WO2021095269A1 - 情報生成装置、情報生成方法、及びコンピュータプログラム - Google Patents

情報生成装置、情報生成方法、及びコンピュータプログラム Download PDF

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Publication number
WO2021095269A1
WO2021095269A1 PCT/JP2019/044975 JP2019044975W WO2021095269A1 WO 2021095269 A1 WO2021095269 A1 WO 2021095269A1 JP 2019044975 W JP2019044975 W JP 2019044975W WO 2021095269 A1 WO2021095269 A1 WO 2021095269A1
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WIPO (PCT)
Prior art keywords
vehicle
information
accuracy
unit
length
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Ceased
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PCT/JP2019/044975
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English (en)
French (fr)
Japanese (ja)
Inventor
昇平 小河
享広 吉田
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Sumitomo Electric Industries Ltd
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Sumitomo Electric Industries Ltd
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Priority to CN201980101626.2A priority Critical patent/CN114631038B/zh
Priority to US17/770,229 priority patent/US20220398850A1/en
Priority to JP2021555777A priority patent/JP7380705B2/ja
Priority to PCT/JP2019/044975 priority patent/WO2021095269A1/ja
Publication of WO2021095269A1 publication Critical patent/WO2021095269A1/ja
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G06V20/54—Surveillance or monitoring of activities, e.g. for recognising suspicious objects of traffic, e.g. cars on the road, trains or boats
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    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
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    • 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
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
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    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
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    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
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    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/08—Detecting or categorising vehicles

Definitions

  • This disclosure relates to an information generator, an information generation method, and a computer program.
  • Patent Document 1 Conventionally, various systems for supporting the driving of a vehicle traveling on a road have been proposed (see Patent Document 1).
  • the vehicle is detected by a sensor such as a radar sensor or a camera, for example.
  • Patent Document 2 discloses a traveling vehicle grasping device that grasps a vehicle condition by a radar sensor.
  • the radar sensors of Patent Document 2 are installed at a plurality of locations on the road and irradiate a vehicle with a pulsed laser beam.
  • Patent Document 3 discloses a vehicle type discriminating device that discriminates a vehicle type from image data obtained by a camera that photographs a vehicle.
  • the vehicle type discriminating device of Patent Document 3 uses a grid pattern provided on the road to photograph a vehicle traveling on the pattern.
  • the vehicle type discriminating device calculates the vehicle length from the image data obtained by shooting, and discriminates the vehicle type from the calculated vehicle length.
  • the disclosed information generator includes a measurement unit for obtaining a plurality of measurement results by measuring the vehicle size of the same traveling vehicle a plurality of times, and a detection unit for detecting the accuracy of each of the plurality of measurement results. And a determination unit for determining the vehicle size of the traveling vehicle from the plurality of measurement results based on the accuracy.
  • the disclosed information generation method is to obtain a plurality of measurement results by measuring the vehicle size of the same traveling vehicle a plurality of times, to detect the accuracy of each of the plurality of measurement results, and based on the accuracy. , The vehicle size of the traveling vehicle is determined from the plurality of measurement results.
  • the disclosed computer program is for operating a computer as an information generator.
  • the information generator includes a measurement unit for obtaining a plurality of measurement results by measuring the vehicle size of the same traveling vehicle a plurality of times, and a detection unit for detecting the accuracy of each of the plurality of measurement results.
  • a determination unit for determining the vehicle size of the traveling vehicle from the plurality of measurement results based on the accuracy.
  • FIG. 1 is a diagram showing an overall configuration of a traffic information providing system according to the first embodiment.
  • FIG. 2 is a block diagram showing a configuration of a traffic flow measuring device according to the first embodiment.
  • FIG. 3 is a diagram showing the measurement results of each measurement point output from the sensor.
  • FIG. 4 is a diagram for explaining a method of determining the vehicle length by the vehicle length determining unit.
  • FIG. 5 is a diagram showing an example of information stored in the storage unit.
  • FIG. 6 is a flowchart showing an example of a processing procedure of the traffic flow measuring device according to the first embodiment.
  • FIG. 7 is a diagram showing an overall configuration of the traffic information providing system according to the second embodiment.
  • FIG. 8 is a block diagram showing a configuration of the driving support device according to the second embodiment.
  • FIG. 9 is a flowchart showing an example of the processing procedure of the driving support device according to the second embodiment.
  • FIG. 10 is an explanatory diagram of the inter-vehicle distance.
  • the measurement accuracy of vehicle size such as vehicle length may differ depending on the position in the area.
  • the grid pattern appears small at a point far from the camera, so that the measurement accuracy of the vehicle length deteriorates.
  • the measurement accuracy of the vehicle size may differ depending on the measured position.
  • the information generator detects the accuracy of each of the measurement unit for obtaining a plurality of measurement results and the accuracy of each of the plurality of measurement results by measuring the vehicle size of the same traveling vehicle a plurality of times.
  • a detection unit for determining the size of the traveling vehicle and a determination unit for determining the vehicle size of the traveling vehicle from the plurality of measurement results based on the accuracy are provided. According to this configuration, among a plurality of vehicle size measurement results for the same traveling vehicle, the one with good accuracy can be determined as the vehicle size. Therefore, even if the plurality of measurement results include those with poor accuracy, the vehicle size can be appropriately determined.
  • the determination unit is configured to determine the measurement result having the highest accuracy among the plurality of measurement results as the vehicle size. In this case, the most accurate measurement result is determined as the vehicle size.
  • the plurality of measurement results are preferably measurement results measured at each of the plurality of positions.
  • the plurality of measurement results are the measurement results measured at each of the plurality of positions.
  • the information generating device further includes a tracking unit for determining the vehicle detected at the plurality of positions as the same traveling vehicle.
  • the tracking unit can determine the vehicles detected at a plurality of positions as the same traveling vehicle.
  • the information generating device further includes a vehicle type determining unit for determining the vehicle type of the traveling vehicle based on the vehicle size determined by the determining unit.
  • the vehicle type can be accurately determined based on the accurate vehicle size.
  • the information generating device further includes a flow measuring unit for measuring a traffic flow for each vehicle type based on the vehicle type determined by the vehicle type determining unit.
  • the traffic flow for each vehicle type can be accurately measured based on the vehicle type determined accurately.
  • the traffic flow for each vehicle type preferably includes the number of vehicles for each vehicle type.
  • the number of vehicles for each vehicle type can be measured accurately.
  • the number of vehicles is measured as, for example, the number of vehicles at predetermined time intervals.
  • the information generating device further includes a providing unit for providing the first information based on the vehicle size determined by the determining unit.
  • the first information based on the determined vehicle size can be used for driving support of another vehicle.
  • the driving of the other vehicle may be a human driving or an automatic driving.
  • the first information is preferably further based on the position of the traveling vehicle. In this case, it is possible to provide the first information based on the determined vehicle size and the position of the traveling vehicle. This makes driving assistance for other vehicles more appropriate.
  • the information providing unit is configured to further provide second information indicating the measurement time of the position.
  • the other vehicle can also use the measurement time of the position of the traveling vehicle.
  • the first information includes inter-vehicle distance data between the first traveling vehicle and the second traveling vehicle traveling behind the first traveling vehicle, and the determined vehicle size indicates at least the vehicle length, and the inter-vehicle distance data. Is obtained by using at least the vehicle length indicated by the vehicle size of the first traveling vehicle.
  • the inter-vehicle data preferably includes at least one of the inter-vehicle distance and the inter-vehicle time length.
  • the inter-vehicle distance or inter-vehicle time length between the first traveling vehicle and the second traveling vehicle is useful for driving support of another vehicle trying to enter between the first traveling vehicle and the second traveling vehicle.
  • the first information is provided to the first traveling vehicle and the vehicle trying to enter the lane in which the second traveling vehicle is traveling.
  • a vehicle trying to enter the lane in which the first traveling vehicle and the second traveling vehicle travel can enter the lane in which the first traveling vehicle and the second traveling vehicle travel by using the first information including the inter-vehicle data. Can be done smoothly.
  • the vehicle size preferably indicates at least the vehicle length. It is preferable that the information generating device further includes a providing unit for providing first information based on the vehicle length indicated by the vehicle size and the position of the traveling vehicle. It is preferable that the first information is provided to another vehicle.
  • the other vehicle is, for example, a vehicle that attempts to enter the lane in which the traveling vehicle travels.
  • the measurement result is preferably obtained based on the image data obtained by photographing the road.
  • the accuracy is preferably detected based on the number of pixels included in the image of the traveling vehicle in the image data. Vehicles that appear larger in the image data often have higher accuracy in measurement results. Therefore, the accuracy can be detected by using the number of pixels included in the image of the traveling vehicle.
  • the measurement vehicle length is preferably determined based on a cluster of measurement points obtained from the reflected wave of the transmitted wave irradiated on the road by the radar sensor.
  • the accuracy is preferably detected based on the number of measurement points included in the cluster. The larger the number of measurement points, the higher the measurement accuracy of the measurement vehicle size. Therefore, the accuracy can be detected by using the number of measurement points.
  • the measured vehicle size is preferably determined based on the reflected wave of the transmitted wave irradiated on the road by the radar sensor.
  • the accuracy is preferably detected based on the position of the traveling vehicle on which the vehicle size has been measured. For example, by investigating the relationship between the measurement error of the vehicle size and the position of the vehicle in advance, the accuracy of the vehicle size can be detected from the position of the vehicle based on the investigation result.
  • the information generation method is to obtain a plurality of measurement results by measuring the vehicle length of the same traveling vehicle a plurality of times, and to detect the measurement accuracy of each of the plurality of measurement results. Further, the vehicle length of the traveling vehicle is determined from the plurality of measurement results based on the accuracy.
  • the computer program according to the embodiment operates the computer as an information generator.
  • the information generator includes a measurement unit for obtaining a plurality of measurement results by measuring the vehicle size of the same traveling vehicle a plurality of times, and a detection unit for detecting the accuracy of each of the plurality of measurement results.
  • a determination unit for determining the vehicle size of the traveling vehicle from the plurality of measurement results based on the accuracy.
  • the above-mentioned computer program can be distributed via a computer-readable non-temporary recording medium such as a CD-ROM (Compact Disc-Read Only Memory) or a communication network such as the Internet. ..
  • the information generator may be partially or wholly realized by a semiconductor integrated circuit. The information generator may be used in a system including the information generator.
  • FIG. 1 is a diagram showing an overall configuration of a traffic information providing system according to the first embodiment.
  • the traffic information providing system 1 is a system that measures the traffic flow of the vehicle 60 traveling on the road 100.
  • the traffic information providing system 1 includes a sensor 2 and a traffic flow measuring device 3 as an information generating device.
  • the sensor 2 is, for example, a radar sensor.
  • the radar sensor transmits radio waves (transmitted waves) to the area 70 on the road 100 and receives the reflected waves of the transmitted waves.
  • the area 70 has a length of several hundred meters, for example, in the traveling direction of the vehicle 60.
  • the sensor 2 obtains a plurality of measurement points corresponding to the objects in the area 70 based on the received reflected wave.
  • the measurement point is, for example, a point where the level of the reflected wave is higher than the threshold value for detection.
  • the sensor 2 receives reflected waves from a plurality of measurement points of an object in the area 70, and based on the received reflected waves, the distance from the sensor 2 to each measurement point and each measurement point based on the sensor 2. Measure the direction (horizontal angle) and the speed of each measurement point. A plurality of measurement points are clustered as described later for vehicle detection.
  • the senor 2 includes a transmitting antenna and a plurality of receiving antennas having different installation positions.
  • the sensor 2 measures the position, direction, and speed of each measurement point from the reflected wave using a frequency-modulated continuous wave (FM-CW) method.
  • FM-CW frequency-modulated continuous wave
  • the sensor 2 outputs a measurement result including the position, direction, and speed of the measurement point to the traffic flow measuring device 3 as an information generating device.
  • the radio wave is, for example, a millimeter wave in the 24 GHz band, 79 GHz band, or 76 GHz band.
  • the transmitted wave may be an ultrasonic wave having a frequency of 20 kHz or higher instead of the radio wave.
  • the sensor 2 is installed at a position where a vehicle 60 traveling upstream of the sensor 2 can be measured from the front of the vehicle 60, for example.
  • the installation position of the sensor 2 is not limited to this.
  • the sensor 2 may be installed at a position where the vehicle 60 traveling downstream of the sensor 2 can be measured from the rear of the vehicle 60.
  • the sensor 2 may be installed at a position where the vehicle 60 can be measured from above or from the side of the vehicle 60.
  • the traffic flow measuring device 3 receives the measurement result from the sensor 2 and measures the traffic flow of the vehicle 60 traveling on the road 100.
  • the traffic flow includes, for example, the number of vehicles per unit time and at least one of the average speeds. Traffic flow is measured for each vehicle type. That is, the number of vehicles is measured for each vehicle type, and the average speed is also measured for each vehicle type.
  • the traffic flow measuring device 3 transmits the traffic information indicating the measured traffic flow to the central device 10.
  • the traffic flow measuring device 3 transmits traffic information to the central device 10 by using a communication network such as a mobile phone network, a dedicated wireless line, or a wired line.
  • the central device 10 is, for example, a server installed in a traffic control center or the like.
  • FIG. 2 is a block diagram showing the configuration of the traffic flow measuring device 3 according to the first embodiment.
  • the traffic flow measuring device 3 includes a vehicle position measuring unit 31, a speed measuring unit 32, a vehicle length measuring unit 33, an accuracy detecting unit 34, a vehicle tracking unit 35, a vehicle length determining unit 36, and a vehicle type determining unit 37.
  • a traffic flow measuring unit 38, a traffic information providing unit 39, and a storage unit 40 are provided.
  • the traffic flow measuring device 3 can also be configured by a computer equipped with a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), a communication I / F (interface), and the like.
  • a CPU Central Processing Unit
  • ROM Read Only Memory
  • RAM Random Access Memory
  • communication I / F interface
  • Each of the processing units 31 to 39 is functionally realized by executing a computer program on the CPU.
  • the vehicle position measuring unit 31 measures the position of the vehicle 60. More specifically, the vehicle position measuring unit 31 measures the position of the vehicle 60 based on the measurement results of each measurement point output from the sensor 2.
  • FIG. 3 is a diagram showing the measurement results of each measurement point output from the sensor 2.
  • the measurement result of each measurement point is represented as a point (black point in FIG. 3) in a three-dimensional space consisting of a distance, a direction and a velocity.
  • the vehicle position measuring unit 31 clusters the points in the space (black points in FIG. 3). For example, the vehicle position measuring unit 31 clusters points whose speed is within x (km / h) and whose direction is within y (°) into one cluster. Here, the measurement points are classified into two clusters, cluster CA and CB. One cluster represents one vehicle 60. Therefore, the vehicle position measuring unit 31 specifies the point where the distance is the smallest for each cluster as the point at the tip position of the vehicle 60 corresponding to the cluster. The vehicle position measuring unit 31 measures the tip position of the vehicle 60 as the position of the vehicle 60 by calculating the tip position based on the distance and the direction corresponding to the point of the tip position. The position can be indicated, for example, in two-dimensional coordinates.
  • the vehicle position measuring unit 31 may measure the rear end position of the vehicle 60 as the position of the vehicle 60. Further, when the sensor 2 measures the vehicle 60 from above or from the side, the vehicle position measuring unit 31 measures a preset position among the front end position and the rear end position of the vehicle 60 as the position of the vehicle 60. You may.
  • the vehicle position measuring unit 31 stores the measured position information of the vehicle 60 in the storage unit 40 for each vehicle 60 in association with the information of the measurement time of the position.
  • the speed measuring unit 32 measures the speed of the vehicle 60 based on the measurement results of each measurement point output from the sensor 2.
  • the speed measuring unit 32 measures the speed of the vehicle 60 corresponding to the cluster from the speed corresponding to the measurement point included in each cluster. For example, the speed measuring unit 32 may measure the average value or the median speed of each measurement point included in the cluster as the speed of the vehicle 60 corresponding to the cluster. The speed measuring unit 32 stores the measured speed information of the vehicle 60 in the storage unit 40.
  • the vehicle length measuring unit (vehicle size measuring unit) 33 measures the vehicle length of the vehicle 60. More specifically, the vehicle length measuring unit 33 measures the vehicle length of the vehicle 60 based on the measurement results of each measurement point output from the sensor 2. For example, the vehicle length measuring unit 33 measures the difference between the maximum value and the minimum value of the distances of the measurement points included in the cluster for each cluster as the vehicle length of the vehicle 60 corresponding to the cluster. In the example shown in FIG. 3, the vehicle length of the vehicle 60 corresponding to the cluster CA is measured as LA, and the vehicle length of the vehicle 60 corresponding to the cluster CB is measured as LB.
  • the vehicle size measuring unit 33 can also measure the vehicle width based on the cluster CA and CB. Further, depending on the installation position of the sensor 2, the cluster CA and CB indicate the vehicle height, so that the vehicle size measuring unit 33 can measure the vehicle height based on the cluster CA and CB.
  • the vehicle length measuring unit 33 stores information on the measured vehicle size such as the vehicle length (measured vehicle length) of the measured vehicle 60 in the storage unit 40.
  • the measured vehicle size (measured vehicle length, etc.) stored here is the vehicle size as a provisional value.
  • the accuracy detection unit 34 detects the measurement accuracy of the measurement result (measurement vehicle length) of the vehicle length measured by the vehicle length measurement unit 33. More specifically, the accuracy detection unit 34 determines the accuracy of the measurement result of the vehicle length of the vehicle 60 based on the measurement result of each measurement point output from the sensor 2.
  • the accuracy detection unit 34 obtains the accuracy of the measurement result of the vehicle length of the vehicle 60 based on the number of measurement points included in the cluster of each vehicle 60.
  • the accuracy detection unit 34 may use the number of measurement points included in the cluster of each vehicle 60 as the accuracy of the measurement result of the vehicle length of the vehicle 60, or may use the index obtained from the number of measurement points as the accuracy. ..
  • the accuracy detection unit 34 stores the accuracy information (measurement accuracy; vehicle length accuracy) of the measurement result of the vehicle length of the vehicle 60 in the storage unit 40.
  • the storage unit 40 stores information on the position of the vehicle 60, the measurement time and speed of the position, the vehicle length, and the accuracy of the measurement result of the vehicle length for each vehicle 60.
  • the traffic flow measuring device 3 detects a vehicle 60 whose position changes as it travels in the area 70 at each of a plurality of positions in the area 70. That is, the vehicle position measuring unit 31 measures the vehicle position of the same vehicle at each of the plurality of positions in the area 70. Further, the speed measuring unit 32 measures the speed of the same vehicle at each of the plurality of positions in the area 70, and the vehicle length measuring unit 33 measures the speed of the same vehicle at each of the plurality of positions in the area 70. ..
  • the measurement time, speed, vehicle length, and accuracy information of the measurement result of the vehicle length of the vehicle 60 are measured or detected at each of the plurality of positions in the area 70, and are stored in the storage unit 40 for each of the plurality of positions. Will be done.
  • the vehicle tracking unit 35 tracks the vehicle 60.
  • the vehicle tracking unit 35 operates so as to determine the traveling vehicles 60 detected at a plurality of positions in the area 70 as the same vehicle. More specifically, the vehicle tracking unit 35 tracks the vehicle 60 by associating the information of the vehicles 60 having different measurement times with each other based on the information stored in the storage unit 40 for each vehicle 60. For example, the vehicle tracking unit 35 uses a Kalman filter to estimate the position of the first vehicle at the second measurement time from information such as the position and speed of the first vehicle at the first measurement time. The vehicle tracking unit 35 tracks the first vehicle by determining that the second vehicle having the measurement position at the second measurement time closest to the estimated position of the first vehicle is the same vehicle as the first vehicle. Do.
  • the vehicle tracking unit 35 assigns the same vehicle ID (identifier) to the first vehicle and the second vehicle determined to be the same vehicle, and stores them in the storage unit 40.
  • the vehicle length determination unit 36 obtains the determined vehicle size (determined vehicle length) as a definite value from the measured vehicle length (measured vehicle size) which is a provisional value.
  • the vehicle length determination unit 36 compares the accuracy of the vehicle length measurement result of the same traveling vehicle based on the vehicle tracking result by the vehicle tracking unit 35 and the accuracy determination result of the vehicle length measurement result by the accuracy detection unit 34. To do.
  • the vehicle length determination unit 36 determines the vehicle length of the vehicle based on the accuracy comparison result. In the embodiment, the vehicle length determination unit 36 determines the vehicle length determined to have the highest accuracy among the vehicle lengths of the same vehicle as the vehicle length (determined vehicle length) of the vehicle.
  • FIG. 4 is a diagram for explaining a method of determining the vehicle length by the vehicle length determination unit.
  • vehicle length accuracy the accuracy of each measurement result of the measured vehicle length
  • the set of the measured vehicle length and the vehicle length accuracy of the vehicle 60 at the position P1 is (L1,30), and the above sets at the positions P2 to P6 are (L2, 42), (L3, 49), (L3, 49), respectively. It is assumed that the numbers are L4,56), (L5,40), and (L6,30).
  • the vehicle length accuracy of the vehicle 60 increases as the vehicle advances from the position P1 and becomes the highest accuracy at the position P4, but then the vehicle length accuracy decreases. This is because the number of measurement points of the vehicle 60 decreases at a position far from the sensor 2, and the vehicle length accuracy decreases.
  • the vehicle 60 is too close to the sensor 2, it is affected by noise and is included in one cluster. This is because the number of measurement points to be measured is reduced.
  • the vehicle length determination unit 36 determines the vehicle length of the vehicle 60 in the order of positions P1, P2, P3, P4, P5, P6. At each position, the vehicle length determining unit 36 determines the measured vehicle length having the highest vehicle length accuracy among the measured vehicle lengths of the vehicle 60 measured so far, and the vehicle length of the vehicle 60 at that position (determined vehicle length). To determine as.
  • the vehicle length determining unit 36 measures only the measured vehicle length L1 at the position P1, and the measured vehicle length L1 has the highest accuracy. Therefore, the measured vehicle length L1 is set as the determined vehicle length. Further, the vehicle length determination unit 36 determines the measurement vehicle length L2 because the vehicle length accuracy “42” of the measurement vehicle length L2 is the highest accuracy among the vehicle length accuracy of the measurement vehicle lengths L1 and L2 at the position P2. Make it long. Similarly, the vehicle length determining unit 36 sets the measured vehicle lengths L3 and L4 as the determined vehicle lengths at the positions P3 and P4, respectively.
  • the vehicle length determination unit 36 determines the measurement vehicle length L4 because the vehicle length accuracy “56” of the measurement vehicle length L4 is the highest accuracy among the vehicle length accuracy of the measurement vehicle lengths L1 to L5 at the position P5. Make it long. Further, the vehicle length determination unit 36 determines the measurement vehicle length L4 because the vehicle length accuracy "56" of the measurement vehicle length L4 is the highest accuracy among the vehicle length accuracy of the measurement vehicle lengths L1 to L6 at the position P6. Make it long.
  • the determined vehicle length is sequentially updated up to the position P4 where the vehicle length accuracy continues to increase, but after the position P4, the vehicle length accuracy continues to decrease and is not updated.
  • the vehicle length determination unit 36 may determine the vehicle lengths of positions P1 to P6 after the vehicle 60 has passed through the area 70. In this case, the vehicle length determination unit 36 determines the vehicle lengths of positions P1 to P6 because the vehicle length accuracy "56" of the measurement vehicle length L4 is the highest accuracy among the vehicle length accuracy of the measurement vehicle lengths L1 to L6. All may be determined to be L4. The vehicle length determination unit 36 stores the determined vehicle length in the storage unit 40.
  • the vehicle type determination unit 37 determines the vehicle type of the vehicle 60 based on the vehicle length determined by the vehicle length determination unit 36. For example, the vehicle type determination unit 37 determines that the vehicle type of the vehicle 60 is a large vehicle when the determined vehicle length is 5.5 m or more, and the vehicle type of the vehicle 60 is a small vehicle when the determined vehicle length is less than 5.5 m. decide.
  • the vehicle length may differ depending on the position of the same vehicle 60.
  • the vehicle type determination unit 37 may determine the vehicle type based on the most accurate vehicle length. That is, in the example shown in FIG. 4, the vehicle type determination unit 37 determines the vehicle type based on the determination vehicle length L4 of the position P4 having the highest vehicle length accuracy.
  • the vehicle type determination unit 37 may determine the vehicle type by performing threshold processing on the vehicle width or vehicle height.
  • the vehicle type determination unit 37 stores the determined vehicle type in the storage unit 40.
  • the storage unit 40 is composed of a storage device such as an HDD (Hard Disk Drive) or a flash memory, and stores the above-mentioned various information.
  • a storage device such as an HDD (Hard Disk Drive) or a flash memory
  • FIG. 5 is a diagram showing an example of information stored in the storage unit 40.
  • the storage unit 40 stores the vehicle ID, position, measurement time, measurement vehicle length, vehicle length accuracy, determined vehicle length, and vehicle type of the vehicle 60 as a set.
  • the information of the vehicle ID "C1" is the information of the same vehicle tracked by the vehicle tracking unit 35.
  • the traffic flow measurement unit 38 measures the traffic flow of the vehicle 60 for each vehicle type based on the tracking result by the vehicle tracking unit 35. As an example, the traffic flow measuring unit 38 measures the number of large vehicles and the number of small vehicles that have passed through the area 70 in a certain time as traffic flow, respectively, with reference to the information stored in the storage unit 40. .. The traffic flow measuring unit 38 measures the number of vehicles 60 by regarding the information with the same vehicle ID as the information of the same vehicle 60, which is determined by the vehicle tracking unit 35 to be the same vehicle.
  • the traffic flow is not limited to the number of vehicles 60, and may be, for example, the average speed of the vehicles 60. The average speed can also be measured for each vehicle type.
  • the traffic information providing unit 39 provides traffic information by transmitting the traffic flow information of the vehicle 60 for each vehicle type measured by the traffic flow measuring unit 38 to the central device 10 as traffic information.
  • FIG. 6 is a flowchart showing an example of a processing procedure of the traffic flow measuring device according to the first embodiment of the present disclosure.
  • the vehicle position measuring unit 31 measures the position of the vehicle 60 based on the measurement results of each measurement point output from the sensor 2, and the measurement results are combined with the vehicle ID of the vehicle 60. It is stored in the storage unit 40 (S1). The vehicle position measuring unit 31 generates a value that has not been assigned as a vehicle ID so far, for example, randomly or sequentially and assigns it as a vehicle ID.
  • the speed measuring unit 32 measures the speed of the vehicle 60 based on the measurement results of each measurement point output from the sensor 2, and stores the measurement results in the storage unit 40 (S2).
  • the measurement result is associated with the vehicle ID generated in step S1.
  • the vehicle length measuring unit 33 measures the vehicle length of the vehicle 60 based on the measurement results of each measurement point output from the sensor 2, and stores the measured vehicle length in the storage unit 40 (S3).
  • the measured vehicle length is associated with the vehicle ID generated in step S1.
  • the accuracy detection unit 34 determines the accuracy of the measurement result of the vehicle length of the vehicle 60 based on the measurement result of each measurement point output from the sensor 2, and stores the determined vehicle length accuracy in the storage unit 40 (S4). ).
  • the vehicle length accuracy is associated with the vehicle ID generated in step S1.
  • the vehicle tracking unit 35 tracks the vehicle 60 by associating the information of the vehicles 60 having different measurement times with each other based on the information stored in the storage unit 40 for each vehicle 60 (S5).
  • the vehicle tracking unit 35 updates the vehicle ID so that the vehicle IDs of the associated information have the same value.
  • the vehicle length determination unit 36 determines whether or not the vehicle length measured in step S3 is the highest accuracy among the vehicle lengths having the same vehicle ID. Is determined (S6).
  • the vehicle length determining unit 36 replaces the measured vehicle length with the most accurate vehicle length, thereby changing the replaced vehicle length to the vehicle of the vehicle 60. Determined as the length (S7).
  • the vehicle length determination unit 36 stores the determined vehicle length in the storage unit 40 (S8).
  • the determined vehicle length is associated with the vehicle ID.
  • the vehicle length determining unit 36 determines the measured vehicle length as the vehicle length of the vehicle 60 and stores it in the storage unit 40 in association with the vehicle ID. (S8).
  • the measured vehicle length of the vehicle 60 is determined to be the vehicle length of the vehicle 60, and is stored in the storage unit 40 in association with the vehicle ID. ..
  • the vehicle type determination unit 37 determines whether or not a certain time (for example, 1 minute) has elapsed since the process of step S1 was started, based on the output of the timer or the like (S9).
  • step S1 If a certain time has not passed (NO in S9), the processes after step S1 are repeatedly executed. By repeating the process after step S1, the vehicle position, the vehicle speed, and the vehicle length are measured a plurality of times for the same traveling vehicle. The measurement accuracy of the vehicle length is detected for each of the plurality of measured vehicle lengths.
  • the vehicle type determination unit 37 determines the vehicle type from the determined vehicle length for each information based on the information stored in the storage unit 40, and determines the determined vehicle type. It is stored in the storage unit 40 in association with the vehicle ID (S10). By the processing up to this point, the information shown in FIG. 5 is stored in the storage unit 40.
  • the traffic flow measuring unit 38 measures the number of large vehicles and the number of small vehicles that have passed through the area 70 in a fixed time as traffic flows, respectively, with reference to the information stored in the storage unit 40 (S11). ..
  • the traffic information providing unit 39 provides traffic information by transmitting the traffic flow information of the vehicle 60 for each vehicle type measured by the traffic flow measuring unit 38 to the central device 10 as traffic information (S12).
  • the traffic flow measuring device 3 determines whether or not a predetermined end condition is satisfied (S13). For example, when the traffic flow measuring device 3 receives a stop instruction signal for processing of the traffic flow measuring device 3 from the outside, it may be determined that the end condition is satisfied.
  • step S13 If the end condition is satisfied (YES in S13), the traffic flow measuring device 3 ends the process. If the end condition is not satisfied (NO in S13), the processes after step S1 are repeatedly executed.
  • the vehicle 60 is tracked, and for the same traveling vehicle 60, the accuracy of the measurement result of the vehicle length measured at a certain position at a certain time and the accuracy of the measurement result of the other at another time.
  • the vehicle length of the vehicle 60 can be determined based on the comparison result with the accuracy of the measurement result of the vehicle length measured at the position. Thereby, it is possible to adopt the vehicle length with higher accuracy and determine the vehicle length of the vehicle 60.
  • the area 70 where the vehicle 60 is detected can be widened, and even if there is a place in the area 70 where the measurement accuracy of the vehicle size is low, it is possible to avoid using the vehicle size having a low measurement accuracy. .. Therefore, the area 70 can be widened, and the number of sensors installed can be suppressed. Therefore, the vehicle length of the vehicle 60 can be determined with high accuracy at a low installation cost.
  • the vehicle 60 having more measurement points of the reflected wave with respect to the irradiated radio wave has higher accuracy of the measurement result of the vehicle length. Thereby, the accuracy of the measurement result of the vehicle length can be accurately determined.
  • the vehicle type based on the highly accurate vehicle length and measure the traffic flow for each vehicle type.
  • the number of vehicles 60 of each vehicle type can be measured at predetermined time intervals. Therefore, it is possible to measure the traffic flow for each vehicle type with high accuracy.
  • a radar sensor is used as an example of the sensor 2, but the sensor 2 is not limited to the radar sensor.
  • another device can be used as long as the area 70 can be observed substantially at the same time.
  • a camera can be used as the sensor 2, or LiDAR (Light Detection and Ringing) can be used.
  • the vehicle position measuring unit 31 of the traffic flow measuring device 3 identifies the position of the vehicle 60 by performing image processing on the image data obtained by the camera photographing the area 70.
  • the vehicle position measuring unit 31 identifies the position of the vehicle 60 by using the background subtraction method or the like. That is, the vehicle position measuring unit 31 binarizes the difference data between the background image data obtained by photographing the area 70 when the vehicle 60 is not included and the image data output from the camera. Create binarized image data by.
  • the vehicle position measurement unit 31 extracts an image of the vehicle 60 from the binarized image data and estimates the position for each vehicle 60.
  • the uppermost position is specified for each image of the vehicle 60, and the position in the three-dimensional space (real space) corresponding to the position is specified as the position of the vehicle 60. It is assumed that the relationship between the position in the image data and the position in the three-dimensional space is known by prior calibration or the like.
  • the vehicle length measuring unit 33 measures the vehicle length of the vehicle 60 from the length of the image based on the image of the vehicle 60 in the binarized image data. It is assumed that the relationship between the length of the image at each position in the image data and the length of the vehicle is known by prior calibration or the like.
  • the accuracy detection unit 34 determines the accuracy of the measurement result of the vehicle length measured by the vehicle length measurement unit 33 based on the image of the vehicle 60 in the binarized image data. For example, the accuracy detection unit 34 may determine that the larger the number of pixels included in the image of the vehicle 60, the higher the accuracy of the measurement result of the vehicle length. That is, the accuracy detection unit 34 may determine the accuracy from the number of pixels based on the table information showing the relationship between the number of pixels and the accuracy.
  • the vehicle tracking unit 35 recognizes the license plate from the image data output from the camera, and associates the vehicles 60 having the same number between the frames, so that the vehicle 60 May be tracked.
  • the accuracy detection unit 34 of the traffic flow measurement device 3 of the first embodiment described above detects the accuracy of the measurement result of the vehicle length based on the number of measurement points included in the cluster, but the accuracy detection method is limited to this. It is not something that is done.
  • the error between the vehicle length measured by the vehicle length measuring unit 33 at that position and the correct vehicle length is obtained, and the smaller the error, the smaller the error.
  • Information on the relationship between the position of the vehicle 60 and the accuracy of the measurement result of the vehicle length is obtained so that the accuracy of the measurement result of the vehicle length is high.
  • the accuracy detection unit 34 refers to the relevant information and detects the accuracy of the measurement result of the vehicle length of the vehicle 60 existing at the position based on the position of the vehicle 60 measured by the vehicle position measurement unit 31. ..
  • Relationship information may be obtained based on the error.
  • the vehicle length is measured from the position of the vehicle 60 based on the relationship information which is the investigation result.
  • the accuracy of the result can be detected.
  • the accuracy of the measurement result of the vehicle length can be accurately detected.
  • FIG. 7 is a diagram showing the overall configuration of the traffic information providing system according to the second embodiment.
  • the traffic information providing system 1A is a system that supports the driving of a vehicle, and includes a sensor 2 and a driving support device 5 as an information generation device.
  • the driving support device 5 of the embodiment provides driving support to the vehicle 60 trying to enter the lane 101 from outside the lane 101.
  • a lane change from the second lane 102 included in the road 100 to the first lane 101 included in the road 100 will be described as an example.
  • the approach to the lane 101 may be to enter the road 100 from a position outside the road 100 such as a parking lot.
  • the sensor 2 is a radar sensor similar to that of the first embodiment.
  • the vehicle 60, 60A, 60B traveling in the area 70 upstream of the sensor 2 is the vehicle 60, 60A. It is installed at a position where it can be measured from the front of the 60B.
  • the area 70 in which the vehicles 60, 60A, and 60B are detected by the sensor 2 includes the first lane 101 and the second lane 102 of the road 100.
  • the sensor 2 may be installed at a position where the vehicles 60, 60A, 60B traveling in the area 70 can be measured from the rear of the vehicles 60, 60A, 60B. Further, the sensor 2 may be installed at a position where the vehicles 60, 60A, 60B can be measured from above or from the side of the vehicles 60, 60A, 60B.
  • driving support for the vehicle 60 when the vehicle 60 traveling in the second lane 102 changes lanes to the first lane 101 in which the first traveling vehicle 60A and the second traveling vehicle 60B travel will be described.
  • Information on the vehicles 60A and 60B traveling in the first lane is provided to the vehicle 60 to support the lane change to the vehicle 60.
  • the driving assistance described below is also used when the vehicles 60A and 60B traveling in the first lane 101 change lanes to the second lane 102.
  • the driving support device 5 receives the measurement result from the sensor 2 and provides the first information based on the positions and vehicle lengths of the vehicles 60A and 60B traveling in the first lane 101.
  • the driving support device 5 may provide the vehicle 60 traveling in the second lane 102 with information on the positions and vehicle lengths of the vehicles 60A and 60B traveling in the first lane 101 as vehicle information (first information).
  • vehicle information first information
  • the driving support device 5 provides vehicle information (first information) such as the inter-vehicle distance between the vehicles 60 and 60B and the inter-vehicle time length between the vehicles 60A and 60B based on the positions and lengths of the vehicles 60A and 60B. ), And this vehicle information may be provided to the vehicle 60.
  • the vehicles 60A and 60B traveling in the first lane 101 and the vehicles 60 traveling in the second lane 102 are distinguished by the position (direction) of the vehicle measured by the sensor 2.
  • FIG. 8 is a block diagram showing a configuration of the driving support device 5 according to the second embodiment.
  • the driving support device 5 includes a vehicle position measuring unit 31, a speed measuring unit 32, a vehicle length measuring unit 33, an accuracy detecting unit 34, a vehicle tracking unit 35, a vehicle length determining unit 36, and a vehicle information providing unit 51. And a storage unit 40.
  • the driving support device 5 can also be configured by a computer including a CPU, ROM, RAM, communication I / F, and the like.
  • a computer including a CPU, ROM, RAM, communication I / F, and the like.
  • Each of the processing units 31 to 36 and 51 is functionally realized by executing a computer program on the CPU.
  • Each processing unit 31 to 36 is the same as that shown in the first embodiment. Therefore, the detailed description will not be repeated here.
  • the vehicle information providing unit 51 provides vehicle information (first information) based on the positions of the vehicles 60A and 60B measured by the vehicle position measuring unit 31 and the vehicle lengths of the vehicles 60A and 60B determined by the vehicle length determining unit 36. To generate.
  • the vehicle information (first information) is information for supporting the lane change to the first lane 101 for the vehicle 60 traveling in the second lane 102.
  • the vehicle information providing unit 51 wirelessly transmits the generated vehicle information (first information) to the vehicle 60.
  • the vehicle information may be received by the vehicles 60A and 60B.
  • the vehicle information (first information) includes at least information based on the determined vehicle size (determined vehicle length).
  • the information based on the determined vehicle size (determined vehicle length) may be the determined vehicle size (determined vehicle length) itself, or may be information obtained from the determined vehicle size (determined vehicle length).
  • the vehicle information (first information) preferably includes information based on the position of the vehicle.
  • the information based on the position of the vehicle may be the position of the vehicle itself or the information obtained from the position of the vehicle.
  • the vehicle information providing unit 51 may generate information on the positions and vehicle lengths (determined vehicle lengths) of the vehicles 60A and 60B traveling in the first lane 101 as vehicle information (first information).
  • the vehicle information providing unit 51 may generate inter-vehicle data including information on the inter-vehicle distance and inter-vehicle time of the vehicle 61 as vehicle information (first information). Specifically, the vehicle information providing unit 51 sets the front end positions P1 and P2 and the rear end positions P11 and P12 for each of the vehicles 60A and 60B based on the positions of the vehicles 60A and 60B and the vehicle lengths of the respective vehicles 60A and 60B. Identify (see FIG. 10). For example, the vehicle information providing unit 51 identifies the rear end position P12 of the vehicle 61 by adding the vehicle length (determined vehicle length) to the tip position P1 of the vehicle 60A measured by the vehicle position measuring unit 31.
  • the vehicle information providing unit 51 is a distance between the rear end position P11 of the front vehicle 60A and the tip position P2 of the rear vehicle 60B for each group of vehicles 60A and 60B adjacent to each other in the front-rear direction traveling in the first lane 101. Calculate the distance (inter-vehicle data).
  • the vehicle information providing unit 51 may calculate the time required for the rear vehicle 60B to travel the inter-vehicle distance as the inter-vehicle time length (inter-vehicle data) from the inter-vehicle distance and the speed of the rear vehicle 60B.
  • the inter-vehicle distance data is useful when a vehicle 60 other than the vehicles 60A and 60B intends to travel between the vehicle 60A and the vehicle 60B.
  • the vehicle 60 traveling between the vehicle 60A and the vehicle 60B occurs, for example, when the vehicle 60 changes lanes. Further, the vehicle 60 trying to travel between the vehicle 60A and the vehicle 60B also occurs when the vehicle 60 turns across the oncoming lane at an intersection. For example, in a country where a vehicle is in the left lane, such as Japan, crossing the oncoming lane at an intersection occurs when turning right. In such cases, inter-vehicle data is useful.
  • the vehicle information providing unit 51 transmits the created vehicle information (first information) to the vehicle 60.
  • the vehicle 60 traveling in the second lane 102 can determine the lane change position or the lane change timing to the first lane 101, and can smoothly change lanes.
  • the vehicle information providing unit 51 transmits the measurement time information (second information) such as the positions of the vehicles 60A and 60B in association with the vehicle information (first information). May be good.
  • the vehicle information may be provided by the vehicle information providing unit 51.
  • the vehicle 60 traveling in the second lane 102 can accurately determine the lane change position to the first lane 101, the lane change timing, and the like.
  • the vehicle information (first information) provided to the vehicle 60 includes the positions of the vehicles 60A and 60B and the determined vehicle length of each vehicle 60A and 60B, but does not include the inter-vehicle distance data, the vehicle that has received the vehicle information. 60 may generate inter-vehicle distance data from the positions of the vehicles 60A and 60B and the determined vehicle length of each vehicle 60A and 60B.
  • the storage unit 40 stores the same information as shown in FIG. However, vehicle model information is not stored.
  • FIG. 9 is a flowchart showing an example of the processing procedure of the driving support device 5 according to the second embodiment.
  • the driving support device 5 executes the processes of steps S1 to S8. These processes are the same as those described with reference to FIG. Therefore, the detailed description will not be repeated here.
  • the vehicle information providing unit 51 makes the vehicle 60 traveling in the second lane 102 based on the position of the vehicle 61 measured by the vehicle position measuring unit 31 and the determined vehicle length of the vehicle 61 determined by the vehicle length determining unit 36. On the other hand, vehicle information for supporting the lane change to the first lane 101 is created (S21).
  • the vehicle information providing unit 51 wirelessly transmits the created vehicle information to the vehicle 60 to provide the vehicle information (S22).
  • the driving support device 5 determines whether or not the same termination conditions as those described in the first embodiment are satisfied (S13).
  • step S13 If the end condition is satisfied (YES in S13), the driving support device 5 ends the process. If the end condition is not satisfied (NO in S13), the processes after step S1 are repeatedly executed.
  • the vehicle 60 traveling in the second lane 102 is provided with vehicle information such as the positions and vehicle lengths of the vehicles 60A and 60B traveling in the first lane 101. Can be done. As a result, the vehicle 60 traveling in the second lane 102 can determine the lane change position to the first lane 101, the lane change timing, and the like, thereby supporting the lane change of the vehicle 60.
  • the computer program for operating the computer as the traffic flow measuring device 3 or the driving support device 5 may be recorded on a computer-readable non-temporary recording medium such as an HDD, a CD-ROM, or a semiconductor memory. Good.
  • the computer program may be transmitted via a telecommunication line, a wireless or wired communication line, a network represented by the Internet, data broadcasting, or the like. Further, each of the above devices may be realized by a plurality of computers.
  • each of the above devices may be provided by cloud computing. That is, some or all the functions of each device may be realized by the cloud server.
  • the function of the traffic flow measuring unit 38 of the traffic flow measuring device 3 is realized by the cloud server, and the traffic flow measuring device 3 transmits the information stored in the storage unit 40 to the cloud server, and the cloud server. It may be configured to receive traffic flow information from.
  • Traffic information providing system 1A Traffic information providing system 2 Sensor 3 Traffic flow measuring device 5 Driving support device 10 Central device 31 Vehicle position measuring unit 32 Speed measuring unit 33 Vehicle length measuring unit (vehicle size measuring unit) 34 Accuracy detection unit 35 Vehicle tracking unit 36 Vehicle length determination unit 37 Vehicle type determination unit 38 Traffic flow measurement unit 39 Traffic information provision unit 40 Storage unit 51 Vehicle information provision unit 60 Vehicle 60A Vehicle 60B Vehicle 70 Area 100 Road 101 First lane 102 2nd lane P1 Tip position P11 Rear end position P12 Rear end position P2 Tip position

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2024019819A (ja) * 2022-08-01 2024-02-14 株式会社ブレインズ 移動速度測定装置

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20220144456A (ko) * 2021-04-19 2022-10-27 현대모비스 주식회사 Svm 원 영상을 기반으로 근접 주행 환경을 인식하는 방법 및 시스템

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002056493A (ja) * 2000-08-07 2002-02-22 Hitachi Ltd 車両特定装置
JP2004005726A (ja) * 2003-07-24 2004-01-08 Fujitsu Ltd 移動物体の交通流監視システム

Family Cites Families (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5528234A (en) * 1994-02-01 1996-06-18 Mani; Siva A. Traffic monitoring system for determining vehicle dimensions, speed, and class
JPH1186192A (ja) * 1997-09-05 1999-03-30 Omron Corp 車輌情報提供システム
JPH1186183A (ja) * 1997-09-11 1999-03-30 Hitachi Ltd 交通流計測装置、及びこれを利用する装置
DE10323422B4 (de) * 2002-08-23 2022-05-05 Carl Zeiss Meditec Ag Vorrichtung und Verfahren zur Messung eines optischen Durchbruchs in einem Gewebe
DE102011056861A1 (de) * 2011-12-22 2013-06-27 Jenoptik Robot Gmbh Verfahren und Anordnung zur Erfassung von Messdaten eines Fahrzeugs in einem Radarfeld
JP2016133341A (ja) * 2015-01-16 2016-07-25 株式会社リコー 物体検出装置、センシング装置、移動体装置及び物体検出方法
JP6650344B2 (ja) * 2015-10-02 2020-02-19 パナソニック株式会社 物体検出装置及び物体検出方法
JP2017096792A (ja) * 2015-11-25 2017-06-01 株式会社デンソーウェーブ 交通量計測装置
JP6571545B2 (ja) * 2016-01-19 2019-09-04 パナソニック株式会社 物体検出装置および物体検出方法
JP7152395B2 (ja) * 2016-11-02 2022-10-12 ぺロトン テクノロジー インコーポレイテッド 車両隊列のためのギャップ測定
JP6965050B2 (ja) * 2017-07-21 2021-11-10 株式会社タダノ ガイド情報表示装置およびこれを備えたクレーンおよびガイド情報表示方法
DE102017120788A1 (de) * 2017-09-08 2019-03-14 Liebherr-Verzahntechnik Gmbh Verfahren und Vorrichtung zum Wälzschälen
JP6953084B2 (ja) * 2017-10-06 2021-10-27 日本無線株式会社 レーダ信号処理装置およびレーダ信号処理プログラム
JP2019070567A (ja) * 2017-10-06 2019-05-09 日本無線株式会社 移動体認識レーダ装置
JP7092540B2 (ja) * 2018-04-04 2022-06-28 パナソニックホールディングス株式会社 交通監視システムおよび交通監視方法
JP7196412B2 (ja) * 2018-04-09 2022-12-27 株式会社デンソー 物体認識装置、及び、物体認識方法
CN109614889B (zh) * 2018-11-23 2020-09-18 华为技术有限公司 对象检测方法、相关设备及计算机存储介质
JP7295648B2 (ja) * 2019-02-05 2023-06-21 古河電気工業株式会社 レーダ装置およびレーダ装置の制御方法

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002056493A (ja) * 2000-08-07 2002-02-22 Hitachi Ltd 車両特定装置
JP2004005726A (ja) * 2003-07-24 2004-01-08 Fujitsu Ltd 移動物体の交通流監視システム

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2024019819A (ja) * 2022-08-01 2024-02-14 株式会社ブレインズ 移動速度測定装置
JP7757576B2 (ja) 2022-08-01 2025-10-22 株式会社ブレインズ 移動速度測定装置

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