーザレーダ装置21、衛星電波受信用アンテナ22、無線電波受信用アンテナ27、情報受信部23a、走行状態計測部24a、記憶部25a、収集データ生成部26a及びデータ補正部3aを備える。
The point cloud data collecting device 2a includes a laser radar device 21, a satellite radio wave receiving antenna 22, a radio wave receiving antenna 27, an information receiving unit 23a, a traveling state measuring unit 24a, a storage unit 25a, a collected data generation unit 26a, and data correction. A unit 3a is provided.
無線電波受信用アンテナ27は、無線通信ネットワークを介して位置情報サービス事業者サーバ装置50から補正データ45が重畳された電波を受信する。情報受信部23aは、情報受信部23が備える構成に加えて以下の構成を備える。情報受信部23aは、無線電波受信用アンテナ27に接続しており、無線電波受信用アンテナ27が受信した電波に重畳されている補正データ45を検出し、検出した補正データ45を記憶部25aに書き込む。
The radio wave receiving antenna 27 receives the radio wave on which the correction data 45 is superimposed from the location information service provider server device 50 via the wireless communication network. The information receiving unit 23a has the following configuration in addition to the configuration provided in the information receiving unit 23. The information receiving unit 23a is connected to the radio wave receiving antenna 27, detects the correction data 45 superimposed on the radio wave received by the radio wave receiving antenna 27, and stores the detected correction data 45 in the storage unit 25a. Write.
データ補正部3aは、走行軌跡データ生成部31a、走行軌跡解析部32a、測定条件生成部33a、道路交通情報取得部34、走行軌跡データ正常判定部35及び補正処理部36を備える。
The data correction unit 3a includes a travel locus data generation unit 31a, a travel locus analysis unit 32a, a measurement condition generation unit 33a, a road traffic information acquisition unit 34, a travel locus data normality determination unit 35, and a correction processing unit 36.
走行状態計測部24aは、例えば、車両1aが備える速度を検出する車速センサ、ステアリングの操舵角を検出するステアリングセンサ及び水平水準器に接続する。走行状態計測部24aは、車速センサから得られるデータに基づいて、測定時刻ごとの車両1aの速度を計測する。走行状態計測部24aは、ステアリングセンサから得られるデータに基づいて測定時刻ごとのステアリングの操舵角を計測する。走行状態計測部24aは、水平水準器から得られるデータに基づいて測定時刻ごとの車両1aの傾きを計測する。
The traveling state measuring unit 24a is connected to, for example, a vehicle speed sensor for detecting the speed of the vehicle 1a, a steering sensor for detecting the steering angle of the steering, and a horizontal level. The traveling state measuring unit 24a measures the speed of the vehicle 1a at each measurement time based on the data obtained from the vehicle speed sensor. The traveling state measuring unit 24a measures the steering angle of the steering at each measurement time based on the data obtained from the steering sensor. The traveling state measuring unit 24a measures the inclination of the vehicle 1a at each measurement time based on the data obtained from the horizontal level.
走行状態計測部24aは、測定時刻ごとのステアリングの操舵角から車両1aの水平面上での走行方向を算出し、測定時刻ごとの車両1aの傾きから鉛直面上での走行方向を算出する。走行状態計測部24aは、測定時刻ごとの車両1aの速度を示す車速データ42-1と、測定時刻ごとの車両1aの水平面上での走行方向と、鉛直面上での走行方向とによって特定される走行方向示す走行方向データ42a-2とを含む走行状態データ42aを生成する。走行状態計測部24aは、生成した走行状態データ42aを記憶部25aに書き込む。
The traveling state measuring unit 24a calculates the traveling direction of the vehicle 1a on the horizontal plane from the steering angle of the steering at each measurement time, and calculates the traveling direction on the vertical surface from the inclination of the vehicle 1a at each measurement time. The traveling state measuring unit 24a is specified by the vehicle speed data 42-1 indicating the speed of the vehicle 1a at each measurement time, the traveling direction of the vehicle 1a on the horizontal plane at each measurement time, and the traveling direction on the vertical surface. The traveling state data 42a including the traveling direction data 42a-2 indicating the traveling direction is generated. The traveling state measuring unit 24a writes the generated traveling state data 42a in the storage unit 25a.
収集データ生成部26aは、第1の実施形態の収集データ生成部26と以下の点を除いて同一の構成を有している。第1の実施形態の収集データ生成部26は、走行方向データ42-2を参照していたが、第2の実施形態の収集データ生成部26aは、走行方向データ42a-2を参照する際、走行方向データ42a-2に含まれる走行方向の水平成分の方向のみを参照する。
The collected data generation unit 26a has the same configuration as the collected data generation unit 26 of the first embodiment except for the following points. The collected data generation unit 26 of the first embodiment referred to the traveling direction data 42-2, but the collected data generation unit 26a of the second embodiment refers to the traveling direction data 42a-2. Only the direction of the horizontal component of the traveling direction included in the traveling direction data 42a-2 is referred to.
記憶部25aは、図10に示すように、上記したGPS観測データ40、準天頂衛星観測データ41、補正データ45、走行状態データ42a、点群データ43及び収集データ44を記憶する。
As shown in FIG. 10, the storage unit 25a stores the GPS observation data 40, the quasi-zenith satellite observation data 41, the correction data 45, the traveling state data 42a, the point group data 43, and the collected data 44.
走行軌跡データ生成部31aは、記憶部25aが記憶するGPS観測データ40と、準天頂衛星観測データ41と、補正データ45とに基づいて、車両1aの走行軌跡を示す走行軌跡データを生成する。なお、補正データ45は、GPS観測データ40や準天頂衛星観測データ41等から生成されるデータであり、補正データ45の中に観測時刻が含まれている。そのため、走行軌跡データ生成部31aは、GPS観測データ40及び準天頂衛星観測データ41の観測時刻に対応する補正データ45を用いて走行軌跡データを生成する。走行軌跡データ生成部31aが生成する走行軌跡データは、第1の実施形態の走行軌跡データ生成部31が生成する走行軌跡データとは異なり、鉛直方向の成分が含まれる。
The travel locus data generation unit 31a generates travel locus data indicating the travel locus of the vehicle 1a based on the GPS observation data 40 stored in the storage unit 25a, the quasi-zenith satellite observation data 41, and the correction data 45. The correction data 45 is data generated from GPS observation data 40, quasi-zenith satellite observation data 41, and the like, and the correction data 45 includes the observation time. Therefore, the travel locus data generation unit 31a generates travel locus data using the correction data 45 corresponding to the observation time of the GPS observation data 40 and the quasi-zenith satellite observation data 41. The travel locus data generated by the travel locus data generation unit 31a includes components in the vertical direction, unlike the travel locus data generated by the travel locus data generation unit 31 of the first embodiment.
走行軌跡解析部32aは、走行軌跡データ生成部31aが生成した走行軌跡データに基づいて、第1の実施形態において、図3に示した手法を鉛直方向にも拡張して、測定時刻ごとの車両1aの位置と、速度と、走行方向と、測定位置間隔とを推定する。ここで、測定時刻ごとの車両1aの位置には、水平成分及び鉛直成分が含まれるため、例えば、緯度、経度、標高で示される三次元座標で示される位置である。測定時刻ごとの車両1aの走行方向は、水平成分と鉛直成分とにより特定される方向である。
Based on the travel locus data generated by the travel locus data generation unit 31a, the travel locus analysis unit 32a extends the method shown in FIG. 3 in the vertical direction in the first embodiment to the vehicle for each measurement time. The position of 1a, the speed, the traveling direction, and the measurement position interval are estimated. Here, since the position of the vehicle 1a at each measurement time includes a horizontal component and a vertical component, it is a position indicated by three-dimensional coordinates indicated by, for example, latitude, longitude, and altitude. The traveling direction of the vehicle 1a at each measurement time is a direction specified by a horizontal component and a vertical component.
走行軌跡解析部32aは、推定した測定時刻ごとの車両1aの位置を示す推定位置データと、推定した測定位置間隔を示す推定測定位置間隔データと、推定した測定時刻ごとの車両1aの速度及び走行方向を含む推定走行状態データを生成する。
The travel locus analysis unit 32a includes estimated position data indicating the position of the vehicle 1a for each estimated measurement time, estimated measurement position interval data indicating the estimated measurement position interval, and speed and travel of the vehicle 1a for each estimated measurement time. Generate estimated driving condition data including direction.
走行軌跡解析部32aは、ある測定時刻の推定走行状態データと、記憶部25aが記憶する当該測定時刻に対応する走行状態データ42aとを対比し、速度の相違が予め定められる範囲内であり、かつ、走行方向の相違が予め定められる範囲内である場合、走行状態データ42aを利用して、推定位置データ、推定測定位置間隔データ及び推定走行状態データの精度を高める処理を行う。
The traveling locus analysis unit 32a compares the estimated traveling state data at a certain measurement time with the traveling state data 42a stored in the storage unit 25a corresponding to the measurement time, and the difference in speed is within a predetermined range. Moreover, when the difference in the traveling direction is within a predetermined range, the traveling state data 42a is used to perform a process of improving the accuracy of the estimated position data, the estimated measurement position interval data, and the estimated traveling state data.
ここで、速度の相違についての予め定められる範囲内及び走行方向の相違についての予め定められる範囲内とは、例えば、走行状態データ42aが示す車両1aの速度及び走行方向が、推定走行状態データが示す車両1aの速度及び走行方向と大きく異なっていない範囲内であって、走行状態データ42aが、推定位置データ、推定測定位置間隔データ及び推定走行状態データの精度を高める処理に利用できる程度の範囲内である。
Here, the predetermined range for the difference in speed and the predetermined range for the difference in the traveling direction are, for example, the speed and the traveling direction of the vehicle 1a indicated by the traveling state data 42a, and the estimated traveling state data. Within a range not significantly different from the speed and traveling direction of the vehicle 1a shown, the traveling state data 42a can be used for processing for improving the accuracy of the estimated position data, the estimated measurement position interval data, and the estimated running state data. Inside.
測定条件生成部33aは、走行軌跡解析部32aが生成した測定時刻ごとの推定位置データと、推定測定位置間隔データと、推定走行状態データとに基づいて、測定時刻におけるレーザレーダ装置21の測定条件を示す測定条件データを生成する。
The measurement condition generation unit 33a is the measurement condition of the laser radar device 21 at the measurement time based on the estimated position data for each measurement time generated by the travel locus analysis unit 32a, the estimated measurement position interval data, and the estimated travel state data. Generate measurement condition data indicating.
(鉛直方向に車両の位置が変動する場合のレーザ照射方向の変化)
図11及び図12を参照しつつ、鉛直方向に車両1aの位置が変動する場合のレーザ照射方向の変化について説明する。図11は、凹凸のある道路300を走行する車両1aを側面方向から見た図である。符号200で示す二重線の矢印は、車両1aが走行した軌跡を示しており、以下、走行軌跡200という。車両1aは、走行軌跡200の矢印が示すように、右方向に走行している。符号210で示す一点鎖線は、車両1aの平均標高を示しており、以下、車両平均標高210という。 (Change in laser irradiation direction when the position of the vehicle changes in the vertical direction)
With reference to FIGS. 11 and 12, changes in the laser irradiation direction when the position of thevehicle 1a fluctuates in the vertical direction will be described. FIG. 11 is a view of the vehicle 1a traveling on the uneven road 300 as viewed from the side surface. The double-lined arrow indicated by reference numeral 200 indicates the locus on which the vehicle 1a has traveled, and is hereinafter referred to as the travel locus 200. The vehicle 1a is traveling to the right as indicated by the arrow of the traveling locus 200. The alternate long and short dash line indicated by reference numeral 210 indicates the average altitude of the vehicle 1a, and is hereinafter referred to as the vehicle average altitude 210.
図11及び図12を参照しつつ、鉛直方向に車両1aの位置が変動する場合のレーザ照射方向の変化について説明する。図11は、凹凸のある道路300を走行する車両1aを側面方向から見た図である。符号200で示す二重線の矢印は、車両1aが走行した軌跡を示しており、以下、走行軌跡200という。車両1aは、走行軌跡200の矢印が示すように、右方向に走行している。符号210で示す一点鎖線は、車両1aの平均標高を示しており、以下、車両平均標高210という。 (Change in laser irradiation direction when the position of the vehicle changes in the vertical direction)
With reference to FIGS. 11 and 12, changes in the laser irradiation direction when the position of the
走行軌跡200は、道路300の凹凸の状況により上下に変化する。車両平均標高210と比較することにより、車両1aの位置が、平均標高よりも高いか低いかが分かることになる。例えば、符号310で示す区間では、車両1aが平均標高よりも高い所に位置しており、符号320で示す区間では、車両1aが平均標高よりも低い所に位置していることが分かる。第1の実施形態で述べた右左折、屈曲などの水平面上での走行方向の変化に比べると、鉛直面上での走行方向の変化は小さい。例えば、5%の上り下り坂では、100mの走行に対して、鉛直面上での変化は5mであるが、一般的には急な坂道と言われる。
The traveling locus 200 changes up and down depending on the unevenness of the road 300. By comparing with the vehicle average altitude 210, it is possible to know whether the position of the vehicle 1a is higher or lower than the average altitude. For example, it can be seen that in the section indicated by reference numeral 310, the vehicle 1a is located at a position higher than the average altitude, and in the section indicated by reference numeral 320, the vehicle 1a is located at a position lower than the average altitude. Compared with the change in the traveling direction on the horizontal plane such as turning left and right and bending described in the first embodiment, the change in the traveling direction on the vertical surface is small. For example, on a 5% uphill and downhill, the change on the vertical surface is 5m for a 100m run, but it is generally said to be a steep slope.
図12は、図11に示す道路300を走行する車両1aのレーザレーダ装置21のレーザ照射方向の変化を示した図である。なお、上記したように、一般的には急な坂道と言われるものであっても、鉛直面上での変化は小さいので、図12では、鉛直面上での走行方向の変化を大きく示すために、道路300の凹凸の変化を誇張して示している。
FIG. 12 is a diagram showing changes in the laser irradiation direction of the laser radar device 21 of the vehicle 1a traveling on the road 300 shown in FIG. As described above, even if the road is generally called a steep slope, the change on the vertical surface is small. Therefore, in FIG. 12, the change in the traveling direction on the vertical surface is largely shown. The change in the unevenness of the road 300 is exaggerated.
走行軌跡200に沿って示している複数の点線が、車両1aに搭載されたレーザレーダ装置21が、測定時刻ごとに照射したレーザ光の照射方向を示したレーザ照射ラインである。図12から分かるように、車両1aが等速で走行しており、かつ車両1aの標高が変わらない場合、レーザ照射ラインは、走行方向に対して垂直になり、等間隔で、平行に並ぶことになる。これに対して、車両1aの標高が上下に変化する場合、レーザ照射ラインは、車両1aの傾きに応じて角度が変わるため平行ではなく乱れが生じ、更に、等速でない場合、等間隔でもなくなる。
A plurality of dotted lines shown along the traveling locus 200 are laser irradiation lines indicating the irradiation direction of the laser light emitted by the laser radar device 21 mounted on the vehicle 1a at each measurement time. As can be seen from FIG. 12, when the vehicle 1a is traveling at a constant speed and the altitude of the vehicle 1a does not change, the laser irradiation lines are perpendicular to the traveling direction and are arranged in parallel at equal intervals. become. On the other hand, when the altitude of the vehicle 1a changes up and down, the angle of the laser irradiation line changes according to the inclination of the vehicle 1a, so that it is not parallel and turbulent. ..
そのため、車両1aの走行方向の鉛直成分を考慮しないまま、収集データ44に基づいて点群データ43の各点の位置を特定しても、レーザレーダ装置21の方向が正確でないことから、特定した点群データ43の各点の位置も正確にはならない。したがって、車両1aの標高の変化している間に収集された点群データ43は、右左折や屈曲の場合と同様に、信頼指標を「低い」、または、「無い」とするのが妥当である。
Therefore, even if the position of each point of the point cloud data 43 is specified based on the collected data 44 without considering the vertical component of the traveling direction of the vehicle 1a, the direction of the laser radar device 21 is not accurate. The position of each point in the point cloud data 43 is also not accurate. Therefore, it is appropriate that the point cloud data 43 collected while the altitude of the vehicle 1a is changing has a reliability index of "low" or "absent", as in the case of turning left or right or bending. be.
第2の実施形態では、走行軌跡データ生成部31aは、GPS観測データ40と、準天頂衛星観測データ41と、補正データ45とに基づいて走行軌跡データを生成する。上記したように、GPS観測データ40と、準天頂衛星観測データ41と、補正データ45とを利用することで、車両1aの標高を3~4cm程度の高い精度で推定することができる。
In the second embodiment, the travel locus data generation unit 31a generates travel locus data based on the GPS observation data 40, the quasi-zenith satellite observation data 41, and the correction data 45. As described above, by using the GPS observation data 40, the quasi-zenith satellite observation data 41, and the correction data 45, the altitude of the vehicle 1a can be estimated with a high accuracy of about 3 to 4 cm.
そのため、走行軌跡解析部32aが推定した測定時刻ごとの車両1aの位置は、例えば、図12の走行軌跡200上に丸印で示すように、実際の測定時刻においてレーザレーダ装置21がレーザ光を照射した位置に一致することになる。例えば、車両1aが等速で直進している場合に、走行軌跡解析部32aが、連続する4つの測定時刻の車両1aの位置を車両位置60,61,62,63として推定したとする。車両位置60,61,62,63において隣接する各々の間を結ぶベクトルを生成し、第1の実施形態において説明したように生成したベクトルを、直角を挟む2辺のうちの一方の辺とする直角三角形を仮定すると、直角三角形の直角を挟む他方の辺とレーザ照射ラインとが一致することになる。
Therefore, the position of the vehicle 1a at each measurement time estimated by the travel locus analysis unit 32a is, for example, as shown by a circle on the travel locus 200 in FIG. 12, the laser radar device 21 emits laser light at the actual measurement time. It will match the irradiated position. For example, suppose that when the vehicle 1a is traveling straight at a constant speed, the traveling locus analysis unit 32a estimates the positions of the vehicle 1a at four consecutive measurement times as the vehicle positions 60, 61, 62, 63. A vector connecting the adjacent portions at the vehicle positions 60, 61, 62, and 63 is generated, and the generated vector as described in the first embodiment is used as one of the two sides sandwiching the right angle. Assuming a right triangle, the other side of the right triangle that sandwiches the right angle coincides with the laser irradiation line.
車両1aの標高に変化が生じた場合に、走行軌跡解析部32aは、連続する4つの測定時刻の車両1aの位置を車両位置64,65,66,67として推定したとする。この場合も、車両位置64,65,66,67において隣接する各々の間を結ぶベクトルを生成した上で、上記のように生成したベクトルを、直角を挟む2辺のうちの一方の辺とする直角三角形を仮定すると、直角三角形の直角を挟む他方の辺と、傾いたレーザ照射ラインとが一致することになる。
It is assumed that when the altitude of the vehicle 1a changes, the traveling locus analysis unit 32a estimates the positions of the vehicle 1a at four consecutive measurement times as the vehicle positions 64, 65, 66, 67. Also in this case, after generating a vector connecting the adjacent ones at the vehicle positions 64, 65, 66, 67, the vector generated as described above is set as one of the two sides sandwiching the right angle. Assuming a right triangle, the other side of the right triangle that sandwiches the right angle coincides with the tilted laser irradiation line.
したがって、車両1aの位置の推定にGPS観測データ40と、準天頂衛星観測データ41とを用いることで、鉛直方向を考慮した車両1aの位置と走行方向を高い精度で推定可能であることが分かり、更に、車速データ42-1と、走行方向データ42a-2とを用いることで、より高い精度で推定することができることになる。
Therefore, by using the GPS observation data 40 and the quasi-zenith satellite observation data 41 to estimate the position of the vehicle 1a, it is possible to estimate the position and the traveling direction of the vehicle 1a in consideration of the vertical direction with high accuracy. Further, by using the vehicle speed data 42-1 and the traveling direction data 42a-2, it is possible to estimate with higher accuracy.
(第2の実施形態の処理)
収集データ生成部26aは、第1の実施形態の収集データ生成部26と同様の処理を行って収集データ44を生成する。図13は、データ補正部3aによる収集データ44を補正する処理の流れを示すフローチャートである。 (Processing of the second embodiment)
The collecteddata generation unit 26a performs the same processing as the collected data generation unit 26 of the first embodiment to generate the collected data 44. FIG. 13 is a flowchart showing a flow of processing for correcting the collected data 44 by the data correction unit 3a.
収集データ生成部26aは、第1の実施形態の収集データ生成部26と同様の処理を行って収集データ44を生成する。図13は、データ補正部3aによる収集データ44を補正する処理の流れを示すフローチャートである。 (Processing of the second embodiment)
The collected
走行軌跡データ生成部31aは、記憶部25aにおいて新たな測定時刻の収集データ44が収集データ生成部26aによって記録されたことを検出する(ステップSb1)。走行軌跡データ生成部31aは、新たに記録された収集データ44の測定時刻(以下「処理対象の測定時刻」ともいう。)を含む前後4つの観測時刻におけるGPS観測データ40と、準天頂衛星観測データ41と、補正データ45とを記憶部25aから読み出す。走行軌跡データ生成部31aは、読み出したGPS観測データ40と、準天頂衛星観測データ41と、補正データ45とに基づいて、鉛直成分を含んだ走行軌跡データを生成する(ステップSb2)。走行軌跡データ生成部31aは、生成した走行軌跡データと、処理対象の測定時刻とを走行軌跡解析部32aに出力する。
The travel locus data generation unit 31a detects that the collection data 44 at the new measurement time has been recorded by the collection data generation unit 26a in the storage unit 25a (step Sb1). The travel locus data generation unit 31a includes GPS observation data 40 at four observation times before and after including the measurement time of the newly recorded collected data 44 (hereinafter, also referred to as “measurement time to be processed”), and quasi-zenith satellite observation. The data 41 and the correction data 45 are read from the storage unit 25a. The travel locus data generation unit 31a generates travel locus data including a vertical component based on the read GPS observation data 40, the quasi-zenith satellite observation data 41, and the correction data 45 (step Sb2). The travel locus data generation unit 31a outputs the generated travel locus data and the measurement time of the processing target to the travel locus analysis unit 32a.
走行軌跡解析部32aは、走行軌跡データ生成部31aが出力する処理対象の測定時刻と、走行軌跡データとを取り込む。走行軌跡解析部32aは、図3に示した手法を鉛直方向にも拡張して、走行軌跡データに基づいて、処理対象の測定時刻における車両1aの三次元空間での位置と、速度と、水平成分及び鉛直成分を含んだ走行方向と、測定位置間隔とを推定する。走行軌跡解析部32aは、推定した車両1aの位置を示す推定位置データと、推定した測定位置間隔を示す推定測定位置間隔データと、推定した車両1aの速度及び走行方向を含む推定走行状態データを生成する(ステップSb3)。
The travel locus analysis unit 32a captures the measurement time of the processing target output by the travel locus data generation unit 31a and the travel locus data. The travel locus analysis unit 32a extends the method shown in FIG. 3 in the vertical direction, and based on the travel locus data, the position, speed, and horizontal of the vehicle 1a in the three-dimensional space at the measurement time of the processing target. The traveling direction including the component and the vertical component and the measurement position interval are estimated. The travel locus analysis unit 32a obtains estimated position data indicating the estimated position of the vehicle 1a, estimated measurement position interval data indicating the estimated measurement position interval, and estimated travel state data including the estimated speed and travel direction of the vehicle 1a. Generate (step Sb3).
走行軌跡解析部32aは、記憶部25aから処理対象の測定時刻の走行状態データ42aを読み出す。走行軌跡解析部32aは、読み出した走行状態データ42aと、生成した推定走行状態データとを対比し、速度の相違が予め定められる範囲内であり、かつ、走行方向の相違が予め定められる範囲内であるか否かを判定する(ステップSb4)。すなわち、走行軌跡解析部32aは、走行状態データ42aに含まれる車速データ42-1が示す車両1aの速度と、推定走行状態データに含まれる車両1aの速度との相違が予め定められる範囲内であるか否かを判定するとともに、走行状態データ42aに含まれる走行方向データ42a-2が示す車両1aの走行方向と、推定走行状態データに含まれる車両1aの走行方向との相違が予め定められる範囲内であるか否かを判定する。
The traveling locus analysis unit 32a reads out the traveling state data 42a at the measurement time to be processed from the storage unit 25a. The travel locus analysis unit 32a compares the read travel state data 42a with the generated estimated travel state data, and the difference in speed is within a predetermined range, and the difference in travel direction is within a predetermined range. (Step Sb4). That is, the traveling locus analysis unit 32a is within a range in which the difference between the speed of the vehicle 1a indicated by the vehicle speed data 42-1 included in the traveling state data 42a and the speed of the vehicle 1a included in the estimated traveling state data is predetermined. In addition to determining whether or not there is, the difference between the traveling direction of the vehicle 1a indicated by the traveling direction data 42a-2 included in the traveling state data 42a and the traveling direction of the vehicle 1a included in the estimated traveling state data is predetermined. Determine if it is within range.
走行軌跡解析部32aは、2つの速度の相違が予め定められる範囲内でないか、または、2つの走行方向の相違が予め定められる範囲内でないと判定した場合(ステップSb4、No)、処理対象の測定時刻と、生成した推定位置データとを含む正常判定指示信号を走行軌跡データ正常判定部35に出力する。
When the travel locus analysis unit 32a determines that the difference between the two speeds is not within the predetermined range or the difference between the two travel directions is not within the predetermined range (steps Sb4, No), the processing target is The normality determination instruction signal including the measurement time and the generated estimated position data is output to the travel locus data normality determination unit 35.
ステップSb5,Sb6,Sb7の処理は、図8に示したステップSa5,Sa6,Sa7と同一の処理が、走行軌跡データ正常判定部35、道路交通情報取得部34及び補正処理部36によって行われる。
The processing of steps Sb5, Sb6, and Sb7 is the same as that of steps Sa5, Sa6, and Sa7 shown in FIG. 8, and the traveling locus data normality determination unit 35, the road traffic information acquisition unit 34, and the correction processing unit 36 perform the same processing.
一方、走行軌跡解析部32aは、2つの速度の相違が予め定められる範囲内であり、かつ2つの走行方向の相違が予め定められる範囲内であると判定した場合(ステップSb4、Yes)、図4に示した手法を鉛直方向にも拡張して、推定位置データ、推定測定位置間隔データ及び推定走行状態データに対して、処理対象の測定時刻の走行状態データ42aを適用して、改めて推定位置データと、推定測定位置間隔データと、推定走行状態データとを生成する(ステップSb8)。
On the other hand, when the travel locus analysis unit 32a determines that the difference between the two speeds is within the predetermined range and the difference between the two travel directions is within the predetermined range (steps Sb4, Yes), the figure. The method shown in 4 is extended in the vertical direction, and the running state data 42a at the measurement time to be processed is applied to the estimated position data, the estimated measurement position interval data, and the estimated running state data, and the estimated position is again estimated. The data, the estimated measurement position interval data, and the estimated running state data are generated (step Sb8).
走行軌跡解析部32aは、記憶部25aから処理対象の測定時刻の直前の測定時刻に対応する収集データ44を読み出す。走行軌跡解析部32aは、読み出した収集データ44に含まれる測定位置間隔、車両1aの走行方向の各々が、推定測定位置間隔データが示す測定位置間隔、推定走行状態データが示す車両1aの走行方向の各々に一致するか否かを判定する(ステップSb9)。
The traveling locus analysis unit 32a reads out the collected data 44 corresponding to the measurement time immediately before the measurement time of the processing target from the storage unit 25a. In the travel locus analysis unit 32a, the measurement position interval included in the read collected data 44 and the travel direction of the vehicle 1a are each the measurement position interval indicated by the estimated measurement position interval data and the travel direction of the vehicle 1a indicated by the estimated travel state data. It is determined whether or not each of the above is matched (step Sb9).
走行軌跡解析部32aが、2つの測定位置間隔が一致し、2つの車両1aの走行方向が一致すると判定した場合(ステップSb9、Yes)、車両1aは処理対象の測定時刻において、等速で走行しており、かつ直進していることになる。そのため、処理対象の測定時刻の収集データ44を補正する必要がない。そのため、走行軌跡解析部32aは、収集データ44を補正する処理に進めずに、ステップSb13に処理を進める。
When the travel locus analysis unit 32a determines that the distance between the two measurement positions matches and the travel directions of the two vehicles 1a match (steps Sb9, Yes), the vehicle 1a travels at a constant speed at the measurement time to be processed. And you are going straight. Therefore, it is not necessary to correct the collected data 44 at the measurement time of the processing target. Therefore, the traveling locus analysis unit 32a does not proceed to the process of correcting the collected data 44, but proceeds to the process of step Sb13.
一方、走行軌跡解析部32aは、2つの測定位置間隔が一致しないか、または、2つの車両1aの走行方向が一致しないと判定した場合(ステップSb9、No)、改めて生成した推定位置データと、推定測定位置間隔データと、推定走行状態データと、処理対象の測定時刻とを測定条件生成部33aに出力する。
On the other hand, when the travel locus analysis unit 32a determines that the distance between the two measurement positions does not match or the travel directions of the two vehicles 1a do not match (steps Sb9, No), the estimated position data generated again and the estimated position data are used. The estimated measurement position interval data, the estimated running state data, and the measurement time of the processing target are output to the measurement condition generation unit 33a.
測定条件生成部33aは、走行軌跡解析部32aが出力した推定位置データと、車両1aにおいて固定設置されているレーザレーダ装置21の位置関係とに基づいて、処理対象の測定時刻におけるレーザレーダ装置21の三次元空間における位置を算出する。測定条件生成部33aは、走行軌跡解析部32aが出力する推定走行状態データに含まれる車両1aの走行方向の水平成分の方向の180°逆の向きをレーザレーダ装置21の方向の水平成分とし、車両1aの走行方向の鉛直成分の方向の180°逆の向きをレーザレーダ装置21の方向の鉛直成分とする。すなわち、車両1aの走行方向をベクトルで示した場合、当該ベクトルの逆ベクトルの方向が、レーザレーダ装置21の方向を示すことになる。そのため、測定条件生成部33aは、上記のように、レーザレーダ装置21の水平成分の方向と、鉛直成分の方向を求める。
The measurement condition generation unit 33a is based on the estimated position data output by the traveling locus analysis unit 32a and the positional relationship of the laser radar device 21 fixedly installed in the vehicle 1a, and the laser radar device 21 at the measurement time of the processing target. Calculate the position of the above in three-dimensional space. The measurement condition generation unit 33a uses the direction 180 ° opposite to the horizontal component direction of the vehicle 1a included in the estimated travel state data output by the travel locus analysis unit 32a as the horizontal component in the direction of the laser radar device 21. The direction 180 ° opposite to the direction of the vertical component in the traveling direction of the vehicle 1a is defined as the vertical component in the direction of the laser radar device 21. That is, when the traveling direction of the vehicle 1a is indicated by a vector, the direction of the inverse vector of the vector indicates the direction of the laser radar device 21. Therefore, the measurement condition generation unit 33a obtains the direction of the horizontal component and the direction of the vertical component of the laser radar device 21 as described above.
測定条件生成部33aは、算出したレーザレーダ装置21の位置と、レーザレーダ装置21の水平面上及び鉛直面上での方向と、推定測定位置間隔データが示す測定位置間隔と、推定走行状態データに含まれる車両1aの速度及び走行方向と、処理対象の測定時刻とを含むデータを測定条件データとして生成する(ステップSb10)。測定条件生成部33aは、生成した測定条件データを補正処理部36に出力する。
The measurement condition generation unit 33a uses the calculated position of the laser radar device 21, the direction of the laser radar device 21 on the horizontal plane and the vertical surface, the measurement position interval indicated by the estimated measurement position interval data, and the estimated running state data. Data including the speed and traveling direction of the included vehicle 1a and the measurement time to be processed is generated as measurement condition data (step Sb10). The measurement condition generation unit 33a outputs the generated measurement condition data to the correction processing unit 36.
補正処理部36は、測定条件生成部33aが出力する測定条件データを取り込む。補正処理部36は、記憶部25aが記憶する収集データ44の中から取り込んだ測定条件データに含まれている処理対象の測定時刻に対応する収集データ44を選択する。補正処理部36は、選択した収集データ44に含まれているデータを、測定条件データに含まれているデータに書き替えて、収集データ44を補正する(ステップSb11)。補正処理部36は、記憶部25aの点群データ43を参照し、測定条件データに含まれている処理対象の測定時刻に対応する点群データ43の信頼指標を「高い」に補正する(ステップSb12)。
The correction processing unit 36 takes in the measurement condition data output by the measurement condition generation unit 33a. The correction processing unit 36 selects the collection data 44 corresponding to the measurement time of the processing target included in the measurement condition data captured from the collection data 44 stored in the storage unit 25a. The correction processing unit 36 rewrites the data included in the selected collected data 44 with the data included in the measurement condition data, and corrects the collected data 44 (step Sb11). The correction processing unit 36 refers to the point cloud data 43 of the storage unit 25a, and corrects the reliability index of the point cloud data 43 corresponding to the measurement time of the processing target included in the measurement condition data to “high” (step). Sb12).
ステップSb13の処理は、図8に示したステップSa13と同一の処理が、補正処理部36によって行われる。
The processing of step Sb13 is the same as that of step Sa13 shown in FIG. 8, and the correction processing unit 36 performs the same processing.
上記の第2の実施形態の構成において、走行軌跡データ生成部31aは、観測時刻ごとに得られる車両1aの鉛直面上での位置を示すデータを取得し、取得した車両1aの鉛直面上での位置を示すデータに基づいて、車両1aの走行軌跡を示す走行軌跡データを生成する。走行軌跡解析部32aは、走行軌跡データを解析して、測定時刻ごとの車両1aの位置及び走行状態を推定する。測定条件生成部33aは、測定時刻ごとの車両1aの位置及び走行状態に基づいて、測定時刻ごとのレーザレーダ装置21の測定条件を示す測定条件データを生成する。補正処理部36は、測定条件データに基づいて、収集データ44を補正する。
In the configuration of the second embodiment described above, the travel locus data generation unit 31a acquires data indicating the position of the vehicle 1a on the vertical surface obtained at each observation time, and acquires the data indicating the position of the vehicle 1a on the vertical surface. Based on the data indicating the position of, the traveling locus data indicating the traveling locus of the vehicle 1a is generated. The travel locus analysis unit 32a analyzes the travel locus data and estimates the position and travel state of the vehicle 1a at each measurement time. The measurement condition generation unit 33a generates measurement condition data indicating the measurement conditions of the laser radar device 21 for each measurement time based on the position and running state of the vehicle 1a for each measurement time. The correction processing unit 36 corrects the collected data 44 based on the measurement condition data.
車両1aの標高が上下に変動する走行を車両1aがした場合、収集データ生成部26が生成した収集データ44に含まれるレーザレーダ装置21の位置や方向に誤差が含まれるが、誤差が含まれる収集データ44に対応する点群データ43に対して適切な信頼指標を付与していなかった。そのため、置局設計において、信頼度合いの低い点群データ43を利用してしまうことがあった。これに対して、第2の実施形態では、車両1aの標高を検出するため、車両1aの標高が上下に変動する走行を車両1aがした場合であっても、車両1aの位置と、水平面上及び鉛直面上での走行方向とを高い精度で推定することできる。それにより、収集データ44に含まれるレーザレーダ装置21の位置と、レーザレーダ装置の水平及び鉛直方向とを正確に補正することができる。そのため、車両1aの標高が上下に変動する走行を車両1aがした場合に収集された点群データ43の信頼度合いを高めることができるので、車両1aの標高が上下に変動する走行を車両1aがした場合に収集された点群データ43に対して信頼指標「高い」を付与することができる。したがって、レーザ照射ラインが乱れる箇所における車両の位置及び走行状態を従来よりも高精度に推定することにより、レーザ照射ラインの乱れによって信頼度合いが低下した点群データを利用可能にすることができ、例えば、置局設計を行う際に利用することができる点群データ43の信頼度合いを高めることができる。
When the vehicle 1a travels with the altitude of the vehicle 1a fluctuating up and down, an error is included in the position and direction of the laser radar device 21 included in the collected data 44 generated by the collected data generation unit 26, but the error is included. An appropriate reliability index was not given to the point cloud data 43 corresponding to the collected data 44. Therefore, the point cloud data 43 having a low degree of reliability may be used in the station design. On the other hand, in the second embodiment, since the altitude of the vehicle 1a is detected, the position of the vehicle 1a and the horizontal plane even when the vehicle 1a travels while the altitude of the vehicle 1a fluctuates up and down. And the traveling direction on the vertical surface can be estimated with high accuracy. Thereby, the position of the laser radar device 21 included in the collected data 44 and the horizontal and vertical directions of the laser radar device can be accurately corrected. Therefore, the reliability of the point cloud data 43 collected when the vehicle 1a travels with the altitude of the vehicle 1a fluctuating up and down can be increased, so that the vehicle 1a travels with the altitude of the vehicle 1a fluctuating up and down. In this case, the confidence index "high" can be given to the point cloud data 43 collected. Therefore, by estimating the position and running state of the vehicle in the place where the laser irradiation line is disturbed with higher accuracy than before, it is possible to use the point cloud data whose reliability is lowered due to the disturbance of the laser irradiation line. For example, it is possible to increase the reliability of the point cloud data 43 that can be used when designing the station.
なお、上記の第2の実施形態では、走行状態計測部24aは、ステアリングセンサから得られるデータに基づいて測定時刻ごとのステアリングの操舵角を計測し、水平水準器から得られるデータに基づいて測定時刻ごとの車両1aの傾きを計測するようにしているが、本発明は、当該実施の形態に限られない。走行状態計測部24aは、ステアリングセンサ及び水平水準器に替えて、三次元ジャイロセンサから得られるデータを取得し、取得したデータに基づいて、車両1aの水平面上及び鉛直面上での走行方向を算出するようにしてもよい。
In the second embodiment described above, the traveling state measuring unit 24a measures the steering angle of the steering at each measurement time based on the data obtained from the steering sensor, and measures based on the data obtained from the horizontal level. Although the inclination of the vehicle 1a is measured at each time, the present invention is not limited to the embodiment. The traveling state measuring unit 24a acquires data obtained from the three-dimensional gyro sensor instead of the steering sensor and the horizontal level, and based on the acquired data, determines the traveling direction of the vehicle 1a on the horizontal plane and on the vertical surface. It may be calculated.
(第3の実施形態)
図14は、第3の実施形態の点群データ収集システムγの構成を示すブロック図である。第3の実施形態の点群データ収集システムγにおいて、第1及び第2の実施形態の点群データ収集システムα,βと同一の構成については、同一の符号を付し、以下、異なる構成について説明する。点群データ収集システムγは、点群データ収集装置2bを備えた車両1bと、複数のGPS衛星10-1,10-2及び準天頂衛星11と、位置情報サービス事業者サーバ装置50とを備えている。車両1bは、例えば、自動車であり、上記したMMSに相当する。 (Third embodiment)
FIG. 14 is a block diagram showing a configuration of the point cloud data collection system γ according to the third embodiment. In the point cloud data collection system γ of the third embodiment, the same configurations as the point cloud data collection systems α and β of the first and second embodiments are designated by the same reference numerals, and the following, different configurations are used. explain. The point cloud data collection system γ includes avehicle 1b equipped with a point cloud data collection device 2b, a plurality of GPS satellites 10-1, 10-2 and a quasi-zenith satellite 11, and a location information service provider server device 50. ing. The vehicle 1b is, for example, an automobile and corresponds to the above-mentioned MMS.
図14は、第3の実施形態の点群データ収集システムγの構成を示すブロック図である。第3の実施形態の点群データ収集システムγにおいて、第1及び第2の実施形態の点群データ収集システムα,βと同一の構成については、同一の符号を付し、以下、異なる構成について説明する。点群データ収集システムγは、点群データ収集装置2bを備えた車両1bと、複数のGPS衛星10-1,10-2及び準天頂衛星11と、位置情報サービス事業者サーバ装置50とを備えている。車両1bは、例えば、自動車であり、上記したMMSに相当する。 (Third embodiment)
FIG. 14 is a block diagram showing a configuration of the point cloud data collection system γ according to the third embodiment. In the point cloud data collection system γ of the third embodiment, the same configurations as the point cloud data collection systems α and β of the first and second embodiments are designated by the same reference numerals, and the following, different configurations are used. explain. The point cloud data collection system γ includes a
点群データ収集装置2bは、レーザレーダ装置21、衛星電波受信用アンテナ22、無線電波受信用アンテナ27、情報受信部23a、走行状態計測部24a、記憶部25a、収集データ生成部26b及びデータ補正部3bを備える。
The point cloud data collecting device 2b includes a laser radar device 21, a satellite radio wave receiving antenna 22, a radio wave receiving antenna 27, an information receiving unit 23a, a traveling state measuring unit 24a, a storage unit 25a, a collected data generation unit 26b, and data correction. A part 3b is provided.
レーザレーダ装置21は、第1及び第2の実施形態と異なり、車両1bの天部に対して、符号100で示す一定の角度を設けて設置されている。以下、符号100で示す一定の角度を傾斜角度100という。そのため、レーザレーダ装置21の回転軸も傾斜角度100の角度で傾斜することになり、レーザレーダ装置21の方向は符号4bの矢印が示す方向となる。
Unlike the first and second embodiments, the laser radar device 21 is installed at a constant angle indicated by reference numeral 100 with respect to the top of the vehicle 1b. Hereinafter, the constant angle indicated by the reference numeral 100 is referred to as an inclination angle 100. Therefore, the rotation axis of the laser radar device 21 is also tilted at an angle of inclination of 100, and the direction of the laser radar device 21 is the direction indicated by the arrow of reference numeral 4b.
例えば、特開2017-156179には、「レーザスキャナの発振するスキャンラインの角度を鉛直方向に対して斜め方向となる様に当該装置を配置する」(段落[0018])ということが記載されており、このようにスキャンラインの角度を傾斜させることにより、「検査車両の走行速度を低速化したり、レーザスキャナの秒間あたりの照射点の数を多くすることなく、設備の状態を正確に検出することができる」(段落[0019])という効果が得られることが記載されている。
For example, Japanese Patent Application Laid-Open No. 2017-156179 describes that "the device is arranged so that the angle of the scan line oscillated by the laser scanner is oblique with respect to the vertical direction" (paragraph [0018]). By inclining the angle of the scan line in this way, "the state of the equipment is accurately detected without slowing down the traveling speed of the inspection vehicle or increasing the number of irradiation points per second of the laser scanner. It is stated that the effect of "can be done" (paragraph [0019]) can be obtained.
第3の実施形態では、特開2017-156179に示されている効果を得るために、レーザレーダ装置21を傾斜角度100の角度で傾斜させている。これにより、照射するレーザ光の照射方向も傾斜角度100の角度で傾斜することになる。そのため、傾斜角度100を考慮して収集データ44を生成する必要がある。車両1bの標高が上下に変動した場合、傾斜角度100を考慮して収集データ44を補正する必要がある。
In the third embodiment, the laser radar device 21 is tilted at an tilt angle of 100 in order to obtain the effect shown in Japanese Patent Application Laid-Open No. 2017-156179. As a result, the irradiation direction of the laser beam to be irradiated is also tilted at an inclination angle of 100. Therefore, it is necessary to generate the collected data 44 in consideration of the inclination angle 100. When the altitude of the vehicle 1b fluctuates up and down, it is necessary to correct the collected data 44 in consideration of the inclination angle 100.
収集データ生成部26bは、第2の実施形態の収集データ生成部26aと以下の点を除いて同一の構成を有している。第2の実施形態の収集データ生成部26aは、第1の実施形態の収集データ生成部26と同様に、レーザレーダ装置21の回転軸が、常に水平面に対して一定であるとし、レーザレーダ装置21の鉛直面上での方向を常に「0°」として収集データ44を生成している。これに対して、第3の実施形態の収集データ生成部26bは、レーザレーダ装置21の鉛直面上での方向を常に傾斜角度100の分、傾いた方向として収集データ44を生成する。
The collected data generation unit 26b has the same configuration as the collected data generation unit 26a of the second embodiment except for the following points. Similar to the collected data generation unit 26 of the first embodiment, the collected data generation unit 26a of the second embodiment assumes that the rotation axis of the laser radar device 21 is always constant with respect to the horizontal plane, and the laser radar device. The collected data 44 is generated with the direction of 21 on the vertical plane always set to "0 °". On the other hand, the collected data generation unit 26b of the third embodiment always generates the collected data 44 with the direction of the laser radar device 21 on the vertical plane as the tilted direction by the tilt angle of 100.
データ補正部3bは、走行軌跡データ生成部31a、走行軌跡解析部32a、測定条件生成部33b、道路交通情報取得部34、走行軌跡データ正常判定部35及び補正処理部36を備える。
The data correction unit 3b includes a travel locus data generation unit 31a, a travel locus analysis unit 32a, a measurement condition generation unit 33b, a road traffic information acquisition unit 34, a travel locus data normality determination unit 35, and a correction processing unit 36.
測定条件生成部33bは、走行軌跡解析部32aが生成した測定時刻ごとの推定位置データと、推定測定位置間隔データと、推定走行状態データと、傾斜角度100とに基づいて、測定時刻におけるレーザレーダ装置21の測定条件を示す測定条件データを生成する。
The measurement condition generation unit 33b is a laser radar at the measurement time based on the estimated position data for each measurement time, the estimated measurement position interval data, the estimated travel state data, and the inclination angle 100 generated by the travel locus analysis unit 32a. Generates measurement condition data indicating the measurement conditions of the device 21.
図15は、第2の実施形態の図11に示した道路300を、第3の実施形態の車両1bが走行した場合のレーザ照射ラインの変化を示した図である。第2の実施形態の車両1aと、第3の実施形態の車両1bとの形状は同一であるため、平均の車両標高は同一になり、走行軌跡も同一になる。そのため、図12と同じ符号を付して走行軌跡200と、車両平均標高210とを示している。
FIG. 15 is a diagram showing changes in the laser irradiation line when the vehicle 1b of the third embodiment travels on the road 300 shown in FIG. 11 of the second embodiment. Since the vehicle 1a of the second embodiment and the vehicle 1b of the third embodiment have the same shape, the average vehicle altitude is the same and the traveling locus is also the same. Therefore, the traveling locus 200 and the vehicle average altitude 210 are shown with the same reference numerals as those in FIG.
走行軌跡200に沿って示している複数の点線が、車両1bに搭載されたレーザレーダ装置21が、測定時刻ごとに照射したレーザ光の照射方向を示したレーザ照射ラインである。レーザレーダ装置21は、傾斜角度100の角度で傾斜している。そのため、レーザ照射ラインも全て傾斜角度100の角度で傾斜することになる。
A plurality of dotted lines shown along the traveling locus 200 are laser irradiation lines indicating the irradiation direction of the laser light emitted by the laser radar device 21 mounted on the vehicle 1b at each measurement time. The laser radar device 21 is tilted at an inclination angle of 100. Therefore, all the laser irradiation lines are also inclined at an inclination angle of 100.
第2の実施形態と同様に、走行軌跡解析部32aが推定した測定時刻ごとの車両1bの位置は、例えば、図15の走行軌跡200上に丸印で示すように、実際の測定時刻においてレーザレーダ装置21がレーザ光を照射した位置に一致することになる。例えば、車両1bが等速で直進している場合に、走行軌跡解析部32aが、連続する4つの測定時刻の車両1aの位置を車両位置60,61,62,63として推定したとする。車両位置60,61,62,63において隣接する各々の間を結ぶベクトルを生成し、第1の実施形態において説明したように生成したベクトルを、直角を挟む2辺のうちの一方の辺とする直角三角形を仮定する。第3の実施形態では、レーザレーダ装置21が傾斜角度100の角度で傾斜しているため、直角三角形の直角を挟む他方の辺を傾斜角度100の角度で傾斜させるとレーザ照射ラインに一致することになる。
Similar to the second embodiment, the position of the vehicle 1b for each measurement time estimated by the travel locus analysis unit 32a is, for example, a laser at the actual measurement time as shown by a circle on the travel locus 200 in FIG. It coincides with the position where the radar device 21 irradiates the laser beam. For example, suppose that when the vehicle 1b is traveling straight at a constant speed, the traveling locus analysis unit 32a estimates the positions of the vehicle 1a at four consecutive measurement times as the vehicle positions 60, 61, 62, 63. A vector connecting the adjacent portions at the vehicle positions 60, 61, 62, and 63 is generated, and the generated vector as described in the first embodiment is used as one of the two sides sandwiching the right angle. Assume a right triangle. In the third embodiment, since the laser radar device 21 is tilted at an angle of inclination of 100, tilting the other side of the right triangle sandwiching the right angle at an angle of tilt of 100 coincides with the laser irradiation line. become.
車両1bの標高に変化が生じた場合に、走行軌跡解析部32aは、連続する4つの測定時刻の車両1bの位置を車両位置64,65,66,67として推定したとする。この場合も、車両位置64,65,66,67において隣接する各々の間を結ぶベクトルを生成した上で、上記のように生成したベクトルを、直角を挟む2辺のうちの一方の辺とする直角三角形を仮定する。直角三角形の直角を挟む他方の辺を傾斜角度100の角度で傾斜させるとレーザ照射ラインに一致することになる。
It is assumed that when the altitude of the vehicle 1b changes, the traveling locus analysis unit 32a estimates the positions of the vehicle 1b at four consecutive measurement times as the vehicle positions 64, 65, 66, 67. Also in this case, after generating a vector connecting the adjacent ones at the vehicle positions 64, 65, 66, 67, the vector generated as described above is set as one of the two sides sandwiching the right angle. Assume a right triangle. If the other side of the right triangle sandwiching the right angle is tilted at an tilt angle of 100, it coincides with the laser irradiation line.
測定条件生成部33bは、走行軌跡解析部32aが生成した推定走行状態データに含まれる車両1bの走行方向に基づいて、レーザレーダ装置21の傾斜である傾斜角度100を考慮してレーザレーダ装置21の方向の水平成分及び鉛直成分を算出する。算出されたレーザレーダ装置21の方向の水平成分及び鉛直成分を用いることにより、正確に点群データ43の各点の三次元空間における位置を特定することが可能になる。
The measurement condition generation unit 33b is based on the travel direction of the vehicle 1b included in the estimated travel state data generated by the travel locus analysis unit 32a, and takes into consideration the inclination angle 100 which is the inclination of the laser radar device 21 and the laser radar device 21. Calculate the horizontal and vertical components in the direction of. By using the calculated horizontal component and vertical component in the direction of the laser radar device 21, it is possible to accurately specify the position of each point of the point cloud data 43 in the three-dimensional space.
(第3の実施形態の処理)
収集データ生成部26bは、第1の実施形態の収集データ生成部26と同様の処理を行って収集データ44を生成する。ただし、収集データ生成部26bは、レーザレーダ装置21の方向のうち鉛直面上での方向を常に傾斜角度100の分、傾いた方向として収集データ44を生成する。 (Processing of the third embodiment)
The collecteddata generation unit 26b performs the same processing as the collected data generation unit 26 of the first embodiment to generate the collected data 44. However, the collected data generation unit 26b generates the collected data 44 with the direction on the vertical surface of the direction of the laser radar device 21 always set as the tilted direction by the tilt angle of 100.
収集データ生成部26bは、第1の実施形態の収集データ生成部26と同様の処理を行って収集データ44を生成する。ただし、収集データ生成部26bは、レーザレーダ装置21の方向のうち鉛直面上での方向を常に傾斜角度100の分、傾いた方向として収集データ44を生成する。 (Processing of the third embodiment)
The collected
第3の実施形態における収集データ44を補正する処理は、図13に示した第2の実施形態の処理のうち、ステップSb10の処理以外については、第2の実施形態と同一の処理が行われる。
The process of correcting the collected data 44 in the third embodiment is the same as that of the second embodiment except for the process of step Sb10 among the processes of the second embodiment shown in FIG. ..
第3の実施形態では、ステップSb10の処理として以下の処理が行われる。測定条件生成部33bは、走行軌跡解析部32aが出力した推定位置データと、車両1bにおいて固定設置されているレーザレーダ装置21の位置関係とに基づいて、処理対象の測定時刻におけるレーザレーダ装置21の三次元空間における位置を算出する。測定条件生成部33bは、走行軌跡解析部32aが出力する推定走行状態データに含まれる車両1bの走行方向の水平成分の方向の180°逆の向きをレーザレーダ装置21の水平面上での方向とし、車両1bの走行方向の鉛直成分の方向の180°逆の向きに、傾斜角度100を加えた向きをレーザレーダ装置21の方向の鉛直成分とする。すなわち、車両1bの走行方向をベクトルで示した場合、当該ベクトルの逆ベクトルを鉛直方向に傾斜角度100の分傾けたベクトルの方が、レーザレーダ装置21の方向を示すことになる。そのため、測定条件生成部33bは、上記のように、レーザレーダ装置21の水平成分の方向と、鉛直成分の方向を求める。
In the third embodiment, the following processing is performed as the processing of step Sb10. The measurement condition generation unit 33b is based on the estimated position data output by the traveling locus analysis unit 32a and the positional relationship of the laser radar device 21 fixedly installed in the vehicle 1b, and the laser radar device 21 at the measurement time of the processing target. Calculate the position of the above in three-dimensional space. The measurement condition generation unit 33b sets the direction 180 ° opposite to the direction of the horizontal component in the travel direction of the vehicle 1b included in the estimated travel state data output by the travel locus analysis unit 32a as the direction on the horizontal plane of the laser radar device 21. The direction obtained by adding the inclination angle 100 to the direction 180 ° opposite to the direction of the vertical component in the traveling direction of the vehicle 1b is defined as the vertical component in the direction of the laser radar device 21. That is, when the traveling direction of the vehicle 1b is indicated by a vector, the vector obtained by tilting the inverse vector of the vector in the vertical direction by the inclination angle of 100 indicates the direction of the laser radar device 21. Therefore, the measurement condition generation unit 33b obtains the direction of the horizontal component and the direction of the vertical component of the laser radar device 21 as described above.
測定条件生成部33bは、算出したレーザレーダ装置21の位置と、レーザレーダ装置21の水平面上及び鉛直面上での方向と、推定測定位置間隔データが示す測定位置間隔と、推定走行状態データに含まれる車両1bの速度及び走行方向と、処理対象の測定時刻とを含むデータを測定条件データとして生成する。
The measurement condition generation unit 33b uses the calculated position of the laser radar device 21, the direction of the laser radar device 21 on the horizontal plane and the vertical surface, the measurement position interval indicated by the estimated measurement position interval data, and the estimated running state data. Data including the speed and traveling direction of the included vehicle 1b and the measurement time to be processed is generated as measurement condition data.
第3の実施形態では、第2の実施形態で得られる効果に加えて、以下のような効果を奏することになる。レーザレーダ装置21が傾斜して車両1bの天部に取り付けられていて、車両1bの標高が上下に変動する走行を車両1bがした場合、レーザレーダ装置21の方向の鉛直成分が複雑に変化することになる。これに対して、第3の実施形態の構成を適用することで、レーザレーダ装置21の傾斜を加味して、正確なレーザレーダ装置21の方向の鉛直成分を算出することが可能となる。それにより、収集データ44に含まれるレーザレーダ装置21の方向の鉛直成分を正確に補正することができる。そのため、車両1bの標高が上下に変動する走行を車両1bがした場合に収集された点群データ43の信頼度合いを高めることができ、点群データ43に対して信頼指標「高い」を付与することができる。したがって、レーザ照射ラインが乱れる箇所における車両の位置及び走行状態を従来よりも高精度に推定することにより、レーザ照射ラインの乱れによって信頼度合いが低下した点群データを利用可能にすることができ、例えば、置局設計を行う際に利用することができる点群データ43の信頼度合いを高めることができる。
In the third embodiment, in addition to the effects obtained in the second embodiment, the following effects are exhibited. When the laser radar device 21 is tilted and attached to the top of the vehicle 1b and the vehicle 1b travels in which the altitude of the vehicle 1b fluctuates up and down, the vertical component in the direction of the laser radar device 21 changes in a complicated manner. It will be. On the other hand, by applying the configuration of the third embodiment, it is possible to calculate an accurate vertical component in the direction of the laser radar device 21 in consideration of the inclination of the laser radar device 21. Thereby, the vertical component in the direction of the laser radar device 21 included in the collected data 44 can be accurately corrected. Therefore, the reliability of the point cloud data 43 collected when the vehicle 1b travels in which the altitude of the vehicle 1b fluctuates up and down can be increased, and the reliability index "high" is given to the point cloud data 43. be able to. Therefore, by estimating the position and running state of the vehicle in the place where the laser irradiation line is disturbed with higher accuracy than before, it is possible to use the point cloud data whose reliability is lowered due to the disturbance of the laser irradiation line. For example, it is possible to increase the reliability of the point cloud data 43 that can be used when designing the station.
なお、上記の第2及び第3の実施形態では、走行軌跡解析部32aは、ネットワーク型RTK-GNSS測位方式を利用して車両1a,1bの標高を検出していたが、他の方式を利用してもよい。例えば、参考文献2-1,2-2,2-3に示される光格子時計を利用してもよい。光格子時計とは、レーザ光を干渉させて作り出した光の波長より小さな多数の領域である光格子に原子を1つずつ収め,別のレーザ光を当て共鳴周波数を測定する原子時計である。アインシュタインの一般相対性理論では、重力が強い、すなわち標高が低い場所で時間が遅れる。この極めて僅かな遅れの測定は、18桁の精度の時計により可能になり、2台の時計の高さに数cmの差があれば、時間差の計測ができる。したがって、基準となる標高との時間差を計測することにより、相対論的測地、すなわち標高差の測定が可能になる。GNSSでは、3~4cm程度の精度で標高を検出することができるのに対して、光格子時計では、5cmの精度で標高を検出することが可能である。
In the second and third embodiments described above, the traveling locus analysis unit 32a detects the altitudes of the vehicles 1a and 1b by using the network type RTK-GNSS positioning method, but other methods are used. You may. For example, the optical lattice clock shown in References 2-1, 2, 2 and 2-3 may be used. An optical lattice clock is an atomic clock in which atoms are placed one by one in an optical lattice, which is a large number of regions smaller than the wavelength of light created by interfering with laser light, and another laser light is applied to measure the resonance frequency. In Einstein's general theory of relativity, time is delayed where gravity is strong, that is, at low altitudes. This extremely slight delay measurement is made possible by a clock with an accuracy of 18 digits, and if there is a difference of several centimeters in height between the two clocks, the time difference can be measured. Therefore, by measuring the time difference from the reference altitude, relativistic geodesy, that is, the measurement of the altitude difference becomes possible. While GNSS can detect the altitude with an accuracy of about 3 to 4 cm, the optical lattice clock can detect the altitude with an accuracy of 5 cm.
[参考文献2-1:“超高精度の「光格子時計」で標高差の測定に成功 ~火山活動の監視など、時計の常識を超える新たな応用に期待~”,科学技術振興機構(JST),東京大学,理化学研究所,国土地理院,先端光量子科学アライアンス,平成28年8月16日,[令和2年7月12日検索],インターネット(URL: https://www.jst.go.jp/pr/announce/20160816/)]
[Reference 2-1: "Successful measurement of elevation difference with ultra-high-precision" optical grid clock "-Expected to be new applications beyond the common sense of clocks such as monitoring of volcanic activity-", Japan Science and Technology Agency (JST) ), The University of Tokyo, RIKEN, Geospatial Information Authority of Japan, Advanced Photon Science Alliance, August 16, 2016, [Search on July 12, 2016], Internet (URL: https://www.jst. go.jp/pr/announce/20160816/)]
[参考文献2-2:“日本発の光格子時計 相対性理論で標高差を測定 次世代の世界標準に期待”,産経ニュース,2016年10月24日,[令和2年7月12日検索],インターネット(URL: https://www.sankei.com/life/news/161024/lif1610240029-n1.html)]]
[Reference 2-2: "Optical lattice clock from Japan, measuring elevation difference by the theory of relativity, expectation for the next generation world standard", Sankei News, October 24, 2016, [Rewa 2 July 12, 2016 Search], Internet (URL: https://www.sankei.com/life/news/161024/lif1610240029-n1.html)]]
[参考文献2-3:“世界初、「光格子時計」で標高差5cmの測定精度を実現 東京大学など”,大学ジャーナル,2016年8月22日,[令和2年7月12日検索],インターネット(URL: https://univ-journal.jp/9185/)]]
[Reference 2-3: "The world's first" optical grid clock "achieves a measurement accuracy of 5 cm above sea level, such as the University of Tokyo", University Journal, August 22, 2016, [Search on July 12, 2016 ], Internet (URL: https://univ-journal.jp/9185/)]]
上記の第1から第3の実施形態において、走行軌跡データ生成部31,31aが、準天頂衛星観測データ41に基づいて走行軌跡データを生成する際、例えば、MADOCA(Multi-GNSS Advanced Demonstration tool for Orbit and Clock Analysis)(参考文献3-1)、QZS準スタティック法(参考文献3-2)等の準天頂衛星観測データ41の測位データを補正する補正アルゴリズムを利用するようにしてもよい。
In the first to third embodiments described above, when the travel locus data generation units 31, 31a generate travel locus data based on the quasi-zenith satellite observation data 41, for example, MADOCA (Multi-GNSS Advanced Demonstration tool for) A correction algorithm for correcting the positioning data of the quasi-zenith satellite observation data 41 such as Orbit and Clock Analysis) (Reference 3-1) and the QZS quasi-static method (Reference 3-2) may be used.
第1の実施形態における点群データ収集システムαに対して、第2及び第3の実施形態において説明したネットワーク型RTK-GNSS測位方式を適用してもよい。この場合、走行軌跡データ生成部31,31aが、ネットワーク型RTK-GPS測位方式の測位処理(参考文献3-3)などの準天頂衛星観測データ41の測位データを補正する補正アルゴリズムを利用するようにしてもよい。これらの測位データを補正する補正アルゴリズムを利用することにより、走行軌跡データ生成部31,31aが行う車両1,1a,1bの位置、速度、走行方向の推定精度が向上することになる。
The network type RTK-GNSS positioning method described in the second and third embodiments may be applied to the point cloud data collection system α in the first embodiment. In this case, the travel locus data generation units 31, 31a should use a correction algorithm for correcting the positioning data of the quasi-zenith satellite observation data 41 such as the positioning process of the network type RTK-GPS positioning method (Reference 3-3). You may do it. By using the correction algorithm for correcting these positioning data, the estimation accuracy of the positions, speeds, and traveling directions of the vehicles 1, 1a, 1b performed by the traveling locus data generation units 31, 31a is improved.
三次元データ(3Dデータ)である点群データ43のノイズを除去する補正手法として、例えば、汎用的な処理を行う点群データ処理ソフトウェア(参考文献3-4)、壁状ノイズ除去処理(参考文献3-5)などが知られている。したがって、高精度な走行軌跡データを生成した上で、このような点群データ43のノイズを除去する補正手法を適用することにより、点群データ43を更に高精度に補正することができる。
As a correction method for removing noise from point cloud data 43, which is three-dimensional data (3D data), for example, point cloud data processing software (Reference 3-4) that performs general-purpose processing, wall noise removal processing (reference). Documents 3-5) and the like are known. Therefore, the point cloud data 43 can be corrected with higher accuracy by applying the correction method for removing the noise of the point cloud data 43 after generating the traveling locus data with high accuracy.
[参考文献3-1:小暮 聡(JAXA),“高精度測位技術の応用について”,第13回クリティカルソフトウェアワークショップ,2016年1月21日,[令和2年7月12日検索],インターネット(URL: https://www.ipa.go.jp/files/000050351.pdf),21~25ページに「6.高精度測位技術(MADOCA開発),複数GNSS対応の精密起動クロック推定ソフトウェア」が示されており,34ページに、水平方向誤差6cm、垂直方向誤差10cmに達するまでの時間が示されている。]
[Reference 3-1: Satoshi Kogure (JAXA), "Application of High Precision Positioning Technology", 13th Critical Software Workshop, January 21, 2016, [Search on July 12, 2016], Internet (URL: https://www.ipa.go.jp/files/000050351.pdf), pages 21-25, "6. High-precision positioning technology (MADOCA development), precision startup clock estimation software for multiple GNSS" Is shown, and on page 34, the time required to reach a horizontal error of 6 cm and a vertical error of 10 cm is shown. ]
[参考文献3-2:矢来博司,“準天頂衛星による高精度測位補正に関する技術開発”,第40回国土地理院報告会,2011年6月3日,[令和2年7月12日検索],インターネット(URL: https://www.gsi.go.jp/common/000061189.pdf),15~29ページに「(2)測量向け高精度測位補正技術の開発」が示されている。18ページに、補正情報受信・測位処理‘QZS準スタティック法’或いは‘QZS-QS(QZS-Quasi Static)法’が示されており、20ページに「試験観測結果(標準地区)RMS(Root Mean Square)(cm)として、水平:1.2~6.7 上下:2.0~8.4、(山間部)RMS(cm)として、水平:2.1~3.7 上下:3.4~5.3」が示されている。24ページに「みちびき実機を用いた精度検証」境界測量におけるTSでの2回測定の比較の許容誤差範囲が5mmであることが示されている。]
[Reference 3-2: Hiroshi Yaku, "Technology Development for High-precision Positioning Correction by Quasi-Zenith Satellite", 40th Geospatial Information Authority of Japan Report Meeting, June 3, 2011, [Search on July 12, 2011 ], Internet (URL: https://www.gsi.go.jp/common/000061189.pdf), pages 15-29 show "(2) Development of high-precision positioning correction technology for surveying". On page 18, the correction information reception / positioning process'QZS quasi-static method'or'QZS-QS (QZS-Quasi Static) method' is shown, and on page 20, "test observation result (standard area) RMS (Root Mean)" is shown. Square) (cm), horizontal: 1.2 to 6.7, vertical: 2.0 to 8.4, (mountainous area) RMS (cm), horizontal: 2.1 to 3.7, vertical: 3.4 ~ 5.3 "is shown. On page 24, it is shown that the permissible margin of error for the comparison of the two measurements with TS in the "Accuracy verification using the actual Michibiki machine" boundary survey is 5 mm. ]
[参考文献3-3:“準天頂衛星による高精度測位補正情報の生成・配信による技術開発 アルゴリズム詳細説明書”,国土交通省 国土地理院,平成20年3月25日,[令和2年7月12日検索],インターネット(URL: https://www.gsi.go.jp/common/000065384.pdf),61ページに「4.4 ネットワーク型RTK-GPS測位方式の測位処理」が示されている。]
[Reference 3-3: "Technical Development by Generating and Distributing High-precision Positioning Correction Information by Quasi-Zenith Satellite: Detailed Algorithm Manual", Geographical Survey Institute, Ministry of Land, Infrastructure, Transport and Tourism, March 25, 2008, [Reiwa 2nd year] Search on July 12], Internet (URL: https://www.gsi.go.jp/common/000065384.pdf), page 61 shows "4.4 Network-type RTK-GPS positioning method positioning process" Has been done. ]
[参考文献3-4:何啓源,窪田論,岡本桂輔,“地上レーザスキャナによる3次元点群データを用いた道路維持管理システムの検討”,情報処理学会,第80回全国大会,1ZC-01,p.4-539-540,2018年,[令和2年7月12日検索],インターネット(URL: https://www.ipsj.or.jp/event/taikai/80/ipsj_web2018/data/pdf/1ZC-01.html),図1に道路維持管理システムの定義 点群データ処理ソフトウェア(汎用的な処理)が示されている。]
[Reference 3-4: Keigen, Kubota, Keisuke Okamoto, "Examination of Road Maintenance System Using 3D Point Cloud Data by Ground Laser Scanner", Information Processing Society of Japan, 80th National Convention, 1ZC-01, p.4-539-540, 2018, [Search on July 12, 2nd year of Reiwa], Internet (URL: https://www.ipsj.or.jp/event/taikai/80/ipsj_web2018/data/pdf /1ZC-01.html), Fig. 1 shows the definition of the road maintenance system, point cloud data processing software (general-purpose processing). ]
[参考文献3-5:田中成典,今井龍一,中村健二,河野浩平,“点群座標データを用いた3次元モデルの自動生成に関する研究”,知能と知識(日本知能情報ファジィ学会誌),Vol.23,No.4,pp.572-590,2011年,[令和2年7月12日検索],インターネット(URL: http://www.nilim.go.jp/lab/qbg/ronbun/H23_fajii01.pdf),202ページの図6の提案手法の処理の流れに「壁状ノイズ除去処理」が示されている。]
[Reference 3-5: Shigenori Tanaka, Ryuichi Imai, Kenji Nakamura, Kohei Kono, "Study on Automatic Generation of 3D Models Using Point Cloud Coordinate Data", Intelligence and Knowledge (Journal of the Japan Intelligent Information Fuzzy Society), Vol. .23, No.4, pp.572-590, 2011, [Search on July 12, 2nd year of Reiwa], Internet (URL: http://www.nilim.go.jp/lab/qbg/ronbun/ H23_fajii01.pdf), “Wall noise removal processing” is shown in the processing flow of the proposed method in FIG. 6 on page 202. ]
上記の第1の実施形態においてGPS衛星10-1,10-2及び準天頂衛星11を利用せず、第2及び第3の実施形態においてGPS衛星10-1,10-2、準天頂衛星11、位置情報サービス事業者サーバ装置50を利用せず、その替わりにデジタルカメラやビデオカメラでの手ぶれ補正における手ぶれ検出機能を利用してもよい(例えば、参考文献4-1,4-2,4-3,4-4参照)。この場合、車両1,1a,1bは、例えば、ビデオカメラ等の撮像部と、撮像部から得られた映像を解析する映像解析部を備える。映像解析部は、撮像部から得られる映像から車両1,1a,1bが走行した軌跡が屈曲したり、上下に変動したりしていることを検出した場合、細かな変位、例えば、手ぶれに対応する振動、回転、移動量等の変位情報を検出することができる。この場合、映像解析部の解析の速度は任意に調整が可能であり、映像解析部の解析の時間間隔を第1から第3の実施形態における観測時刻の間隔である1秒よりも短い時間間隔、例えば、レーザレーダ装置21の測定時刻の間隔に一致させることもできるため、高い精度の変位情報を検出することが可能になる。検出した変位情報を、収集データ44の補正に用いることで、レーザレーダ装置21の詳細な水平方向及び鉛直方向の変位量などを特定することができる。特定したレーザレーダ装置21の変位量を利用することで、点群データの信頼度合いを高めることができ、信頼度合いを高めた点群データを置局設計に活かすことが可能になる。第1から第3の実施形態の構成に、手ぶれ検出機能を加えるようにしてもよい、手ぶれ検出機能では、上記のように観測時刻より短い間隔で変位情報を得ることが可能であり、観測時刻の間隔の間を補完する情報として利用することができ、観測時刻の間の車両1,1a,1bの移動を更に高い精度で推定することが可能になる。
The GPS satellites 10-1, 10-2 and the quasi-zenith satellite 11 are not used in the first embodiment described above, and the GPS satellites 10-1, 10-2 and the quasi-zenith satellite 11 are used in the second and third embodiments. , The location information service provider server device 50 may not be used, and instead, the camera shake detection function in the camera shake correction by a digital camera or a video camera may be used (for example, References 4-1 and 4-2, 4). See -3, 4-4). In this case, the vehicles 1, 1a and 1b include, for example, an image pickup unit such as a video camera and a video analysis unit that analyzes an image obtained from the image pickup unit. When the image analysis unit detects from the image obtained from the image pickup unit that the trajectory of the vehicles 1, 1a, 1b is bent or fluctuates up and down, it responds to small displacements, for example, camera shake. It is possible to detect displacement information such as vibration, rotation, and movement amount. In this case, the analysis speed of the video analysis unit can be arbitrarily adjusted, and the time interval of the analysis of the video analysis unit is shorter than the observation time interval of 1 second in the first to third embodiments. For example, since it is possible to match the measurement time interval of the laser radar device 21, it is possible to detect the displacement information with high accuracy. By using the detected displacement information for the correction of the collected data 44, it is possible to specify the detailed horizontal and vertical displacement amounts of the laser radar device 21 and the like. By using the displacement amount of the specified laser radar device 21, the reliability of the point cloud data can be increased, and the point cloud data with the increased reliability can be utilized in the station design. The camera shake detection function may be added to the configuration of the first to third embodiments. With the camera shake detection function, it is possible to obtain displacement information at intervals shorter than the observation time as described above, and the observation time. It can be used as information that complements the interval between the above, and it becomes possible to estimate the movement of the vehicles 1, 1a, 1b during the observation time with higher accuracy.
第1から第3の実施形態において、車両1,1a,1bにレーザレーダ装置21を搭載する際に、屈曲した走行や上下に変動する走行をする際の変位の影響を防ぐために、振動を抑制するヘキサポッド、ジンバルなどの台座に備え付ける構成を適用してもよい。ヘキサポッド、ジンバルなどは、カメラ映像や加速度、傾きを検出するセンサ情報に基づいて振動を抑え、カメラの水平を維持する補正制御技術を備えている(例えば、参考文献4-2,4-5,4-6参照)。そのため、ヘキサポッド、ジンバルなどの台座を車両1,1a,1bに備え、その台座にレーザレーダ装置21を取り付けることにより、振動が抑制された状態になる。そのため、レーザレーダ装置21の回転軸の方向を一定の方向に維持することができるので、点群データの各点の位置を特定する精度を向上させることができる。なお、当該構成では、ヘキサポッド、ジンバルなどによりレーザレーダ装置21の回転軸の方向が一定の方向に維持されるため、車両1,1a,1bの走行方向と、レーザレーダ装置21の方向との間に変位が生じる。そのため、生じる変位を考慮して、第1から第3の実施形態において、収集データ44を補正する必要がある。ヘキサポッド、ジンバルなどが調整する調整量を超えて傾きが生じる場合や、継続的に傾きを調整している状況、例えば、水平に近い状態で傾きの調整量が少ない状況に、更に、追加で傾きが加わり調整ができなくなる場合には、レーザレーダ装置21を水平に維持することができなくなり、その場合には、第1から第3の実施形態の構成による収集データの補正が活かされることになる。
In the first to third embodiments, when the laser radar device 21 is mounted on the vehicles 1, 1a, 1b, vibration is suppressed in order to prevent the influence of displacement when traveling in a bent manner or traveling up and down. A configuration provided on a pedestal such as a hexapod or a gimbal may be applied. Hexapods, gimbals, etc. are equipped with correction control technology that suppresses vibration based on camera images and sensor information that detects acceleration and tilt, and maintains the level of the camera (for example, References 4-2, 4-5). , 4-6). Therefore, by providing a pedestal such as a hexapod or a gimbal in the vehicles 1, 1a, 1b and attaching the laser radar device 21 to the pedestal, the vibration is suppressed. Therefore, since the direction of the rotation axis of the laser radar device 21 can be maintained in a constant direction, the accuracy of specifying the position of each point in the point cloud data can be improved. In this configuration, the direction of the rotation axis of the laser radar device 21 is maintained in a constant direction by the hexapod, gimbal, etc., so that the traveling directions of the vehicles 1, 1a, 1b and the direction of the laser radar device 21 Displacement occurs between them. Therefore, it is necessary to correct the collected data 44 in the first to third embodiments in consideration of the displacement that occurs. In addition, when the tilt exceeds the adjustment amount adjusted by the hexapod, gimbal, etc., or when the tilt is continuously adjusted, for example, when the tilt adjustment amount is small in a state close to horizontal. When the tilt is added and the adjustment cannot be performed, the laser radar device 21 cannot be maintained horizontally. In that case, the correction of the collected data according to the configurations of the first to third embodiments is utilized. Become.
[参考文献4-1:芹田保明,“デジタルカメラの手振れ補正機構”,光学,33巻,9号,p.550(26)-p.555(31),2004年、[令和2年7月12日検索],インターネット(URL: https://annex.jsap.or.jp/photonics/kogaku/public/33-09-kaisetsu5.pdf),551ページの表1に、おもな手ぶれ検出技術として「画像の動きベクトル検出方式:撮像素子から連続的に画像データを読み出して各画像間での像の移動状態からぶれを検出する」ことが示されている。]
[Reference 4-1: Yasuaki Serita, "Image Stabilizer for Digital Cameras", Optics, Vol. 33, No. 9, p.550 (26) -p.555 (31), 2004, [Reiwa 2nd Year 7] Search on 12th of March], Internet (URL: https://annex.jsap.or.jp/photonics/kogaku/public/33-09-kaisetsu5.pdf), Table 1 on page 551 shows the main camera shake detection technologies. "Image motion vector detection method: Image data is continuously read from the image sensor and blur is detected from the moving state of the image between each image". ]
[参考文献4-2:“手ぶれ補正機構”,Wikipedia,[令和2年7月12日検索],インターネット(URL: https://ja.wikipedia.org/wiki/手ぶれ補正機構),「電子式:デジタルカメラやデジタルビデオカメラで搭載されることが多い。撮影可能領域を一定のサイズに狭め、撮影の際にバッファメモリに画像を読み込み、最初に撮影した画像をそれ以降に撮影した画像を比較、その移動量を演算し、撮影可能領域を自動的にずらして撮影し記録する。外装式:ジンバル:ジンバル(Gimbal)は,ジャイロスコープやヤジロベエの原理を用いたスタビライザー。装着したカメラの水平を保ってくれるため,移動撮影時のブレを減少させることができる。]
[Reference 4-2: "Image Stabilizer", Wikipedia, [Search on July 12, 2nd year of Reiwa], Internet (URL: https://ja.wikipedia.org/wiki/Image Stabilizer), "Electronics Formula: Often installed in digital cameras and digital video cameras. The shootable area is narrowed to a certain size, the image is read into the buffer memory at the time of shooting, and the first shot image is taken after that. Comparison, calculation of the amount of movement, shooting and recording by automatically shifting the shootable area. Exterior type: Gimbal: Gimbal is a stabilizer that uses the principle of gyroscope and yajirobee. Horizontal of the attached camera. Because it keeps the image, it is possible to reduce blurring during moving shooting.]
[参考文献4-3:西一樹,“デジタル・ムービーのブレ計測・補正評価システム”,電気通信大学 新技術説明会,2008年5月13日,[令和2年7月12日検索],インターネット(URL: https://shingi.jst.go.jp/past_abst/abst/p/08/802/uec5.pdf),10ページに手ブレ検出結果の統計処理として「手ぶれの3D軌跡⇒多数枚の撮影画像に対する手ブレ検出結果をプロット+主成分分析(PCA)⇒手ブレ検出データの分散図とその傾向を示す楕円体」が示されている。]
[Reference 4-3: Kazuki Nishi, "Digital Movie Blur Measurement / Correction Evaluation System", Telecommunications University New Technology Briefing Session, May 13, 2008, [Search on July 12, 2008], Internet (URL: https://shingi.jst.go.jp/past_abst/abst/p/08/802/uec5.pdf), on page 10 as statistical processing of camera shake detection results, "3D trajectory of camera shake ⇒ many sheets Plot the camera shake detection results for the captured image + Principal component analysis (PCA) ⇒ Dispersion diagram of camera shake detection data and an ellipsoid showing the tendency "is shown. ]
[参考文献4-4:丸山裕士,山口佳樹,児玉祐悦(筑波大),“FPGAによるブレ補正機構に関する研究”,FIT2014(第13回情報科学技術フォーラム),第1分冊,RC-004,p23-p28,2014年,[令和2年7月12日検索],インターネット(URL: https://www.ipsj.or.jp/award/9faeag0000004eyo-att/RC-004.pdf),1ページに「2.オプティカルフロー検出とブレ補正手法(図1.フレーム内オプティカルフローとブレ補正の違い)、2.1.フレーム移動量の推定方法(図2.フレーム移動量の推定方法)」が示されている。]
[References 4-4: Hiroshi Maruyama, Yoshiki Yamaguchi, Yuetsu Kodama (University of Tsukuba), "Study on Image Stabilization Mechanism by FPGA", FIT2014 (13th Information Science and Technology Forum), Volume 1, RC-004, p23 -p28, 2014, [Search on July 12, 2014], Internet (URL: https://www.ipsj.or.jp/award/9faeag0000004eyo-att/RC-004.pdf), on page 1. "2. Optical flow detection and image stabilization method (Fig. 1. Difference between in-frame optical flow and image stabilization), 2.1. Frame movement amount estimation method (Fig. 2. Frame movement amount estimation method)" is shown. ing. ]
[参考文献4-5:ステファン・ボーンドラン,スコット・ジョーダン,“圧電式ヘキサポッドモーションシステム による、手ぶれ補正と画像解像度の改善”,featureイメージング,Laser Focus World Japan,p.26-29,2017年1月,[令和2年7月12日検索],インターネット(URL: http://ex-press.jp/wp-content/uploads/2017/01/LFWJ1701ft4.pdf),29ページに「ヘキサポッドのドライブの種類と応用:H-840ヘキサポッドを用いたドローンカメラのぶれ補正試験に加えて、工業オートメーションと、移動する車両や船舶のモーション安定化を目的とした「PI H-900KSCO」ヘキサポッドも設計されている」ことが示されている。「PI H-900KSCO」ヘキサポッドでは「最大130ポンド(約59kg)の負荷に対応しつつ,最大で200mm(X,Y,Z軸方向)、66°(ピッチ,ヨー,ロール)のモーション範囲をそれぞれ80mm/sと30°/sの速度で提供する」ことが示されている。]
[Reference 4-5: Stephen Boldran, Scott Jordan, "Image Stabilization and Improvement of Image Resolution by Pietrical Hexapod Motion System", feature Imaging, Laser Focus World Japan, p.26-29, 2017 January, [Search on July 12, 2nd year of Reiwa], Internet (URL: http://ex-press.jp/wp-content/uploads/2017/01/LFWJ1701ft4.pdf), "Hexapod" on page 29 Drive types and applications: "PI H-900KSCO" Hexapod for industrial automation and motion stabilization of moving vehicles and ships, in addition to the image stabilization test of drone cameras using H-840 Hexapod. Is also designed. " The "PI H-900KSCO" hexapod has a maximum motion range of 200 mm (X, Y, Z axis direction) and 66 ° (pitch, yaw, roll) while supporting a load of up to 130 pounds (about 59 kg). It is provided at speeds of 80 mm / s and 30 ° / s, respectively. " ]
[参考文献4-6:川村和弘,“まるで映画のような滑らかで手ブレが無い映像が、片手で簡単に撮れる!ドローンのカメラと空撮技術を転用! 3軸電動スタビライザー搭載カメラ「Osmo」登場”,価格.comマガジン,2015年10月26日,[令和2年7月12日検索],インターネット(URL: https://kakakumag.com/camera/?id=3477),「カメラがグリグリと回転し,傾きや向きを検知して水平と保つ」]
[Reference 4-6: Kazuhiro Kawamura, "You can easily take a movie-like smooth and camera-free image with one hand! Divert the drone camera and aerial photography technology! 3-axis electric stabilizer-equipped camera" Osmo " Appearance ", Price.com Magazine, October 26, 2015, [Search on July 12, 2015], Internet (URL: https://kakakumag.com/camera/?id=3477)," Camera It rotates with a muzzle, detects tilt and orientation, and keeps it horizontal. "]]
上記の第1から第3の実施形態において、図8と図13に示したステップSa8,Sb8では、推定位置データ、推定測定位置間隔データ及び推定走行状態データに走行状態データ42,42aを適用して、改めて推定位置データ、推定測定位置間隔データ及び推定走行状態データを生成するようにしているが、本発明の構成は、当該実施の形態に限られない。ステップSa3,Sb3の処理において、走行軌跡データと、走行状態データ42,42aとに基づいて、推定位置データ、推定測定位置間隔データ及び推定走行状態データを生成し、ステップSa8,Sb8の処理を行わないようにしてもよい。この場合、推定位置データ、推定測定位置間隔データ及び推定走行状態データを生成する処理が1回になるため、処理量を軽減化することができる。その一方で、ステップSa4,Sb4の判定処理において、対比する推定走行状態データと、走行状態データとの相違が少なくなる。そのため、ステップSa4,Sb4において、走行軌跡解析部32,32aが「Yes」の判定を行うことが多くなる可能性がある。したがって、最終的に得られる推定位置データ、推定測定位置間隔データ及び推定走行状態データの精度という観点でみると、ステップSa8,Sb8の処理をステップSa3,Sb3の処理としてまとめて行うよりも、図8と図13に示した処理の方が優れている。走行軌跡データのみから推定位置データ、推定測定位置間隔データ及び推定走行状態データを生成するようにして、ステップSa8,Sb8を行わないようにしてもよい。
In the first to third embodiments described above, in steps Sa8 and Sb8 shown in FIGS. 8 and 13, the running state data 42 and 42a are applied to the estimated position data, the estimated measurement position interval data and the estimated running state data. Therefore, the estimated position data, the estimated measurement position interval data, and the estimated running state data are generated again, but the configuration of the present invention is not limited to the embodiment. In the processing of steps Sa3 and Sb3, the estimated position data, the estimated measurement position interval data and the estimated traveling state data are generated based on the traveling locus data and the traveling state data 42 and 42a, and the processing of steps Sa8 and Sb8 is performed. You may not have it. In this case, since the processing for generating the estimated position data, the estimated measurement position interval data, and the estimated running state data is performed once, the processing amount can be reduced. On the other hand, in the determination process of steps Sa4 and Sb4, the difference between the estimated running state data to be compared and the running state data is reduced. Therefore, in steps Sa4 and Sb4, the traveling locus analysis units 32 and 32a may often determine "Yes". Therefore, from the viewpoint of the accuracy of the estimated position data, the estimated measurement position interval data, and the estimated running state data finally obtained, the process of steps Sa8 and Sb8 is not collectively performed as the process of steps Sa3 and Sb3. 8 and the process shown in FIG. 13 are superior. The estimated position data, the estimated measurement position interval data, and the estimated traveling state data may be generated only from the traveling locus data, and the steps Sa8 and Sb8 may not be performed.
上記の第1から第3の実施形態において、収集データ44には、測定時刻と、レーザレーダ装置21の位置と、レーザレーダ装置21の水平成分及び鉛直成分を含んだ方向と、測定位置間隔と、車両1,1a,1bの速度と、車両1,1a,1bの走行方向を含むようにしているが、本発明の構成は、当該実施の形態に限られない。点群データ43における各点の三次元空間での位置が特定できればよいため、第1の実施形態では、収集データ44は、少なくとも測定時刻と、レーザレーダ装置21の位置と、レーザレーダ装置21の水平成分の方向が含まれるようにしてもよく、その場合、第1の実施形態の走行軌跡解析部32は、測定時刻ごとの車両1の水平面上での位置を推定する。次に、走行軌跡解析部32は、測定時刻ごとの車両1の水平面上での走行方向のみを車両1の走行状態として推定する。測定条件生成部33は、測定時刻と、レーザレーダ装置21の位置と、レーザレーダ装置21の水平成分の方向とを含む測定条件データを生成すればよいことになる。第2及び第3の実施形態では、収集データ44は、少なくとも測定時刻と、レーザレーダ装置21の位置と、レーザレーダ装置21の水平成分及び鉛直成分の方向が含まれるようにしてもよく、その場合、第2及び第3の実施形態の走行軌跡解析部32aは、まず測定時刻ごとの車両1aの位置を推定する。次に、走行軌跡解析部32aは、測定時刻ごとの車両1aの水平面上及び鉛直面上での走行方向のみを車両1aの走行状態として推定する。測定条件生成部33a,33bは、測定時刻と、レーザレーダ装置21の位置と、レーザレーダ装置21の水平成分及び鉛直成分の方向とを含む測定条件データを生成すればよいことになる。
In the first to third embodiments described above, the collected data 44 includes the measurement time, the position of the laser radar device 21, the direction including the horizontal component and the vertical component of the laser radar device 21, and the measurement position interval. , The speed of the vehicles 1, 1a, 1b and the traveling direction of the vehicles 1, 1a, 1b are included, but the configuration of the present invention is not limited to the embodiment. Since it is sufficient that the position of each point in the point group data 43 in the three-dimensional space can be specified, in the first embodiment, the collected data 44 includes at least the measurement time, the position of the laser radar device 21, and the laser radar device 21. The direction of the horizontal component may be included, in which case the travel locus analysis unit 32 of the first embodiment estimates the position of the vehicle 1 on the horizontal plane at each measurement time. Next, the traveling locus analysis unit 32 estimates only the traveling direction of the vehicle 1 on the horizontal plane at each measurement time as the traveling state of the vehicle 1. The measurement condition generation unit 33 may generate measurement condition data including the measurement time, the position of the laser radar device 21, and the direction of the horizontal component of the laser radar device 21. In the second and third embodiments, the collected data 44 may include at least the measurement time, the position of the laser radar device 21, and the directions of the horizontal and vertical components of the laser radar device 21. In this case, the traveling locus analysis unit 32a of the second and third embodiments first estimates the position of the vehicle 1a at each measurement time. Next, the traveling locus analysis unit 32a estimates only the traveling direction of the vehicle 1a on the horizontal plane and on the vertical surface at each measurement time as the traveling state of the vehicle 1a. The measurement condition generation units 33a and 33b may generate measurement condition data including the measurement time, the position of the laser radar device 21, and the directions of the horizontal component and the vertical component of the laser radar device 21.
上記の第1から第3の実施形態の点群データ収集装置2,2a,2bにおけるデータ補正部3,3a,3bを、単体の装置であるデータ補正装置として構成してもよい。
上記の第1から第3の実施形態では、道路を走行する車両1を例に説明したが、車両1に限らずドローン等の移動体が用いられてもよい。このように構成される場合、ドローン等の移動体に点群データ収集装置2が備えられる。 The data correction units 3, 3a, 3b in the point cloud data collection devices 2, 2a, 2b of the first to third embodiments may be configured as a single device, the data correction device.
In the first to third embodiments described above, thevehicle 1 traveling on the road has been described as an example, but the vehicle 1 is not limited to the vehicle 1, and a moving body such as a drone may be used. When configured in this way, a moving object such as a drone is provided with a point cloud data collecting device 2.
上記の第1から第3の実施形態では、道路を走行する車両1を例に説明したが、車両1に限らずドローン等の移動体が用いられてもよい。このように構成される場合、ドローン等の移動体に点群データ収集装置2が備えられる。 The
In the first to third embodiments described above, the
上述した実施形態におけるデータ補正部3,3a,3bをコンピュータで実現するようにしてもよい。その場合、この機能を実現するためのプログラムをコンピュータ読み取り可能な記録媒体に記録して、この記録媒体に記録されたプログラムをコンピュータシステムに読み込ませ、実行することによって実現してもよい。なお、ここでいう「コンピュータシステム」とは、OSや周辺機器等のハードウェアを含むものとする。また、「コンピュータ読み取り可能な記録媒体」とは、フレキシブルディスク、光磁気ディスク、ROM、CD-ROM等の可搬媒体、コンピュータシステムに内蔵されるハードディスク等の記憶装置のことをいう。さらに「コンピュータ読み取り可能な記録媒体」とは、インターネット等のネットワークや電話回線等の通信回線を介してプログラムを送信する場合の通信線のように、短時間の間、動的にプログラムを保持するもの、その場合のサーバやクライアントとなるコンピュータシステム内部の揮発性メモリのように、一定時間プログラムを保持しているものも含んでもよい。また上記プログラムは、前述した機能の一部を実現するためのものであってもよく、さらに前述した機能をコンピュータシステムにすでに記録されているプログラムとの組み合わせで実現できるものであってもよく、FPGA(Field Programmable Gate Array)等のプログラマブルロジックデバイスを用いて実現されるものであってもよい。
The data correction units 3, 3a, 3b in the above-described embodiment may be realized by a computer. In that case, a program for realizing this function may be recorded on a computer-readable recording medium, and the program recorded on the recording medium may be read by a computer system and executed. The term "computer system" as used herein includes hardware such as an OS and peripheral devices. Further, the "computer-readable recording medium" refers to a portable medium such as a flexible disk, a magneto-optical disk, a ROM, or a CD-ROM, and a storage device such as a hard disk built in a computer system. Further, a "computer-readable recording medium" is a communication line for transmitting a program via a network such as the Internet or a communication line such as a telephone line, and dynamically holds the program for a short period of time. It may also include a program that holds a program for a certain period of time, such as a volatile memory inside a computer system that is a server or a client in that case. Further, the above program may be for realizing a part of the above-mentioned functions, and may be further realized for realizing the above-mentioned functions in combination with a program already recorded in the computer system. It may be realized by using a programmable logic device such as FPGA (Field Programmable Gate Array).
以上、この発明の実施形態について図面を参照して詳述してきたが、具体的な構成はこの実施形態に限られるものではなく、この発明の要旨を逸脱しない範囲の設計等も含まれる。
As described above, the embodiment of the present invention has been described in detail with reference to the drawings, but the specific configuration is not limited to this embodiment, and the design and the like within a range not deviating from the gist of the present invention are also included.
点群データを収集するMMSに適用することが可能である。
It can be applied to MMS that collects point cloud data.
1…車両、2…点群データ収集装置、3…データ補正部、4…レーザレーダ装置の方向、10-1,10-2…GPS衛星、11…準天頂衛星、21…レーザレーダ装置、22…衛星電波受信用アンテナ、23…情報受信部、24…走行状態計測部、25…記憶部、26…収集データ生成部、31…走行軌跡データ生成部、32…走行軌跡解析部、33…測定条件生成部、34…道路交通情報取得部、35…走行軌跡データ正常判定部、36…補正処理部
1 ... Vehicle, 2 ... Point group data collection device, 3 ... Data correction unit, 4 ... Direction of laser radar device, 10-1, 10-2 ... GPS satellite, 11 ... Quasi-zenith satellite, 21 ... Laser radar device, 22 ... Satellite radio wave receiving antenna, 23 ... Information receiving unit, 24 ... Driving state measurement unit, 25 ... Storage unit, 26 ... Collected data generation unit, 31 ... Travel locus data generation unit, 32 ... Travel locus analysis unit, 33 ... Measurement Condition generation unit, 34 ... Road traffic information acquisition unit, 35 ... Travel locus data normality determination unit, 36 ... Correction processing unit
Claims (8)
- 移動体に搭載されたレーザレーダ装置が、測定時刻ごとにレーザ光を照射することにより測定対象物までの距離を計測して点群データを生成する際に前記点群データに対応付けて生成される収集データであって観測時刻ごとに得られる前記移動体の水平面上での位置を示す水平面位置データから推定される前記レーザレーダ装置の測定条件を示す収集データを補正するデータ補正方法であって、
前記観測時刻ごとに得られる前記水平面位置データよりも高精度の水平面位置データを取得するか、または、前記移動体の鉛直面上での位置を示す鉛直面位置データを取得し、取得した前記高精度の水平面位置データ、または、前記鉛直面位置データに基づいて、前記移動体の移動軌跡を示す移動軌跡データを生成する移動軌跡データ生成データ生成ステップと、
前記移動軌跡データを解析して、前記測定時刻ごとの前記移動体の位置及び移動状態を推定する移動軌跡解析ステップと、
前記測定時刻ごとの前記移動体の位置及び移動状態に基づいて、前記測定時刻ごとの前記レーザレーダ装置の測定条件を示す測定条件データを生成する測定条件生成ステップと、
前記測定条件データに基づいて、前記収集データを補正する補正処理ステップと、
を含むデータ補正方法。 When the laser radar device mounted on the moving body measures the distance to the object to be measured by irradiating the laser beam at each measurement time and generates the point group data, it is generated in association with the point group data. This is a data correction method for correcting the collected data indicating the measurement conditions of the laser radar device estimated from the horizontal plane position data indicating the position of the moving object on the horizontal plane obtained at each observation time. ,
The horizontal plane position data with higher accuracy than the horizontal plane position data obtained at each observation time is acquired, or the vertical plane position data indicating the position of the moving object on the vertical plane is acquired and the acquired height is obtained. A movement locus data generation data generation step that generates movement locus data indicating the movement locus of the moving body based on accurate horizontal plane position data or the vertical plane position data.
A movement locus analysis step that analyzes the movement locus data and estimates the position and movement state of the moving body at each measurement time, and a movement locus analysis step.
A measurement condition generation step for generating measurement condition data indicating measurement conditions of the laser radar device for each measurement time based on the position and moving state of the moving body at each measurement time.
A correction processing step for correcting the collected data based on the measurement condition data, and
Data correction method including. - 前記高精度の水平面位置データとは、前記観測時刻の間隔と同一の時間間隔で得られるデータであって前記収集データを生成する際に用いられた前記水平面位置データよりも誤差の少ない水平面位置データであるか、または、前記観測時刻の間隔よりも短い時間間隔で得られる水平面位置データである、
請求項1に記載のデータ補正方法。 The high-precision horizontal plane position data is data obtained at the same time interval as the observation time interval, and has less error than the horizontal plane position data used when generating the collected data. Or, it is horizontal plane position data obtained at a time interval shorter than the observation time interval.
The data correction method according to claim 1. - 前記レーザレーダ装置が前記移動体に対して傾斜して搭載されている場合、
前記測定条件生成ステップにおいて、前記移動体の位置及び移動状態と、前記傾斜の角度とに基づいて前記測定時刻ごとの前記測定条件データを生成する、
請求項1又は2に記載のデータ補正方法。 When the laser radar device is mounted at an angle with respect to the moving body,
In the measurement condition generation step, the measurement condition data for each measurement time is generated based on the position and the moving state of the moving body and the angle of inclination.
The data correction method according to claim 1 or 2. - 前記補正処理ステップにおいて、前記収集データを補正した場合、補正した前記収集データに対応する点群データに対して高い信頼度合いを示す信頼指標を付与する、
請求項1から3のいずれか一項に記載のデータ補正方法。 When the collected data is corrected in the correction processing step, a reliability index indicating a high degree of reliability is given to the point cloud data corresponding to the corrected collected data.
The data correction method according to any one of claims 1 to 3. - 前記移動軌跡解析ステップにおいて、前記測定時刻において移動体が等速で移動しており、かつ直進していると判定した場合、前記測定条件生成ステップにおいて前記測定条件データを生成せず、
前記移動軌跡解析ステップにおいて、前記測定時刻において移動体が等速で移動していないか、または、直進していないと判定した場合、前記測定条件生成ステップにおいて前記測定条件データを生成する、
請求項1から4のいずれか一項に記載のデータ補正方法。 When it is determined in the movement locus analysis step that the moving body is moving at a constant speed and traveling straight at the measurement time, the measurement condition data is not generated in the measurement condition generation step.
When it is determined in the movement locus analysis step that the moving body is not moving at a constant speed or is not traveling straight at the measurement time, the measurement condition data is generated in the measurement condition generation step.
The data correction method according to any one of claims 1 to 4. - 前記移動軌跡解析ステップにおいて、推定した前記移動体の移動状態を示す推定移動状態データを生成し、前記移動体が内部に備える移動状態計測部が計測して生成した移動状態データであって前記推定移動状態データの測定時刻に対応する移動状態データと、前記推定移動状態データとの相違が、予め定められる範囲内である場合、前記移動軌跡データと、前記移動状態データとに基づいて、前記測定時刻ごとの前記移動体の位置及び移動状態を推定する、
請求項1から5のいずれか一項に記載のデータ補正方法。 In the movement locus analysis step, the estimated movement state data indicating the estimated movement state of the moving body is generated, and the movement state data measured and generated by the movement state measuring unit provided inside the moving body is the estimation. When the difference between the movement state data corresponding to the measurement time of the movement state data and the estimated movement state data is within a predetermined range, the measurement is performed based on the movement trajectory data and the movement state data. Estimate the position and moving state of the moving body for each time,
The data correction method according to any one of claims 1 to 5. - 前記移動状態データと、前記推定移動状態データとの相違が、予め定められる範囲内でない場合、前記移動体が内部に備える道路交通情報取得部が取得する道路交通情報に基づいて前記移動軌跡データが正常であるか否かを判定し、正常でないと判定した場合、外部に異常を出力する移動軌跡データ正常判定ステップ
をさらに含む請求項6に記載のデータ補正方法。 When the difference between the movement state data and the estimated movement state data is not within a predetermined range, the movement trajectory data is generated based on the road traffic information acquired by the road traffic information acquisition unit provided inside the moving body. The data correction method according to claim 6, further comprising a movement locus data normality determination step of determining whether or not the data is normal, and if it is determined that the abnormality is not normal, an abnormality is output to the outside. - 移動体に搭載されたレーザレーダ装置が、測定時刻ごとにレーザ光を照射することにより測定対象物までの距離を計測して点群データを生成する際に前記点群データに対応付けて生成される収集データであって観測時刻ごとに得られる前記移動体の水平面上での位置を示す水平面位置データから推定される前記レーザレーダ装置の測定条件を示す収集データを補正するデータ補正装置であって、
前記観測時刻ごとに得られる前記水平面位置データよりも高精度の水平面位置データを取得するか、または、前記移動体の鉛直面上での位置を示す鉛直面位置データを取得し、取得した前記高精度の水平面位置データ、または、前記鉛直面位置データに基づいて、前記移動体の移動軌跡を示す移動軌跡データを生成する移動軌跡データ生成部と、
前記移動軌跡データを解析して、前記測定時刻ごとの前記移動体の位置及び移動状態を推定する移動軌跡解析部と、
前記測定時刻ごとの前記移動体の位置及び移動状態に基づいて、前記測定時刻ごとの前記レーザレーダ装置の測定条件を示す測定条件データを生成する測定条件生成部と、
前記測定条件データに基づいて、前記収集データを補正する補正処理部と、
を備えるデータ補正装置。 When the laser radar device mounted on the moving body measures the distance to the object to be measured by irradiating the laser beam at each measurement time and generates the point group data, it is generated in association with the point group data. It is a data correction device that corrects the collected data indicating the measurement conditions of the laser radar device estimated from the horizontal plane position data indicating the position of the moving object on the horizontal plane obtained at each observation time. ,
The horizontal plane position data with higher accuracy than the horizontal plane position data obtained at each observation time is acquired, or the vertical plane position data indicating the position of the moving object on the vertical plane is acquired and the acquired height is obtained. A movement locus data generation unit that generates movement locus data indicating the movement locus of the moving body based on accurate horizontal plane position data or the vertical plane position data.
A movement locus analysis unit that analyzes the movement locus data and estimates the position and movement state of the moving body at each measurement time.
A measurement condition generation unit that generates measurement condition data indicating measurement conditions of the laser radar device for each measurement time based on the position and movement state of the moving body at each measurement time.
A correction processing unit that corrects the collected data based on the measurement condition data,
A data correction device equipped with.
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
PCT/JP2020/029047 WO2022024259A1 (en) | 2020-07-29 | 2020-07-29 | Data correction method and data correction device |
JP2022539870A JP7339588B2 (en) | 2020-07-29 | 2020-07-29 | Data correction method and data correction device |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
PCT/JP2020/029047 WO2022024259A1 (en) | 2020-07-29 | 2020-07-29 | Data correction method and data correction device |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2022024259A1 true WO2022024259A1 (en) | 2022-02-03 |
Family
ID=80035508
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/JP2020/029047 WO2022024259A1 (en) | 2020-07-29 | 2020-07-29 | Data correction method and data correction device |
Country Status (2)
Country | Link |
---|---|
JP (1) | JP7339588B2 (en) |
WO (1) | WO2022024259A1 (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20220358635A1 (en) * | 2019-07-26 | 2022-11-10 | Nec Corporation | Inspection apparatus, measuring method, and computer readable medium |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2015096824A (en) * | 2013-11-15 | 2015-05-21 | アジア航測株式会社 | Measurement point height providing system, measurement point height providing method, and measurement point height providing program |
WO2016185637A1 (en) * | 2015-05-20 | 2016-11-24 | 三菱電機株式会社 | Point-cloud-image generation device and display system |
JP2017125820A (en) * | 2016-01-15 | 2017-07-20 | 三菱電機株式会社 | Information processing apparatus, information processing method, and information processing program |
JP2017223511A (en) * | 2016-06-14 | 2017-12-21 | 日本電信電話株式会社 | Road structuring device, road structuring method and road structuring program |
KR20190014237A (en) * | 2017-07-31 | 2019-02-12 | 현대엠엔소프트 주식회사 | Apparatus and method for acquiring of road line using mobile mapping system |
-
2020
- 2020-07-29 WO PCT/JP2020/029047 patent/WO2022024259A1/en active Application Filing
- 2020-07-29 JP JP2022539870A patent/JP7339588B2/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2015096824A (en) * | 2013-11-15 | 2015-05-21 | アジア航測株式会社 | Measurement point height providing system, measurement point height providing method, and measurement point height providing program |
WO2016185637A1 (en) * | 2015-05-20 | 2016-11-24 | 三菱電機株式会社 | Point-cloud-image generation device and display system |
JP2017125820A (en) * | 2016-01-15 | 2017-07-20 | 三菱電機株式会社 | Information processing apparatus, information processing method, and information processing program |
JP2017223511A (en) * | 2016-06-14 | 2017-12-21 | 日本電信電話株式会社 | Road structuring device, road structuring method and road structuring program |
KR20190014237A (en) * | 2017-07-31 | 2019-02-12 | 현대엠엔소프트 주식회사 | Apparatus and method for acquiring of road line using mobile mapping system |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20220358635A1 (en) * | 2019-07-26 | 2022-11-10 | Nec Corporation | Inspection apparatus, measuring method, and computer readable medium |
Also Published As
Publication number | Publication date |
---|---|
JPWO2022024259A1 (en) | 2022-02-03 |
JP7339588B2 (en) | 2023-09-06 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN109141446B (en) | Method, apparatus, device and computer-readable storage medium for obtaining map | |
JP6694395B2 (en) | Method and system for determining position relative to a digital map | |
JP2021068419A (en) | Method and apparatus for detecting obstacle | |
CN101772710A (en) | Method and device for determining a position | |
KR101921429B1 (en) | Method and system for making precise map | |
JP2005069700A (en) | Three-dimensional data acquisition device | |
JP2005070840A (en) | Three dimensional model preparing device, three dimensional model preparing method and three dimensional model preparing program | |
JP2009264983A (en) | Position locating device, position locating system, user interface device of the position locating system, locating server device of the position locating system, and position locating method | |
US11002553B2 (en) | Method and device for executing at least one measure for increasing the safety of a vehicle | |
CN114111775B (en) | Multi-sensor fusion positioning method and device, storage medium and electronic equipment | |
JP2023101820A (en) | Self-location estimation device, control method, program, and storage medium | |
WO2020071117A1 (en) | Information processing device | |
WO2022024259A1 (en) | Data correction method and data correction device | |
JP2021043151A (en) | Void ratio estimation device, void ratio estimation method and program | |
CN113920258A (en) | Map generation method, map generation device, map generation medium and electronic equipment | |
US10895627B2 (en) | Self-position estimation apparatus and self-position estimation method | |
KR101104379B1 (en) | System for forecasting location for vehicle in accordance with receiving interruption of gps signal and method for forecasting location using the same | |
CN1417557A (en) | Intelligent vehicle navigator | |
JP2005072654A (en) | Radio wave propagation simulation apparatus and radio wave propagation simulation method | |
JP2020056657A (en) | Information processing device | |
WO2021220417A1 (en) | Position measurement device, positioning method, and program | |
CN115077500A (en) | Determination method of ground sunlight reflection point and related components thereof | |
KR102018347B1 (en) | Apparatus and method for generating road profile data and program for displaying road profile data | |
JP4358123B2 (en) | Navigation system | |
JP2019132672A (en) | Three-dimensional model generation system |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 20947364 Country of ref document: EP Kind code of ref document: A1 |
|
ENP | Entry into the national phase |
Ref document number: 2022539870 Country of ref document: JP Kind code of ref document: A |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 20947364 Country of ref document: EP Kind code of ref document: A1 |