JP2019132713A - Velocity computation device, velocity computation method, and program - Google Patents

Abstract

To allow for accurately computing velocity in various environments by using a GNSS receiver and external sensor.SOLUTION: A velocity computation device detects satellites whose signals can be received, and identifies satellites blocked by objects using a detection device for detecting objects. The velocity computation device then excludes blocked satellites from the satellites whose signals can be received to identify satellites whose signals can be properly received, and computes velocity of a mobile vehicle using signals from the satellites whose signals can be received properly.SELECTED DRAWING: Figure 10

Description

  The present invention relates to a technique for calculating the speed of a moving object.

  In a vehicle equipped with a navigation device, the vehicle speed is detected using a vehicle speed sensor, a GNSS (GPS) receiver, or the like. A speed detection method using a GNSS receiver obtains a speed by calculating a Doppler shift or a position difference.

  In recent years, a method for detecting the speed of a vehicle using an external sensor such as a lidar (LiDAR: Light Detection And Ranging) has been proposed. In the speed calculation method using the external sensor, the speed is calculated based on a change in distance with respect to the same object recognized by the external sensor. An example of a speed calculation method using an external sensor is described in Patent Document 1.

International Publication WO2017 / 109973

  Since the speed detection method using the GNSS receiver calculates the speed using the observed value, the accuracy is lowered depending on the environment and behavior of the vehicle. Specifically, when the radio wave reception from the satellite is bad or when the acceleration / deceleration of the vehicle is large (especially in the low speed range), the accuracy of the detected value decreases and the speed detection accuracy decreases. . In order to improve this point, a system that corrects dynamics such as actual acceleration / deceleration by combining with an inertial navigation unit (IMU) has been proposed, but the actual positioning environment is poor. The correction according to was not performed. On the other hand, in the speed calculation method using the external sensor, the speed calculation itself cannot be performed when there is no object around the vehicle.

  Examples of the problem to be solved by the present invention include the above. An object of the present invention is to provide a speed calculation device that can calculate a speed with high accuracy in various environments by using a GNSS receiver and an external sensor.

  The invention according to claim 1 is a velocity calculation device, and uses a detection means for detecting a satellite capable of receiving a signal and a detection device for detecting a feature to identify a satellite shielded by the feature. Identifying means, excluding the shielded satellite from satellites that can receive the signal, identifying satellites that can receive signals normally, and based on signals from the satellites that can receive signals normally, Speed calculating means for calculating the speed of the moving body.

  The invention according to claim 7 is a speed calculation method executed by the speed calculation device, wherein a detection step for detecting a satellite capable of receiving a signal and a detection device for detecting the feature are used to detect the feature. A step of specifying a satellite to be shielded; a satellite capable of receiving a signal normally by excluding the shielded satellite from a satellite capable of receiving the signal; A speed calculation step of calculating the speed of the moving body based on a signal from

  The invention according to claim 8 is a program executed by a speed calculation device including a computer, and uses a detection means for detecting a satellite capable of receiving a signal and a detection device for detecting a feature to detect the feature. Identifying means for identifying a shielded satellite, excluding the shielded satellite from satellites that can receive the signal, identifying satellites that can normally receive signals, and from satellites that can normally receive signals Based on this signal, the computer is caused to function as speed calculation means for calculating the speed of the moving body.

It is a block diagram which shows the structure of the speed calculation apparatus which concerns on the Example of this invention. It is a figure explaining the calculation method of the speed by a rider. It is a flowchart of a speed calculation process. It is a flowchart of the accuracy determination process by 1st Example. It is a figure explaining the method to detect the satellite from which an electromagnetic wave is blocked | interrupted by the feature. It is a flowchart of the accuracy determination process by 2nd Example. It is a flowchart of the precision determination process at the time of combining a 1st and 2nd Example. It is a flowchart of the accuracy determination process by 3rd Example. It is a flowchart of the accuracy determination process by 4th Example. It is a block diagram which shows the structure of the speed calculation apparatus which concerns on the modification 1.

  In one preferred embodiment of the present invention, the velocity calculation device uses a detection means for detecting a satellite capable of receiving a signal and a detection device for detecting the feature to identify a satellite shielded by the feature. Identifying means, excluding the shielded satellite from satellites that can receive the signal, identifying satellites that can receive signals normally, and based on signals from the satellites that can receive signals normally, Speed calculating means for calculating the speed of the moving body.

  The speed calculation device detects a satellite that can receive a signal and uses a detection device that detects a feature to identify a satellite that is shielded by the feature. The speed calculation device excludes satellites that are shielded from satellites that can receive signals, identifies satellites that can normally receive signals, and moves based on signals from satellites that can normally receive signals. Calculate body speed. Thereby, based on the signal from a satellite, the speed of a mobile body can be calculated with high precision.

  In one aspect of the speed calculation device, the speed calculation means is based on the elevation angle of the satellite with respect to the receiver that receives the signal, and the distance between the feature existing in the direction of the satellite and the detection device, The shielded satellite is identified. In this aspect, the shielded satellite is detected based on the positional relationship between the receiver and the satellite and the positional relationship between the feature and the detection device.

  In a preferred example in this case, the detection device detects the feature by two-dimensional scanning, and the speed calculation means uses the height of the feature acquired from map information, so that the satellite can detect the feature. It is detected whether or not the object is shielded. In another preferable example, the detection device detects the feature by three-dimensional scanning, and the speed calculation unit is configured to determine an elevation angle in a scanning direction when the detection device detects the top of the feature. Using the elevation angle of the satellite, it is determined whether the satellite is shielded by the feature.

  Another aspect of the speed calculation device includes first calculation means for calculating the speed of the moving body based on an output of a detection device that detects a feature, and the speed calculation means outputs the signal normally. Based on the number of received satellites, the speed calculated based on the signal from the satellite and the speed calculated by the first calculating means are weighted to calculate the speed of the moving body. In this aspect, the speed of the moving object is calculated by weighted addition of the speed calculated based on the signal from the satellite and the speed calculated based on the output of the detection device. In this case, preferably, the speed calculation means increases the weight of the speed calculated based on the signal from the satellite as the number of satellites that can normally receive the signal increases.

  In another preferred embodiment of the present invention, the speed calculation method executed by the speed calculation device uses a detection step for detecting a satellite capable of receiving a signal and a detection device for detecting the feature to detect the feature. A step of specifying a satellite to be shielded; a satellite capable of receiving a signal normally by excluding the shielded satellite from a satellite capable of receiving the signal; A speed calculation step of calculating the speed of the moving body based on a signal from Also by this method, the speed of the moving body can be calculated with high accuracy based on the signal from the satellite.

  In another preferred embodiment of the present invention, a program executed by a speed calculation device including a computer uses a detection unit that detects a satellite capable of receiving a signal, and a detection device that detects a feature. Identifying means for identifying a shielded satellite, excluding the shielded satellite from satellites that can receive the signal, identifying satellites that can normally receive signals, and from satellites that can normally receive signals Based on this signal, the computer is caused to function as speed calculation means for calculating the speed of the moving body. The speed calculation device described above can be realized by executing this program on a computer. This program can be stored and handled in a storage medium.

Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.
[Configuration of speed calculation device]
FIG. 1 shows the configuration of a speed calculation apparatus according to an embodiment of the present invention. The speed calculation device 1 is mounted on a moving body such as a vehicle and calculates its speed. As illustrated, the speed calculation device 1 is connected to a GNSS receiver 2, a rider 3, and a speed sensor 4.

The GNSS receiver 2 is a device that receives radio waves from a plurality of satellites and measures the current position, and includes an antenna 21, a GNSS data acquisition unit 22, and a positioning calculation unit 23. The antenna 21 receives radio waves from a plurality of satellites and supplies received signals to the GNSS data acquisition unit 22. GNSS data acquisition unit 22 acquires the GNSS data _{D G} based on radio waves from satellites, and supplies to the positioning computation unit 23 and the speed calculation device 1. GNSS data D _G is the data including distance and position of each satellite and each satellite that receives radio waves. Positioning calculation unit 23 calculates the current position of the vehicle based on GNSS data D _G from a plurality of satellites, and supplies to the velocity calculating device 1.

The lidar 3 is mounted on a vehicle, scans outgoing light over a predetermined angle range, receives reflected light obtained by reflecting the outgoing light by an object, and indicates point cloud data indicating the object based on the reflected light. supplies lidar data D _L is the velocity calculating apparatus 1. In the present embodiment, the lidar 3 may be a two-dimensional (2D) lidar or a three-dimensional (3D) lidar. The 2D lidar is a device that scans outgoing light in a horizontal plane, and the 3D lidar is a device that scans outgoing light while changing the elevation angle of the outgoing light.

Speed sensor 4, for example the vehicle speed sensor, and the like acceleration sensor, and supplies the sensor data D _S to the speed calculation device 1.

Velocity calculating apparatus 1 includes a GNSS data _{D G} from the GNSS receiver 2, a rider data _{D L} from rider 3, based on the sensor data _{D S} from the speed sensor 4, the speed calculation device 1 is mounted A speed V indicating the speed of the vehicle is output. Specifically, the speed calculation device 1 includes a speed calculation unit 11, a feature specifying unit 12, speed calculation units 13 and 14, a map database (hereinafter, “database” is referred to as “DB”) 15, and A vehicle information DB 16, a situation determination unit 17, and a speed determination unit 18 are provided.

The speed calculation unit 11 calculates the speed of the vehicle based on the position data generated by the positioning calculation unit 23 of the GNSS receiver 2. Specifically, the speed calculation unit 11 calculates the moving amount per unit time of the current position of the vehicle indicated by the position data as the speed. The speed generated by the speed calculation unit 11 based on the output of the GNSS receiver 2 is referred to as “GNSS speed V _G ”. Speed calculation unit 11 supplies the GNSS speed _{V G} to the speed determination unit 18.

Feature identifying unit 12 identifies the feature based on the lidar data D _L is the point group data of the feature, the presence or absence of a feature, the distance to the feature, the feature of the angles (azimuth, elevation), etc. calculating a feature specific data D _GO comprising supplying to the velocity calculation unit 13 and the state determination section 17. Note that the feature is specified using a shape pattern prepared in advance for each type of feature and indicating the shape, size, and the like of the feature.

The speed calculation unit 13 calculates the speed of the vehicle 1 based on the feature specifying data D _GO . The speed at which the velocity calculation unit 13 on the basis of lidar data D _L is calculated from rider 3 is referred to as a "rider velocity V _L". The speed calculation unit 13 supplies the rider speed V _L to the speed determination unit 18.

Here, an example of a method for calculating the rider speed _VL by the speed calculation unit 13 will be described. FIG. 2 is a diagram for explaining a method for calculating the rider speed V _L. Now, two feature A in each onboard rider is a time T ₁ and time T _2, the traveling vehicle, and that detects a feature B. In this case, the distance from the vehicle at time T ₁ the distance to the feature B and L _B, the azimuth viewed feature from the vehicle at time T ₁ and phi _B, from the vehicle at time T _2, to feature B Is defined as L _B ′, an azimuth angle when the feature is viewed from the vehicle at time T ₂ is defined as φ _B ′, and an angle α is defined as α = φ _B ′ −φ _B , the vehicle from time T ₁ to time T ₂ Is given by the following equation.

Therefore, the rider speed V _L is
V _L = ΔD / (T ₂ −T ₁ ) (1)
And obtained. This speed calculation method is described in detail in Patent Document 1.

Speed calculation unit 14 calculates the speed of the vehicle based on the sensor data D _S which is supplied from the speed sensor 4. The speed at which the velocity calculation unit 14 based on the sensor data D _S is calculated from the speed sensor 4 is referred to as a "sensor rate V _S". The speed calculation unit 14 supplies the sensor speed V _S to the speed determination unit 18.

  Map data is memorize | stored in map DB15. The map data includes feature data indicating the shape and height of features such as buildings. The vehicle information DB 16 stores data related to the vehicle on which the speed calculation device 1 is mounted. In particular, the vehicle information DB 16 stores the antenna height, which is the height from the ground of the antenna 21 of the GNSS receiver 2 mounted on the vehicle.

  The situation determination unit 17 detects an environment in which the vehicle is placed, a running state of the vehicle, and the like (hereinafter referred to as “vehicle situation”). Specifically, the situation determination unit 17 determines the reception status of the radio wave from the satellite by the GNSS receiver 2, the detection status of the features around the vehicle by the lidar 3, the acceleration / deceleration status of the vehicle, the weather status of the surroundings of the vehicle, and the like. It determines as a vehicle situation and supplies the control information C1 which shows the determination result to the speed determination part 18. FIG.

The speed determination unit 18 is based on the GNSS speed V _G supplied from the speed calculation unit 11, the rider speed V _L supplied from the speed calculation unit 13, and the sensor speed V _S supplied from the speed calculation unit 14. The speed with the highest accuracy is calculated and output as the final speed V. At that time, the speed determination unit 18 determines the speed V based on the determination result of the vehicle situation supplied from the situation determination unit 17. Specifically, the speed determination unit 18 determines any of the GNSS speed V _G , the rider speed V _L , and the sensor speed V _{S as} the speed V according to the vehicle situation, or the GNSS speed V _G and the rider speed V. _The speed V is calculated by weighting and adding _L.

  In the above configuration, the GNSS receiver 2 is an example of the detection unit of the present invention, the lidar 3 is an example of the detection device of the present invention, and the situation determination unit 17 is an example of the specifying unit of the present invention, and the speed calculation. The unit 11 is an example of a speed calculation unit of the present invention.

[Speed calculation method]
Next, a method for calculating the speed V by the speed calculation unit 18 will be described. FIG. 3 is a flowchart of a speed calculation process for calculating the speed V. This process is mainly executed by the situation determination unit 17 and the speed determination unit 18 shown in FIG. In practice, this processing is realized by a computer such as a CPU executing a program prepared in advance.

First, the situation determination unit 17 determines whether or not the speed calculation by GNSS is valid (step S10). Specifically, state determination section 17, based on GNSS data D _G supplied from the GNSS receiver 2 judges reception conditions of a plurality of satellites, and can receive radio waves at a predetermined level or higher strength When there are a predetermined number or more of satellites, it is determined that speed calculation by GNSS is effective. The “predetermined number” in this case is the minimum number of satellites necessary for positioning the position of the vehicle based on the positions of the satellites, and can be obtained in advance by experiments or the like.

When the speed calculation by GNSS is not valid (step S10: No), the situation determination unit 17 determines whether or not the speed calculation by the rider is valid (step S11). Specifically, state determination section 17, based on the lidar data D _L supplied from the rider 3, the number of features required for calculating the speed is determined whether it has been detected, it is detected In this case, it is determined that the speed calculation by the rider is effective.

When the speed calculation by the rider is not valid (step S11: No), the situation determination unit 17 notifies the speed determination unit 18 that the sensor speed V _S calculated based on the output of the speed sensor 4 is used, and the speed determination unit 17 The determination unit 18 outputs the sensor speed V _S as the speed V (step S12).

On the other hand, when the speed detection by the lidar is valid (step S11: Yes), the situation determination unit 17 speeds up the control signal C1 instructing to use the lidar speed _VL calculated based on the output of the lidar 3. The speed determination unit 18 outputs the lidar speed V _L as the speed V (step S13).

In step S10, when it is determined that the speed calculation by GNSS is valid (step S10: Yes), the situation determination unit 17 determines whether the speed calculation by the rider is valid (step S14). If the speed calculated by the rider is not valid (step S14: No), status determining unit 17, the speed determining portion control signal C1 for instructing the use of GNSS speed _{V G} to be calculated based on the output of the GNSS receiver 2 supplied to 18, the rate determining unit 18 outputs the GNSS speed _{V G} as the speed V (step S15).

On the other hand, if the speed calculated by the rider is enabled (step S14: Yes), so that both the GNSS speed _{V G} and rider velocity _{V L} is obtained. In this case, the speed determination unit 18 calculates the velocity V by weighted addition of GNSS speed _{V G} and rider velocity _{V L.} Assuming that the weight of the GNSS speed V _G is w _G and the weight of the rider speed V _L is w _L , the speed determination unit 18 determines the speed V by the following equation, for example.
V = w _G · V _G + w _L · V _L (2)
However, w _G + w _L = 1
At this time, the situation determination unit 17 determines which one of the GNSS speed V _G and the rider speed V _L is highly accurate, and sets the weights w _G and w _L according to the result.

Specifically, state determination section 17 are both of GNSS speed _{V G} and rider velocity _{V L} is carried out for determining precision determination processing whether a high accuracy (Step S16). There are several examples of accuracy determination, which will be described later. When it is determined by the accuracy determination processing that the GNSS speed V _G is higher accuracy, the situation determination unit 17 makes the weight w _G of the GNSS speed V _G larger than the weight w _L of the rider speed V _L (step S17). ). On the other hand, if the direction of the rider velocity V _L by precision determination processing is determined to be accurate, the status determination unit 17 is larger than the weight w _G of weights w _L a GNSS speed V _G of the rider velocity V _L ( Step S18).

Then, the speed determination unit 18 calculates and outputs the speed V by the above equation (2) using the weights w _G and w _L set in step S17 or S18 (step S19). As described above, by calculating the speed V in consideration of whether the speed calculation by the GNSS and the speed calculation by the lidar are effective, and which of the GNSS speed and the lidar speed is high accuracy, various situations can be obtained. Thus, the speed can be calculated with the highest possible accuracy.

[Accuracy judgment processing]
Next, some examples of the accuracy determination process executed in step S16 of FIG. 3 will be described.
(First embodiment)
In the first embodiment, the situation determination unit 17 performs accuracy determination based on the number of satellites that the GNSS receiver 2 has normally received signals. FIG. 4 is a flowchart of the accuracy determination process according to the first embodiment. First, the situation determination unit 17 acquires the feature specifying data D _GO from the feature specifying unit 12 (step S21). Next, the situation determination unit 17 counts the number of satellites that cannot receive direct waves among a plurality of satellites that are receiving radio waves, that is, the number of satellites that are blocked by obstacles (step S22). Here, the “satellite receiving a radio wave” means a satellite that receives a radio wave at an intensity level necessary for positioning by the GNSS receiver 2.

The process of step S22 will be described in detail with reference to FIG. FIG. 5A shows a method of counting the number of satellites whose radio waves are blocked by obstacles (hereinafter also referred to as “shielded satellites”) when the lidar 3 mounted on the vehicle is a 2D lidar. FIG. FIG. 5A shows a state in which a predetermined azimuth angle direction is viewed from the vehicle 7. Status determining unit 17 selects one satellite being received radio waves, obtain GNSS data _{D G.} The status determining section 17, the position of the satellites included in the GNSS data D _G, based on the position of the vehicle 7, and calculates the elevation angle θ of the satellite. Moreover, the situation determination part 17 acquires the height h0 of the antenna 21 mounted on the vehicle 7 from the vehicle information DB 16. Moreover, the situation determination part 17 acquires the height h of the building which exists in the direction of a satellite from map DB15. Furthermore, the situation determination unit 17 acquires the distance L to the building from the feature specifying data D _GO acquired in step S21. For convenience of explanation, it is assumed that the height of the 2D lidar is the same as the height h0 of the antenna.

Here, the height H at which the satellite is seen from the antenna 21 mounted on the vehicle 7 (broken line 31) hits the building, that is, the broken line 31 connecting the antenna 21 and the satellite intersects the perpendicular to the ground at the position of the building. The height H of the point (hereinafter referred to as “the height H in the satellite direction at the building position”) is:
H = L × tan θ + h0 (3)
Given in. Therefore, when the height H in the satellite direction at the building position is lower than the actual building height h acquired from the map DB 15, the situation determination unit 17 determines that the satellite is a shielded satellite. The situation determination unit 17 performs this process for all satellites that are receiving radio waves, and calculates the number of satellites that are blocked.

FIG. 5B is a diagram illustrating a method of counting the number of satellites that are shielded when the lidar 3 mounted on the vehicle is a 3D lidar. FIG. 5B schematically shows a three-dimensional space including the vehicle 7, the building, and the satellite. Status determining unit 17 selects one satellite being received radio waves, and calculates the elevation angle θ of the satellite using the GNSS data D _G. Moreover, the situation determination part 17 acquires the height h0 of the antenna 21 mounted on the vehicle 7 from the vehicle information DB 16. For convenience of explanation, it is assumed that the height of the 3D lidar is the same as the height h0 of the antenna.

Then, based on the feature specifying data G _DO acquired in step S21, the situation determination unit 17 determines whether there is a building in the direction of viewing the satellite from the position of the antenna 21, that is, in the direction of the elevation angle θ (broken line 32). If there is a building, it is determined that the satellite is a shielded satellite. For example, the situation determination unit 17 determines that the satellite is shielded by the building when the elevation angle in the scanning direction when the top of the building is detected by the 3D lidar is larger than the elevation angle θ of the satellite. The situation determination unit 17 performs this process for all satellites that are receiving radio waves, and calculates the number of satellites that are blocked.

  When the number of shielded satellites is obtained in this way, the situation determination unit 17 subtracts the number of shielded satellites from the total number of satellites being received, that is, the number of satellites that can normally receive radio waves (hereinafter referred to as the number of satellites that can be normally received). , Also referred to as “the number of normally received satellites”) is determined to be equal to or greater than a certain ratio with respect to the total number of satellites being received (step S23). This fixed ratio is a ratio of the number of normally received satellites necessary for realizing the required accuracy, and is determined in advance based on experiments or the like.

When status determination unit 17 is the number of normal reception satellite more than a certain percentage of the total number of satellites being received (step S23: Yes), towards the GNSS speed _{V G} is determined to be a high precision (step S24 ). On the other hand, when the number of normally received satellites is less than a certain ratio of the number of all currently received satellites (step S23: No), the situation determining unit 17 determines that the lidar speed V _L is more accurate (step S25). ). Thus, the accuracy determination process ends.

In this case, the situation determination unit 17 increases the weight w _G of the GNSS speed V _G in step S17 as the ratio of the number of normal reception satellites increases, and the lidar speed V in step S18 as the ratio of the number of normal reception satellites decreases. it is preferable to increase the weights _{w L} of _L.

As described above, according to the accuracy determination method of the first embodiment, the weight w _G is determined by evaluating the accuracy of the GNSS speed V _G based on the number of satellites that can normally receive radio waves. It is possible to calculate the speed V with high accuracy even in a situation of being shielded.

In the above example, the situation determination unit 17 determines whether or not the number of normally received satellites is greater than or equal to a certain ratio with respect to the total number of satellites being received in step S23. It may be determined whether or not the number of satellites to be received is equal to or greater than a certain ratio with respect to the total number of satellites being received. In that case, the situation determination unit 17 determines that the lidar speed _VL is more accurate when the number of satellites to be shielded is equal to or greater than a certain ratio with respect to the total number of satellites being received. towards the GNSS speed V _G may be determined to be accurate if that number of satellites is less than a certain percentage of the total number of satellites being received.

  In the above example, the situation determination unit 17 determines whether or not the number of normally received satellites is equal to or greater than a certain ratio with respect to the total number of satellites being received. It may be determined whether or not is a predetermined number or more. Similarly, when the determination is performed using the number of satellites that are blocked, the situation determination unit 17 may determine whether or not the number of satellites that are blocked is equal to or greater than a predetermined number.

As described above, in the first embodiment, the status determination unit 17, the accuracy relative comparison of accuracy and rider velocity _{V L} of the GNSS speed _{V G,} the weight of the GNSS velocity _{V G w G} and rider velocity _{V L} I have set of weights w _L. In addition, the weights w _G and W _L may be corrected according to the absolute accuracy of each. For example, state determination section 17 calculates the standard deviation of the distance and / or the value of the angle of the satellite with the satellite indicated by the GNSS data D _G obtained within a predetermined time, or these values are what extent variation To detect. The status determining section 17, the larger the variation of the GNSS data _{D G} reduces the weight _{w G} of GNSS speed _{V G,} to increase the weight _{w G} enough GNSS velocity _{V G} variation in GNSS data _{D G} is small. Similarly, state determination section 17 calculates the standard deviation of the distance and / or orientation of the values of the feature of the feature indicated by the lidar data D _L obtained within a predetermined time, vary how those values Detect whether or not The status determining unit 17, to reduce the weight w _G lidar data D _L about rider velocity V _L having large variations of, increasing the weight w _L enough rider velocity V _L variations in rider data D _L is small. As a result, not only the relative comparison between the GNSS speed V _G and the rider speed V _L but also the individual absolute accuracy of the GNSS speed V _G and the rider speed V _L are taken into consideration, and the speed V is calculated by the optimum weighting. can do.

(Second embodiment)
In the second embodiment, the situation determination unit 17 sets weights for the GNSS speed V _G and the rider speed V _L according to the acceleration of the vehicle. Generally, GNSS data D _G obtained by the GNSS receiver 2, when the acceleration of the vehicle is large, the accuracy when the acceleration is large especially at low velocity region tends to decrease. Therefore, in the second embodiment, the situation determination unit 17 determines that the rider speed V _L is more accurate when the acceleration of the vehicle is large, and the GNSS speed V _G when the acceleration of the vehicle is small. Is determined to be highly accurate.

FIG. 6 is a flowchart of the accuracy determination process according to the second embodiment. The situation determination unit 17 acquires the feature specification data D _GO from the feature specification unit 12 (step S31), and determines whether or not the acceleration of the vehicle is equal to or greater than a certain value using the feature specification data G _DO. (Step S32). For example, the situation determination unit 17 periodically calculates the speed based on the feature specifying data G _DO , and if the difference between the previous speed and the current speed is a certain value or more, the vehicle acceleration is a certain value or more. It is determined that The status determining section 17, when the acceleration of the vehicle is less than a predetermined value, it is determined that the direction of GNSS speed V _G is high precision (step S33), if it is the acceleration of the vehicle is above a certain value Determines that the rider speed _VL is more accurate (step S34). Then, the situation determination unit 17 ends the accuracy determination process.

In this case, the situation determination unit 17 increases the weight w _G of the GNSS speed V _G in step S17 as the vehicle acceleration decreases, and increases the weight w _L of the rider speed V _L in step S18 as the vehicle acceleration increases. It is preferable to enlarge it.

Thus, according to the second embodiment, since the weighting of GNSS speed V _G and rider velocity V _L in consideration of the acceleration of the vehicle, and calculates the velocity V with high accuracy even if acceleration and deceleration of the vehicle is large be able to.

It should be noted that the accuracy determination process of the second embodiment can be performed in combination with the accuracy determination process of the first embodiment. In this case, the situation determination unit 17 weights the GNSS speed V _G and the rider speed V _L in consideration of both the ratio of the number of normally received satellites and the acceleration of the vehicle. FIG. 7 is a flowchart of the accuracy determination process when the first embodiment and the second embodiment are combined.

First, the situation determination unit 17 acquires the feature specifying data D _GO from the feature specifying unit 12 (step S41). Next, the situation determination unit 17 counts the number of satellites that are shielded among a plurality of satellites that are receiving radio waves (step S42). Next, the situation determination unit 17 determines whether or not the number of normally received satellites is equal to or greater than a certain ratio with respect to the total number of satellites being received (step S43). When the number of normally received satellites is less than a certain percentage of the total number of satellites being received (step S43: No), the situation determination unit 17 determines that the lidar speed V _L is more accurate (step S46). On the other hand, when the number of normally received satellites is equal to or greater than a certain percentage of the total number of satellites being received (step S43: Yes), the situation determination unit 17 uses the feature specifying data D _GO to increase the vehicle acceleration to a certain value or more. It is determined whether or not (step S44).

State determination section 17, if the acceleration of the vehicle is less than a predetermined value (step S44: No), towards the GNSS speed _{V G} is determined to be accurate (step S45), the acceleration of the vehicle is a predetermined value or more If present (step S44: Yes), it is determined that the rider speed _VL is more accurate (step S46). Thus, the accuracy determination process ends.

As another example in which the first embodiment and the second embodiment are combined, the weight obtained by the accuracy judgment processing of the first embodiment is multiplied by the weight obtained by the accuracy judgment processing of the second embodiment. The final weight may be determined. Specifically, the situation determination unit 17 performs both the accuracy determination process according to the first embodiment and the determination process according to the second embodiment in step S16 in FIG. Here, the weight of GNSS velocity _{V G} obtained by the precision determination process of Embodiment 1 _{w G1,} the weight of the rider velocity _{V L} and _{w L1,} GNSS speed obtained by the precision determination process of the second embodiment the weight of V _{G w G2,} if the weight of the rider velocity _{V L} is the _{w L2,} state determination section 17 multiplies their weights, respectively, the weights _{w G} and rider speeds of GNSS velocity _{V G} as follows it may be calculated the weight _{w L} of V _L.
Weight of GNSS velocity _{V G: w G = w G1} × w G2 (4)
Weight of rider speed VL: w _L = w _L1 × w _L2 (5)

  As described above, by combining the first embodiment and the second embodiment, the speed V can be calculated with high accuracy in consideration of both the satellite reception state and the vehicle acceleration / deceleration state.

(Third embodiment)
In the third embodiment, the situation determination unit 17 sets the weights of the GNSS speed V _G and the rider speed V _L according to the number of features existing around the vehicle, more specifically, the number of features detected by the rider 3. Since the lidar 3 scans the outgoing light around it and receives the reflected light reflected by the feature to detect the feature existing around it, if the number of features around the vehicle is small, the lidar data D The accuracy of the rider speed V _L calculated based on _L decreases. Therefore, in the third embodiment, the situation determination unit 17 determines that the rider speed V _L is more accurate when the number of features existing around the vehicle is large, and the number of features present around the vehicle. towards the GNSS velocity V _G in the case is small is determined to be accurate.

FIG. 8 is a flowchart of the accuracy determination process according to the third embodiment. The situation determination unit 17 acquires the feature specifying data D _GO from the feature specifying unit 12 (step S51), and the number of features existing around the vehicle is equal to or greater than a certain number using the feature specifying data D _GO. It is determined whether or not (step S52). The status determining section 17, when the number of feature existing in the neighborhood of the vehicle is less than a predetermined number, it is determined that the direction of GNSS speed V _G is high precision (step S53), and present in the vicinity of the vehicle If the number of features is equal to or greater than a certain number, it is determined that the rider speed _VL is more accurate (step S54). Thus, the accuracy determination process ends.

In this case, the situation determination unit 17 increases the weight w _G of the GNSS speed V _G in step S17 as the number of features existing in the vicinity of the vehicle decreases, and increases as the number of features existing in the vicinity of the vehicle increases in step S18. In this case, it is preferable to increase the weight w _L of the rider speed V _L.

Thus, according to the third embodiment, since the weighting of GNSS speed V _G and rider velocity V _L in consideration of the number of feature existing in the neighborhood of the vehicle, high depending on the environment where the vehicle is traveling The speed V can be calculated with accuracy.

The accuracy determination process of the third embodiment can be performed in combination with one or both of the accuracy determination processes of the first embodiment and the second embodiment. For example, when combined with the accuracy determination processing of the first embodiment and the second embodiment, the situation determination unit 17 considers the ratio of the number of normally received satellites, the acceleration of the vehicle, and the number of features existing around the vehicle. Thus, the GNSS speed V _G and the rider speed V _L are weighted. As a specific example in this case, the situation determination unit 17 executes the accuracy determination processing of the first to third embodiments in step S16 in FIG. 3 to obtain the weights of the first to third embodiments. Each may be calculated and multiplied to determine the final weight.

(Fourth embodiment)
In the fourth embodiment, the situation determination unit 17 sets the weights of the GNSS speed V _G and the rider speed V _L according to the weather information of the place where the vehicle exists. The lidar 3 scans the outgoing light around it, receives the reflected light reflected by the features and detects the features present in the surroundings, and thus affects the reflection and scattering of light such as fog, snow, and rain. under weather give the accuracy of the lidar speed V _L to be calculated based on the rider data D _L is reduced. Therefore, in the fourth embodiment, the situation determination unit 17 acquires weather information of a place where the vehicle is present, and is a weather situation where the accuracy of the rider is reduced (hereinafter referred to as “low precision weather situation”). towards the GNSS speed _{V G} than rider velocity _{V L} in is judged to be accurate.

  Here, the “low-precision weather situation” includes a situation where humidity (moisture) in the atmosphere is high, such as fog, snow, and rain. Moreover, you may determine whether it is a low precision weather condition based on the visibility ahead of a vehicle. “Visibility” refers to the distance that can be seen in the horizontal direction, and the visibility decreases when the visibility becomes worse due to fog, snow, rain, or the like.

  The determination of whether or not the “low-precision weather condition” is made can be performed as follows. As a first method, the situation determination unit 17 can make this determination based on weather information of the location of the vehicle. In this case, the situation determination unit 17 may access an external server (not shown) to acquire weather information of an area where the vehicle exists, and perform determination based on the weather information. As a second method, when a humidity sensor is mounted on the vehicle, the situation determination unit 17 can make this determination based on the output of the humidity sensor. For example, the situation determination part 17 can determine that it is a low-precision weather situation when the humidity output from the humidity sensor is equal to or higher than a predetermined value. As a third method, the situation determination unit 17 can make this determination based on the output of the raindrop sensor mounted on the vehicle. For example, when the moisture or water pressure detected by the raindrop sensor is greater than or equal to a predetermined value, it can be determined that the weather condition is low accuracy. As a fourth method, when there is a camera that captures the front of the vehicle, the situation determination unit 17 estimates the weather at that time by analyzing the image captured by the camera, and makes this determination based on the result. It can be carried out. Furthermore, this determination may be performed by detecting rain sound included in sound collected by a camera or the like.

FIG. 9 is a flowchart of the accuracy determination process according to the fourth embodiment. The situation determination unit 17 acquires the weather information around the vehicle by any one of the above methods (step S61), and the weather situation around the vehicle changes to a weather situation where the lidar accuracy is lowered, that is, a low-precision weather situation. It is determined whether or not this is true (step S62). State determination section 17, if the weather conditions around the vehicle corresponds to the low precision weather conditions: in (step S62 Yes) determines that towards the GNSS speed V _G is high precision (step S63), the vehicle When the surrounding weather condition does not correspond to the low-accuracy weather condition (step S62: No), it is determined that the rider speed _VL is more accurate (step S64). Thus, the accuracy determination process ends.

In this case, the situation determination unit 17 preferably decreases the weight w _L of the rider speed V _L in step S18 as the weather is worse. For example, the situation determination unit 17 decreases the weight w _L of the rider speed V _L as the humidity detected by the humidity sensor is higher or the visibility is shorter.

Thus, according to the fourth embodiment, by performing the weighting of the GNSS speed V _G and rider velocity V _L in consideration of weather conditions around the vehicle, it is possible to calculate the velocity V with high accuracy.

Note that the accuracy determination process of the fourth embodiment can be performed in combination with any one, any two, or all of the accuracy determination processes of the first to third embodiments. For example, when combined with all the accuracy determination processes of the first to third embodiments, the situation determination unit 17 determines the ratio of the number of normally received satellites, the acceleration of the vehicle, and the number of features existing around the vehicle. , it will perform weighting of GNSS speed V _G and rider velocity V _L in consideration of the weather conditions around the vehicle. As a specific example in this case, the situation determination unit 17 executes the accuracy determination processing of the first to fourth embodiments in step S16 in FIG. 3 to obtain the weights of the first to fourth embodiments. Each may be calculated and multiplied to determine the final weight.

[Modification]
Hereinafter, modifications of the above embodiment will be described.
(Modification 1)
In the first embodiment described above, the status determination unit 17 sets the weight of the GNSS speed V _G and rider velocity V _L on the basis of the number of normal reception satellites. In addition to this, the situation determination unit 17 may limit the satellites used for calculation of the GNSS speed V _G according to the number of normally received satellites. That is, in the first modification, the speed calculation device uses the GNSS data D _G acquired only from the normal reception satellites in addition to weighting the GNSS speed V _G and the lidar speed V _L based on the number of normal reception satellites. To calculate the GNSS speed V _G.

FIG. 10 shows a configuration of a speed calculation device 1A according to the first modification. As can be seen from comparison with FIG. 1, the situation determination unit 17 supplies the control signal C <b> 2 to the positioning calculation unit 23. The control information C2 indicates the satellite to be shielded identified in step S22 of the accuracy determination process of the first embodiment shown in FIG. That is, when the situation determination unit 17 specifies the satellites to be shielded, the situation determination unit 17 supplies the positioning calculation unit 23 with control information C2 for specifying them. Positioning operation unit 23 supplies, among all satellites in reception, satellite other than the satellite to be shielded, i.e. calculates the current position of the vehicle based on GNSS data D _G from the normal reception satellite, the velocity calculation unit 11 . Thereby, the speed calculation unit 11 calculates the GNSS speed V _G based on the GNSS data D _G corresponding only to the normal reception satellite. Therefore, as compared with the case of calculating the GNSS velocity _{V G} based on GNSS data _{D G} from the total received satellite including satellite is shielded, to increase the accuracy of GNSS speed _{V G} for the speed calculation unit 11 outputs it can.

Modification 1 can be implemented in combination with any one, any two, or all of the second to fourth embodiments described above. For example, if a modification 1 in combination with any of the second to fourth embodiments, the speed calculation unit 11 calculates the GNSS velocity _{V G} using GNSS data _{D G} only from normal reception satellite. The status determining section 17, the number of normal reception satellite, and acceleration of the vehicle, the number of feature existing in the neighborhood of the vehicle, the GNSS speed V _G and rider velocity V _L in consideration of the weather conditions around the vehicle Perform weighting.

(Modification 2)
In the above first modification, the speed calculation apparatus 1A, in addition to calculating GNSS velocity _{V G} using GNSS data _{D G} only from normal reception satellite, the GNSS speed _{V G} based on the number of normal reception satellite The rider speed V _L is weighted. Instead, in the second modification, the GNSS speed V _G is calculated using the GNSS data D _G from only the normal receiving satellites, but the weighted addition of the GNSS speed V _G and the lidar speed V _L based on the number of normal receiving satellites Will not be performed.

The configuration of the speed calculation apparatus according to the second modification is basically the same as that of the speed calculation apparatus 1A according to the first modification. However, the situation determination unit 17 does not supply the speed calculation unit 18 with a weighted addition instruction and weights W _G and W _L for that purpose. Therefore, the speed determination unit 18 selects any one of the GNSS speed V _G , the rider speed V _L , and the sensor speed V _S and outputs it as the speed V. Also, the speed calculation unit 11, since the calculated GNSS velocity _{V G} based on GNSS data _{D G} obtained only from the normal reception satellite, GNSS speed based on GNSS data DG from the total received satellite including satellite is shielded as compared with the case of calculating the V _G, it is possible to improve the accuracy of GNSS speed V _G for the speed calculation unit 11 outputs.

Modification 2 can be implemented in combination with any one, any two, or all of the second to fourth embodiments described above. For example, if a modification 2 in combination with any of the second to fourth embodiments, the speed calculation unit 11 calculates the GNSS velocity _{V G} using GNSS data _{D G} only from normal reception satellite. The situation determining unit 13 performs the acceleration of the vehicle, the number of feature existing in the neighborhood of the vehicle, the weighting of the GNSS speed V _G and rider velocity V _L in consideration of the weather conditions around the vehicle.

DESCRIPTION OF SYMBOLS 1 Speed calculation apparatus 2 GNSS receiver 3 Rider 4 Speed sensor 11, 13, 14 Speed calculation part 17 Situation determination part 18 Speed determination part 21 Antenna 22 GNSS data acquisition part 23 Positioning calculation part

Claims (9)

Detection means for detecting a satellite capable of receiving a signal;
A specifying means for specifying a satellite shielded by the feature using a detection device for detecting the feature;
Excluding the shielded satellite from the satellite that can receive the signal, the satellite that can normally receive the signal is specified, and based on the signal from the satellite that can receive the signal normally, the mobile unit Speed calculating means for calculating speed;
A speed calculation device comprising:   The speed calculation means identifies the shielded satellite based on the elevation angle of the satellite with respect to the receiver that receives the signal and the distance between the feature existing in the direction of the satellite and the detection device. The speed calculation apparatus according to claim 1. The detection device detects the feature by two-dimensional scanning,
The speed calculation device according to claim 2, wherein the speed calculation unit detects whether the satellite is shielded by the feature using the height of the feature acquired from map information. The detection device detects the feature by three-dimensional scanning,
The speed calculation means determines whether the satellite is shielded by the feature using the elevation angle in the scanning direction when the detection device detects the top of the feature and the elevation angle of the satellite. The speed calculation apparatus according to claim 2. Based on the output of the detection device for detecting the feature, the first calculation means for calculating the speed of the moving body,
The speed calculation means weights the speed calculated based on the signal from the satellite and the speed calculated by the first calculation means based on the number of satellites that have normally received the signal, and The speed calculation device according to any one of claims 1 to 4, which calculates a speed.   6. The speed calculation apparatus according to claim 5, wherein the speed calculation means increases the weight of the speed calculated based on the signal from the satellite as the number of satellites that can normally receive the signal increases. . A speed calculation method executed by a speed calculation device,
A detection step of detecting a satellite capable of receiving a signal;
A specific step of identifying a satellite shielded by the feature using a detection device for detecting the feature;
Excluding the shielded satellite from the satellite that can receive the signal, the satellite that can normally receive the signal is specified, and based on the signal from the satellite that can receive the signal normally, the mobile unit A speed calculating step for calculating a speed;
A speed calculation method comprising: A program executed by a speed calculation device including a computer,
Detecting means for detecting a satellite capable of receiving a signal;
Identifying means for identifying a satellite shielded by a feature using a detection device for detecting the feature;
Excluding the shielded satellite from the satellite that can receive the signal, the satellite that can normally receive the signal is specified, and based on the signal from the satellite that can receive the signal normally, the mobile unit Speed calculation means for calculating speed;
A program for causing the computer to function as   A storage medium storing the program according to claim 8.