JP7523402B2 - Shape discrimination device, merging support device, shape discrimination method, and program - Google Patents

Description

This disclosure relates to a shape discrimination device, a merging support device, a shape discrimination method, and a program.

At merging sections on expressways, etc., vehicles traveling in the merging lane (hereafter, merging vehicles) must merge into the main lane while checking the position and speed of vehicles traveling in the main lane (hereafter, main lane vehicles).

For this reason, systems that assist with driving operations in merging sections need to accurately identify the shape of vehicles in order to determine things like vehicle spacing between main line vehicles.

As a device for identifying the type of vehicle, for example, a vehicle type discrimination device such as that disclosed in Patent Document 1 is known.

JP 2018-55597 A

Sensors such as vehicle detection sensors are installed on the roadside and perform sensing from the roadside toward the lane, so the angle of the sensor relative to the vehicle being detected may be limited by conditions such as the relative positions of roadside devices, making it difficult to accurately determine the shape of the vehicle, such as its length, height, or width.

The purpose of this disclosure is to provide a shape discrimination device, a merging support device, a shape discrimination method, and a program that can accurately discriminate the shape of a vehicle.

In order to solve the above problem, the shape discrimination device according to the present disclosure includes a first acquisition unit that acquires first detection information from a first sensor that detects a vehicle traveling in a lane from a first direction, a second acquisition unit that acquires second detection information from a second sensor that detects the vehicle from a second direction different from the first direction, a first calculation unit that calculates a first parameter including at least one of vehicle height, vehicle length, and vehicle width based on the first detection information, a second calculation unit that calculates a second parameter including at least one of vehicle height, vehicle length, and vehicle width based on the second detection information, and a complementation unit that complements the first parameter based on the second parameter.

The shape discrimination method disclosed herein acquires first detection information from a first sensor that detects a vehicle traveling in a lane from a first direction, acquires second detection information from a second sensor that detects the vehicle from a second direction different from the first direction, calculates a first parameter including at least one of vehicle height, vehicle length, and vehicle width based on the first detection information, calculates a second parameter including at least one of vehicle height, vehicle length, and vehicle width based on the second detection information, and complements the first parameter based on the second parameter.

The program disclosed herein causes a computer of a shape discrimination device to acquire first detection information from a first sensor that detects a vehicle traveling in a lane from a first direction, acquire second detection information from a second sensor that detects the vehicle from a second direction different from the first direction, calculate a first parameter including at least one of vehicle height, vehicle length, and vehicle width based on the first detection information, calculate a second parameter including at least one of vehicle height, vehicle length, and vehicle width based on the second detection information, and complement the first parameter based on the second parameter.

The shape discrimination device, merging support device, shape discrimination method, and program disclosed herein can accurately discriminate the shape of a vehicle.

1 is an overall view of a merging assistance system according to a first embodiment of the present disclosure. 1 is a block diagram of a shape discrimination device according to a first embodiment of the present disclosure. 4 is a diagram showing an example of first detection information acquired from a first sensor according to the first embodiment of the present disclosure; FIG. 11 is a diagram showing an image obtained by performing coordinate transformation on an image of first detection information D1 according to the first embodiment of the present disclosure. FIG. 11 is a diagram showing an image obtained by performing coordinate transformation on an image of first detection information D1 according to the first embodiment of the present disclosure. FIG. 4A to 4C are diagrams for explaining detection by a second sensor according to the first embodiment of the present disclosure. 4 is a flowchart of a shape discrimination method according to the first embodiment of the present disclosure. FIG. 2 is an overall view showing a modified example of the merging assistance system according to the first embodiment of the present disclosure. FIG. 11 is an overall view of a merging assistance system according to a second embodiment of the present disclosure. FIG. 11 is a block diagram of a matching device according to a second embodiment of the present disclosure. FIG. 11 is a diagram showing a state in which a vehicle is hidden in the X direction according to the second embodiment of the present disclosure. FIG. 11 is a diagram showing a state in which a vehicle is hidden in the Y direction according to the second embodiment of the present disclosure. FIG. 11 is a diagram showing a state in which a vehicle is hidden in the Y direction according to the second embodiment of the present disclosure. FIG. 11 is a diagram showing a state in which a vehicle is hidden in the Y direction according to the second embodiment of the present disclosure. FIG. 11 is a diagram showing an example of a vehicle travel trajectory according to a second embodiment of the present disclosure. FIG. 11 is a diagram showing an example of a vehicle travel trajectory according to a second embodiment of the present disclosure. 11 is a flowchart of a matching method according to a second embodiment of the present disclosure. 1 illustrates an example of a hardware configuration of a computer included in a shape discrimination device, a matching device, or a merging support device according to an embodiment of the present disclosure.

Each embodiment of the present disclosure will be described below with reference to the drawings. The same or corresponding configurations in all drawings will be given the same reference numerals, and common descriptions will be omitted.

First Embodiment
A shape discrimination device according to an embodiment will be described with reference to the drawings.
(Overall configuration of the merging support system)
The merging assistance system 100 is a system for assisting a vehicle traveling on a merging road RM that merges with a road RR with driving operations in the merging section with the road RR depending on the situation of the vehicle traveling on the road RR.

For example, the road RR may have multiple lanes LL on one side.

For example, road RR may be a main road such as a highway.

For example, the merging road RM may be a ramp that merges with a main road such as an expressway.

As shown in FIG. 1, the merging support system 100 includes a merging support device 1, a first sensor 2A, a second sensor 2B, a roadside radio 3, and an on-board device VMa mounted on a vehicle traveling on a merging road RM.

In the following description, a vehicle traveling on road RR will be referred to as "vehicle VV", and a vehicle traveling on merging road RM will be referred to as "merging vehicle VM".

In Figure 1, each vehicle is traveling in the direction indicated by the arrow.

For example, the merging vehicle VM in this embodiment may be an autonomous vehicle.

Hereinafter, the direction in which the road RR extends and in which each vehicle travels will also be referred to as the X direction.

The width direction of the road RR, which is the direction from the road RR toward the merging road RM, is also referred to as the Y direction. Note that the Y direction and the direction opposite to the Y direction are also the vehicle width direction.

Furthermore, the direction above road RR and facing upward from road RR is also referred to as the Z direction.

(Configuration of the merging support device)

As shown in FIG. 2, the merging support device 1 includes a shape discrimination device 11 and a support information generation unit 12.

The merging assistance device 1 is communicatively connected to the first sensor 2A and the second sensor 2B via a dedicated communication line or a public communication line.

The merging support device 1 is connected to the roadside radio 3 via a dedicated communication line or a public communication line so that they can communicate with each other.

For example, the merging support device 1 may be installed on road RR, which is a main road of a road (such as an expressway), near a merging section where merging road RM merges, or may be set up in a remote location away from the merging section.

For example, a computer may function as the merging support device 1 by executing a program described below.

(Configuration of the shape discrimination device)

The shape discrimination device 11 includes a first acquisition unit 111, a second acquisition unit 112, a first calculation unit 113, a second calculation unit 114, and a complementation unit 116. The shape discrimination device 11 may further include a third calculation unit 115.

For example, a computer may function as the shape discrimination device 11 by executing a program described below.

The first acquisition unit 111 acquires first detection information D1 from a first sensor 2A that detects a vehicle VV traveling on a lane LL from a first direction. The first sensor 2A is, for example, an area sensor that performs detection within a two-dimensional range. The first direction is, for example, the X direction.

For example, the detection information D1 may include image data of a specific area AA of a road RR that includes multiple vehicles VV.

The second acquisition unit 112 acquires second detection information D2 from a second sensor 2B that detects the vehicle VV traveling on the lane LL from a second direction. The second sensor 2B is, for example, a line sensor that performs detection within a one-dimensional range. The second direction is, for example, the opposite direction to the Y direction (the direction from the merging road RM toward the road RR). In the following description, the opposite direction to the Y direction may be expressed as the Y' direction.

For example, the detection information D2 may include image data of a specific area AA of a road RR that includes multiple vehicles VV.

For example, the first acquisition unit 111 and the second acquisition unit 112 may assign the same vehicle ID (an identifier for uniquely identifying a vehicle) to vehicles VV that can be identified by matching the detection information D1 and the detection information D2. In this case, the vehicle ID assigned to the vehicle is shared by the first calculation unit 113, the second calculation unit 114, and the complementation unit 116. Vehicles that can be identified are, for example, vehicles that are determined to be in the same position or approximately the same position on the road RR in the detection information D1 and the detection information D2.

The first calculation unit 113 calculates a first parameter P1 including at least one of the vehicle height, vehicle length, and vehicle width based on the first detection information D1.

An example of calculation by the first calculation unit 113 will be described. FIG. 3A is a diagram showing an example of the first detection information D1 acquired from the first sensor 2A. The image shown in FIG. 3A is an image captured from the upstream direction toward the downstream direction. The horizontal axis of the graph indicates the length in the vehicle width direction (approximately the Y' direction), and the vertical axis indicates the length in the height direction (approximately the Z direction). The "distance display" indicates the distance from the first sensor 2A to the subject. The darker the color, the longer the distance from the first sensor 2A to the subject. In FIG. 3A, the rear view of the vehicle is captured in the area surrounded by the dashed line.

Figure 3B is a diagram showing an image obtained by the first calculation unit 113 performing coordinate conversion on the image of the first detection information D1 shown in Figure 3A. The horizontal axis of the graph indicates the length in the Y' direction, and the vertical axis indicates the length in the Z direction. Thus, the image shown in Figure 3B is an image seen from directly behind the vehicle. The first calculation unit 113 calculates the vehicle width and height from this image.

Figure 3C is a diagram showing an image obtained by the first calculation unit 113 performing coordinate conversion on the image of the first detection information D1 shown in Figure 3A. The horizontal axis of the graph indicates the length in the X direction, and the vertical axis indicates the length in the Z direction. Thus, the image shown in Figure 3C is an image seen from directly to the side of the vehicle. However, because the image is unclear, it is difficult for the first calculation unit 113 to calculate the vehicle length and vehicle height. From the above, the first calculation unit 113 in this embodiment can calculate the vehicle width and vehicle height as the first parameter P1.

Returning to the explanation of FIG. 2, the second calculation unit 114 calculates a second parameter P2 including at least one of the vehicle height, vehicle length, and vehicle width based on the second detection information D2.

As described above, the second detection information D2 is acquired from the second sensor 2B. For example, as shown in FIG. 4, the second sensor 2B detects each vehicle VV traveling from the side of the road RR at point A1 as if they are crossing the road.

For example, the second sensor 2B may include a laser scanner 2B1 and a laser scanner 2B2 that emit a laser from the roadside of the road RR so as to cross each vehicle traveling. In this case, the laser scanner 2B1 and the laser scanner 2B2 that scan the laser in the height direction may be installed near the point A1 at a predetermined sensor interval upstream and downstream in the X direction.

For example, each of the laser scanners 2B1 and 2B2 may scan a laser in a plane perpendicular to the X direction.

For example, each of the laser scanners, laser scanner 2B1 and laser scanner 2B2, may be installed on the side of road RR at approximately the same height as each of the vehicles VV. In this case, each of the laser scanners, laser scanner 2B1 and laser scanner 2B2, may scan with a laser centered on the horizontal direction within a plane perpendicular to the X direction.

For example, each of the laser scanners, laser scanner 2B1 and laser scanner 2B2, may be capable of measuring the distance to each vehicle.

For example, the second sensor 2B may acquire detection information D2 for each vehicle VV that enables the second calculation unit 114 to calculate the vehicle distance, vehicle height, vehicle length, etc. From the above, the second calculation unit 114 in this embodiment can calculate the vehicle length and vehicle height as the second parameter P2.

The complementing unit 116 complements the first parameter P1 based on the second parameter P2. The parameter complemented by the complementing unit 116 is called a complemented parameter CP. For each vehicle to which a vehicle ID has been assigned by matching the above-mentioned first detection information and second detection information, the complementing unit 116 complements the first parameter P1 based on the second parameter P2.

For example, in this embodiment, the vehicle width and vehicle height are calculated as the first parameter P1, and the vehicle length and vehicle height are calculated as the second parameter P2. The complementing unit 116 complements the vehicle length as the second parameter P2 to the first parameter for each vehicle ID, thereby obtaining the vehicle width, vehicle height, and vehicle length of each vehicle as the parameters CP. This allows the shape discrimination device 11 to discriminate the shape of the vehicle (vehicle width, vehicle height, vehicle length).

The vehicle height is included in both the first parameter P1 and the second parameter P2. Therefore, the complementing unit 116 may use either the vehicle height of the first parameter P1 or the vehicle height of the second parameter P2, or may use the average value (or weighted average value) of the vehicle height of the first parameter P1 and the vehicle height of the second parameter P2 as the vehicle height.

The third calculation unit 115 calculates the speed or vehicle distance of the vehicle VV traveling in the lane as a third parameter P3 based on the first detection information D1 or the second detection information D2.

For example, the third calculation unit 115 may use the detection information D2 to obtain the orientation vector, acceleration, and vehicle speed of each vehicle VV from the distance between the vehicle VV and each laser scanner, the distance between the two laser scanners, and the time difference between the times when each laser scanner detects the traveling vehicle VV.

(Configuration of the support information generating unit)
The assistance information generating unit 12 generates merging assistance information DA based on the vehicle speed or the vehicle-to-vehicle distance calculated by the third calculating unit 115 .

For example, the assistance information generating unit 12 may create information on the speed or distance between vehicles approaching the merging section and include this in the merging assistance information DA.

For example, the assistance information generating unit 12 may include information including the shape of the vehicle obtained by the complementing unit 116 in the merging assistance information DA.

(Configuration of first sensor 2A)

The first sensor 2A detects a vehicle VV traveling on the road RR.

For example, the first sensor 2A may capture an image looking down on a specific area AA of the road RR and acquire detection information D1 from the specific area AA of the road RR that includes multiple vehicles VV.

For example, the first sensor 2A may be set so that the specified area AA is an area that contains multiple vehicles VV traveling on the road RR in the X direction.

For example, the first sensor 2A may be set so that the specified area AA is an area that contains multiple lanes LL in the Y direction.

For example, the first sensor 2A may repeatedly capture images at a predetermined time and obtain multiple pieces of detection information D1 at different times.

For example, the first sensor 2A may include an area sensor such as a LiDAR (Light Detection and Ranging) or a camera.

For example, the first sensor 2A may provide the acquired detection information D1 to the merging assistance device 1 via a communication line.

(Configuration of roadside wireless device)
The roadside wireless device 3 may acquire the merging assistance information DA from the merging assistance device 1 via a communication line.

For example, the roadside radio 3 may transmit the acquired merging assistance information DA to an on-board device VMa mounted on a merging vehicle VM traveling on the merging road RM, thereby notifying the driver, etc.

For example, the roadside wireless device and the vehicle-mounted device VMa may perform wireless communication based on Dedicated Short Range Communications (DSRC) technology.

For example, the roadside radio 3 may transmit the merging support information DA to the vehicle-mounted device VMa mounted on the merging vehicle VM, or may transmit the information to a display board or the like set up on the roadside, and notify the merging vehicle VM traveling on the merging road RM of the merging support information DA by display or sound via a display board, speaker, or the like.

(motion)
The operation of the shape discrimination device 11 of this embodiment will be described below. Fig. 5 is a flowchart showing the flow of processing of the shape discrimination device 11. The operation of the shape discrimination device 11 corresponds to the shape discrimination method of this embodiment.

The first acquisition unit 111 acquires first detection information D1 from the first sensor 2A (ST01). At this time, the first acquisition unit 111 may assign a vehicle ID to each vehicle in the acquired first detection information D1. In this case, the first acquisition unit 111 outputs the vehicle ID and the position on road RR to the second acquisition unit 112. In addition, the first acquisition unit 111 outputs the first detection information D1 and the vehicle ID to the first calculation unit 113.

The second acquisition unit 112 acquires the second detection information D2 from the second sensor 2B (ST02). At this time, the second acquisition unit 112 may assign the vehicle ID output by the first acquisition unit 111 based on the position of each vehicle in the acquired second detection information D1. In this case, the second acquisition unit 112 outputs the second detection information D2 and the vehicle ID to the second calculation unit 114.

The first calculation unit 113 calculates a first parameter P1 including at least one of the vehicle height, vehicle length, and vehicle width based on the first detection information D1 for each vehicle ID (ST03). The second calculation unit 114 calculates a second parameter P2 including at least one of the vehicle height, vehicle length, and vehicle width based on the second detection information D2 for each vehicle ID (ST04). The complementation unit 116 complements the first parameter P1 based on the second parameter P2 for each vehicle ID (ST05).

In this embodiment, the complementing unit 116 complements the first parameter with the vehicle length as the second parameter P2, but this is not limited to the above. For example, if the vehicle height is included in both the first parameter P1 and the second parameter P2, the vehicle height that is considered to have better accuracy may be used. In addition, an average value (including a weighted average value) may be calculated and used.

(Action and Effects)
According to this embodiment, the complementing unit 116 of the shape discrimination device 11 complements the first parameter based on the second parameter.

Therefore, the shape discrimination device 11 complements the first parameter P1 calculated from the first detection information D1 detected from a different direction based on the second parameter P2 calculated from the second detection information D2, thereby enabling the shape of the vehicle VV to be discriminated with greater accuracy.

In this embodiment, the first sensor 2A is an area sensor.

As a result, the shape discrimination device 11 can detect the entire vehicle VV in the area that can be sensed by the first sensor 2A.

In this embodiment, the second direction is the vehicle width direction of the vehicle VV.

Therefore, the shape discrimination device 11 can acquire second detection information D2 of the side of the vehicle VV. This allows the shape discrimination device 11 to discriminate the shape of the vehicle VV as viewed from the side.

According to this embodiment, the complementing unit 116 complements the first parameter P1 based on the second parameter P2 for each vehicle VV to which a vehicle ID has been assigned by matching the first detection information D1 and the second detection information D2.

This allows the shape discrimination device 11 to discern the shape of each vehicle that has been assigned a vehicle ID.

According to this embodiment, the shape discrimination device 11 is equipped with a third calculation unit 115 that calculates the speed or inter-vehicle distance of a vehicle traveling in a lane based on the first detection information D1 or the second detection information D2.

Therefore, the shape discrimination device 11 can calculate not only the shape of the vehicle VV, but also the speed or inter-vehicle distance of the vehicle VV.

According to this embodiment, the merging support device 1 includes a support information generating unit 12 that generates merging support information DA based on the vehicle speed or vehicle-to-vehicle distance calculated by the third calculation unit 115. This allows the merging support device 1 to generate more detailed support information.

(Modification)
In the above embodiment, the second sensor 2B is a line sensor, but may be an area sensor. In this case, as shown in Fig. 6, the merging support system 100 includes the merging support device 1, the first sensor 2A, the second sensor 2C, the roadside wireless device 3, and an on-board device VMa mounted on a vehicle traveling on the merging road RM.

By using the second sensor 2C as an area sensor, more information can be obtained compared to a line sensor, and the shape discrimination device 11 can discriminate the shape more accurately compared to when the shape is discriminated using a line sensor.

By the shape discrimination device 11 discriminating shapes more accurately, the accuracy of the support information generated by the support information generation unit 12 can be improved.

In the above embodiment, the parameters to be complemented by the complementing unit 116 are, for example, vehicle height, vehicle length, and vehicle width, but are not limited to these and may be other parameters related to the shape of the vehicle.

The following describes how the parameters calculated by both the first calculation unit 113 and the second calculation unit 114 are handled. Among the parameters calculated by both the first calculation unit 113 and the second calculation unit 114, the parameter calculated by the first calculation unit 113 is designated as p1, and the parameter calculated by the second calculation unit 114 is designated as p2.

In the above embodiment, either p1 or p2, or the average value (or weighted average value) is used, but the weighted average value will be specifically described. For example, if the parameter calculated by the first calculation unit 113 is more accurate than the parameter calculated by the second calculation unit 114, the complemented parameter is set to s×p1+t×p2, (s+t=1, 0<t<s). In this way, by increasing the weight of the parameter considered to be more accurate, more accurate complementation can be achieved using the two values calculated by the first calculation unit 113 and the second calculation unit 114.

In the first embodiment, the first sensor 2A and the second sensor 2B (2C) are installed so that the area sensed by the first sensor 2A and the area sensed by the second sensor 2B (2C) overlap, but this is not limited to this.

For example, the area sensed by the first sensor 2A and the area sensed by the second sensor 2B (2C) may be shifted in the X direction without overlapping. In this case, each vehicle is tracked, but as described in the second embodiment, the vehicle travel trajectory may be interrupted. At that time, tracking becomes possible by complementing the vehicle travel trajectory using the matching method shown in the second embodiment. By making tracking possible, it is possible to determine whether or not it is the same vehicle based on the vehicle ID, and the shape can also be determined by the first sensor 2A and the second sensor 2B (2C) which sense different areas.

Second Embodiment
(Overall configuration of the merging support system)
The merging assistance system 700 is a system for assisting a vehicle traveling on a merging road RM that merges with a road RR with driving operations in the merging section with the road RR depending on the situation of the vehicle traveling on the road RR.

For example, the road RR may have multiple lanes LL on one side.

For example, road RR may be a main road such as a highway.

For example, the merging road RM may be a ramp that merges with a main road such as an expressway.

As shown in FIG. 7, the merging support system 700 includes a merging support device 701, an area sensor 702, a roadside radio 703, and an on-board device VMa mounted on a vehicle traveling on a merging road RM.

In the following description, a vehicle traveling on road RR will be referred to as "vehicle VV", and a vehicle traveling on merging road RM will be referred to as "merging vehicle VM".

In Figure 7, each vehicle is traveling in the direction indicated by the arrow.

For example, the merging vehicle VM in this embodiment may be an autonomous vehicle.

Hereinafter, the direction in which the road RR extends and in which each vehicle travels will also be referred to as the X direction.

The width direction of road RR, which is the direction from road RR to merging road RM, is also referred to as the Y direction. In the following explanation, the opposite direction of the Y direction (the direction from merging road RM to road RR) may be referred to as the Y' direction.

Furthermore, the direction above road RR and facing upward from road RR is also referred to as the Z direction.

(Configuration of the merging support device)
As shown in FIG. 8, the merging support device 701 includes a matching device 711 and a support information generating unit 712 .

The merging support device 701 is communicatively connected to the area sensor 702 via a dedicated communication line or a public communication line.

The merging support device 701 is connected to the roadside radio 703 via a dedicated communication line or a public communication line so that they can communicate with each other.

For example, the merging support device 701 may be installed on road RR, which is a main road of a road (such as an expressway), near a merging section where merging road RM merges, or may be set up in a remote location away from the merging section.

For example, a computer may function as a merging support device 701 by executing a program described below.

(Configuration of the matching device)
The matching device 711 includes an acquisition unit 811 , a complementation unit 812 , and a determination unit 813 .

For example, a computer may function as a matching device 711 by executing a program described below.

The acquisition unit 111 acquires the first tracking data TD1 and the second tracking data TD2 obtained from the area sensor 702. The first tracking data TD1 and the second tracking data TD2 are composed of a vehicle ID (an identifier for uniquely identifying a vehicle) and vehicle information indicating the position of the vehicle, the speed of the vehicle, the acceleration of the vehicle, or the direction of movement of the vehicle. For example, the first tracking data TD1 and the second tracking data TD2 are acquired from image data of a specific area AA of a road RR that includes multiple vehicles VV. When there is no particular distinction between the first tracking data TD1 and the second tracking data TD2, they are simply referred to as tracking data.

The complementing unit 812 complements the first tracking data TD1 using the vehicle information CD. The complementing method of the complementing unit 812 is explained below.

First, when vehicles overlap and become hidden, the area sensor 702 may not be able to detect the hidden vehicle. Figure 9 is a diagram showing how a vehicle becomes hidden in the X direction. In Figure 9, the right direction indicates the X direction (the direction in which the vehicle travels), and the vertical direction indicates the Z direction. As shown in Figure 9, if vehicle A is, for example, a large vehicle, it will hide vehicle B traveling in front of it from the area sensor 702.

For example, if the height of the area sensor 702 is 8 m, the height of vehicle A is 3.8 m, and the height of vehicle B is 1.5 m, vehicle A will hide vehicle B when the distance D from the area sensor 702 shown in FIG. 9 is 5.1 m or more. Similarly, if the height of the area sensor 702 is 8 m, the height of vehicle A is 3 m, and the height of vehicle B is 1.5 m, vehicle A will hide vehicle B when the distance D from the area sensor 702 shown in FIG. 9 is 30 m or more.

If the height of the area sensor 702 is reduced to 5 m, and if the height of vehicle A is 3.8 m and the height of vehicle B is 1.5 m, vehicle A will hide vehicle B when the distance D from the area sensor 702 shown in FIG. 9 is 3.9 m or more. Similarly, if the height of the area sensor 702 is 5 m, the height of vehicle A is 3 m, and the height of vehicle B is 1.5 m, vehicle A will hide vehicle B when the distance D from the area sensor 702 shown in FIG. 9 is 12 m or more.

Thus, the lower the height of the area sensor 702 and the higher the height of vehicle A, the shorter the distance D at which vehicle A hides vehicle B.

Vehicles may be hidden not only in the X direction but also in the Y' direction by overlapping each other. Figure 10A is a diagram showing an example of occlusion when the height of the area sensor 702 is 8 m, the height of vehicle A is 3.8 m, and the height of vehicle B is 1.5 m. In the example shown in Figure 10A, vehicle A does not entirely hide vehicle B, so the area sensor 702 can detect vehicle B.

Figure 10B is a diagram showing an example of occlusion when the height of the area sensor 702 is 5 m, the height of vehicle A is 3.8 m, and the height of vehicle B is 1.5 m. In the example shown in Figure 10B, vehicle A hides vehicle B.

Figure 10C is a diagram showing an example of occlusion when the height of the area sensor 702 is 5 m, the height of vehicle A is 3.0 m, and the height of vehicle B is 1.5 m. In the example shown in Figure 10C, vehicle A hides vehicle B. In this way, even if the height of vehicle A is 3.0 m, vehicle A will hide vehicle B if the height of the area sensor 702 is low.

In this way, when a vehicle hides another vehicle, it cannot be detected by the area sensor 702, and the vehicle travel trajectory is interrupted. Figures 11A and 11B are diagrams showing an example of a vehicle travel trajectory. Figures 11A and 11B are diagrams showing a vehicle travel trajectory when the time and the vehicle position at that time are used as vehicle information.

The horizontal axis of the graphs shown in Figures 11A and 11B indicates time, and the vertical axis indicates position. Position here refers to the distance from the area sensor 702. Also, Figures 11A and 11B show the vehicle travel trajectories of vehicles with vehicle IDs L1, L2, L3, L4, and L5. In the following explanation, for simplicity, a vehicle with vehicle ID L1 may be referred to simply as L1. The same applies to vehicle IDs L2, L3, L4, and L5. Also, L3 is assumed to be a large vehicle. Furthermore, each vehicle is assumed to be moving at a uniform speed.

In FIG. 11A, the first vehicle detected by the area sensor 702 is L1. Next, L2 is detected, and then L3 is detected. Thereafter, at time t1 and position d1, the area sensor 702 is no longer able to detect L1, and the vehicle travel path is interrupted. The point at which the path is interrupted is designated as P1. Next, at time t2 and position d2, the area sensor 702 is no longer able to detect L2, and the vehicle travel path is interrupted. The point at which the path is interrupted is designated as P2.

After that, at time t4 and position d4, the area sensor 702 detects L4. The detected point is designated as P4. Next, at time t5 and position d5, the area sensor 702 detects L5. The detected point is designated as P5.

As shown in FIG. 11A, L4 and L5 may be L1 and L2 that were hidden by L3. For example, L1 and L2 may have been detected again due to a lane change. The complementation unit 812 then generates a linear function (d-d1=m1(t-t1)...function LL1) that uses the vehicle speed m1 of L1 at point P1 as the slope and indicates a straight line passing through point P1. The complementation unit 812 substitutes t4 for t in function (1) and calculates the position d4' at t4. This (m1, d4') is generated as the complemented first tracking data corresponding to L1.

Similarly, for L2, the complement unit 812 uses the vehicle speed m2 of L2 at point P2 as the slope and generates a linear function for time t that indicates a straight line passing through point P2 (d-d2=m1(t-t2)...function LL2). The complement unit 812 substitutes t5 for t in function LL2 and calculates the position d5' at t5. This (m2, d5') is generated as the complemented first tracking data corresponding to L2.

Figure 11B is a diagram in which functions LL1 and LL2 are shown by dashed lines in Figure 11A. The determination unit 813 compares the complemented first tracking data TD1 and second tracking data TD2, and determines whether the first tracking data TD1 and the second tracking data TD2 are data belonging to the same vehicle.

The determination unit 813 obtains the vehicle speed m4 and position d4 of L4 at P4 from the second tracking data TD2. Similarly, the determination unit 813 obtains the vehicle speed m5 and position d5 of L5 at P5 from the second tracking data TD2.

The determination unit 813 first determines whether or not the matching condition (|m1-m4|≦prescribed value M, and |d4'-d4|≦prescribed value D) is satisfied for L1. Similarly, the determination unit 813 determines whether or not the matching condition (|m2-m5|≦prescribed value M, and |d5'-d5|≦prescribed value D) is satisfied for L2. In other words, the matching condition is a condition in which the absolute value of the difference in speed is equal to or less than the prescribed value M, and the absolute value of the difference in position is equal to or less than the prescribed value D. Therefore, this matching condition is a condition for determining whether the vehicle that became the first tracking data TD1 is likely to be the vehicle that became the second tracking data TD2. The determination of whether or not this matching condition is satisfied is the likelihood determination.

If the matching condition is satisfied, the determination unit 813 determines that the first tracking data and the second tracking data belong to the same vehicle. If it is determined that the data belong to the same vehicle, L4 is updated to L1, and L5 is updated to L2. In other words, L1 and L4, and L2 and L5 have the same vehicle ID.

By doing this, the vehicle can be tracked with high accuracy. If the vehicle cannot be tracked in this way, L1 and L4, and L2 and L5 will be considered as different vehicles. In this case, there will be five vehicles, and the merging assistance information will be inaccurate.

(Configuration of the support information generating unit)
The assistance information generating unit 712 generates merging assistance information DA based on the result of the determination by the determining unit 813 .

For example, the assistance information generating unit 712 may create information on the speed of a vehicle approaching a merging section whose vehicle ID has been updated based on the determination result by the determining unit 813, and include this information in the merging assistance information DA.

(Configuration of area sensor 702)
The area sensor 702 detects a vehicle VV traveling on a road RR.

For example, the area sensor 702 may capture an image overlooking a specific area AA of the road RR and acquire first tracking data TD1 and second tracking data TD2 from the specific area AA of the road RR that includes multiple vehicles VV.

For example, the area sensor 702 may be set so that the specified area AA is an area that contains multiple vehicles VV traveling on the road RR in the X direction.

For example, the area sensor 702 may be set so that the specified area AA is an area that contains multiple lanes LL in the Y' direction.

For example, the area sensor 702 may repeatedly capture images at a predetermined time and obtain multiple pieces of detection information D1 at different times.

For example, the area sensor 702 may include an area sensor such as a LiDAR (Light Detection and Ranging) or a camera.

For example, the area sensor 702 may provide the acquired first tracking data TD1 and second tracking data TD2 to the merging assistance device 701 via a communication line.

(Configuration of roadside wireless device)
The roadside wireless device 703 may acquire the merging assistance information DA from the merging assistance device 701 via a communication line.

For example, the roadside wireless device 703 may transmit the acquired merging assistance information DA to an on-board device VMa mounted on a merging vehicle VM traveling on the merging road RM, thereby notifying the driver, etc.

For example, the roadside wireless device and the vehicle-mounted device VMa may perform wireless communication based on Dedicated Short Range Communications (DSRC) technology.

For example, the roadside radio 703 may transmit the merging assistance information DA to an on-board device VMa mounted on the merging vehicle VM, or may transmit the information to a display board or the like set up on the roadside, and notify the merging vehicle VM traveling on the merging road RM of the merging assistance information DA by display or voice via a display board, speaker, or the like.

(motion)
The operation of the matching device 711 of this embodiment will be described below. Fig. 12 is a flowchart showing the flow of processing of the matching device 711. The operation of the matching device 711 corresponds to the matching method of this embodiment.

The acquisition unit 111 acquires first tracking data TD1 (ST11). To explain using L1 above, the acquisition unit 111 acquires L1, which is a vehicle ID, vehicle speed m1, and position d1. Next, the acquisition unit 111 acquires second tracking data TD2 (ST12). To explain using L1 above, the acquisition unit 111 acquires L4, which is a vehicle ID, vehicle speed m4, and position d4.

The complementing unit 812 generates the position and vehicle speed as complemented data (ST13). Using the above L1, the complementing unit 812 generates (m1, d4'). The determining unit 813 determines whether or not the matching condition is satisfied (ST14). Using the above L1, the determining unit 813 determines whether or not L1 satisfies the matching condition (|m1-m4|≦prescribed value M, and |d4'-d4|≦prescribed value D).

If the matching conditions are met by the determination unit 813 (ST14: YES), the matching device 711 updates the vehicle ID to the same vehicle ID (ST15) and ends the process. If the matching conditions are not met, the matching device 711 determines that the vehicles are different and ends the process.

In the above explanation, it is assumed that the vehicle is moving at a constant speed, but it may be accelerating. In this case, the vehicle acceleration is used as the vehicle information. For example, the acceleration at point PA1 where the vehicle travel trajectory is interrupted is set to a1, and the position is set to da1. In this case, the complementing unit 812 generates a quadratic function d = a1 x t^2 + da1 for time t. Then, using the time ta when it is detected again, the complementing unit 812 sets da1' = a1 x (ta)^2 + da1. The determining unit 813 also obtains the acceleration a2 and the position da2 at PA2 when it is detected again.

The determination unit 813 determines whether the matching condition (|a1-a2|≦prescribed value A, and |da1'-da2|≦prescribed value D) is satisfied. In this case, the matching condition is that the absolute value of the difference in acceleration is equal to or less than prescribed value A, and the absolute value of the difference in position is equal to or less than prescribed value D. In this way, the vehicle travel trajectory can be complemented even if the vehicle travel trajectory is interrupted while the vehicle is accelerating.

In addition to the speed and acceleration described above, the vehicle's moving direction may be used as vehicle information. An orientation vector is used as the vehicle's moving direction. The orientation vector is a vector that indicates the vehicle's traveling direction. In the following description, the angle of the orientation vector refers to the angle between the orientation vector and the X direction.

For example, the complement unit 812 calculates the angle θ1 from the orientation vector at the point PG1 where the vehicle travel trajectory is interrupted. The complement unit 812 then calculates the angle θ2 from the orientation vector when it is detected again. The determination unit 813 also acquires the angles θ1 and θ2. The determination unit 813 determines whether or not the matching condition (|θ1-θ2|≦prescribed value G) is satisfied. In this case, the matching condition is that the absolute value of the difference between the angles is equal to or less than the prescribed value G, and the absolute value of the difference between the angles is equal to or less than the prescribed value G. In this way, even if the vehicle travel trajectory is interrupted while the vehicle is accelerating, the vehicle travel trajectory can be complemented. Note that the determination unit 813 may also use the above-mentioned speed and acceleration in addition to the angle. The vehicle travel trajectory can be complemented more accurately by using the speed and acceleration in addition to the angle.

(Action and Effects)
According to this embodiment, the determination unit 813 of the matching device 711 compares the complemented first tracking data and second tracking data, and determines whether the first tracking data and the second tracking data belong to the same vehicle.

Conventionally, if a vehicle for which tracking data had been acquired was obscured by another vehicle and the tracking data could no longer be acquired, and then tracking data was acquired again, the former tracking data and the latter tracking data were treated as tracking data belonging to different vehicles. In contrast, the matching device 711 disclosed herein compares the complemented first tracking data and second tracking data, and determines whether the first tracking data and the second tracking data belong to the same vehicle. This makes it possible to complement the vehicle driving trajectory when it is determined that the first tracking data and the second tracking data belong to the same vehicle.

According to this embodiment, the first tracking data and the second tracking data are composed of a vehicle ID for uniquely identifying the vehicle, and vehicle information indicating the position of the vehicle, the speed of the vehicle, the acceleration of the vehicle, or the direction of movement of the vehicle.

Since the determination is made using the vehicle ID and vehicle information indicating the vehicle's position (e.g., d2), the vehicle's speed (e.g., m1), the vehicle's acceleration (e.g., a1), or the vehicle's moving direction (e.g., heading vector), it is possible to accurately determine whether the first tracking data and the second tracking data belong to the same vehicle.

According to this embodiment, the complementing unit 812 complements based on the vehicle information included in the first tracking data.

To explain using L1 above, the complementing unit 812 generates (m1, d4') based on the vehicle information included in the first tracking data. This allows the determining unit 813 to make a more accurate determination.

According to this embodiment, the determination unit 813 performs a likelihood determination between the complemented first tracking data and the second tracking data to determine whether the data belong to the same vehicle.

The matching condition used in the likelihood determination is that the absolute value of the difference in speed is equal to or less than a specified value M, and that the absolute value of the difference in position is equal to or less than a specified value D. Another matching condition is that the absolute value of the difference in acceleration is equal to or less than a specified value A, and that the absolute value of the difference in position is equal to or less than a specified value D. Another matching condition is that the absolute value of the difference in the formed angle is equal to or less than a specified value G, and that the absolute value of the difference in the formed angle is equal to or less than a specified value G. Another matching condition is that the absolute value of the difference in the vehicle height is equal to or less than a specified value H, that the absolute value of the difference in the vehicle length is equal to or less than a specified value L, and that the absolute value of the difference in the vehicle width is equal to or less than a specified value W. This allows the determination unit 813 to more accurately determine whether the first tracking data and the second tracking data belong to the same vehicle. Also, by changing the specified value, the likelihood can also be changed.

According to this embodiment, if the determination unit 813 determines that the data belongs to the same vehicle, the vehicle ID included in the first tracking data and the vehicle ID included in the second tracking data are determined to be the same vehicle ID.

This allows the matching device 711 to complement the vehicle travel trajectory. With this complementation, for example, in the vehicle travel trajectory of FIG. 11A, while the conventional technology would indicate that there are five vehicles, it is possible to obtain accurate information that there are three vehicles.

According to this embodiment, the merging support device 701 includes a matching device 711 and a support information generating unit 712 that generates merging support information based on the determination result by the determining unit 813. This allows the merging support device 701 to generate support information that includes the complemented vehicle traffic trajectory.

(Modification)
Each of the above-mentioned specified values may change according to time. For example, even a vehicle traveling at a constant speed may accelerate (or decelerate (including acceleration with negative acceleration)). In that case, the speed changes, but the degree of change in speed depends not only on the vehicle's performance but also on time. Therefore, each specified value may be proportional to the elapsed time from the point at which the vehicle travel trajectory is interrupted to the point at which the determination is made by the determination unit 813. In other words, the shorter the elapsed time, the smaller each specified value may be, and the longer the time until the point at which the determination is made, the larger each specified value may be. This makes it possible to complement the vehicle travel trajectory with greater accuracy.

The likelihood determination in the above description is a determination using the speed, acceleration, or traveling direction of the vehicle, but is not limited to this. For example, the vehicle height, length, and width calculated in the first embodiment may be used. In this case, the configuration of the merging support system 700 is the same as that of the merging support system 100 in the first embodiment. That is, in addition to the area sensor 702, a second sensor 2B is provided. As described above, the second sensor 2B is, for example, a line sensor or an area sensor.

For example, the determination unit 813 stores the vehicle height h, vehicle length l, and vehicle width w of the vehicle with the vehicle ID where the vehicle travel trajectory is interrupted. After that, the determination unit 813 obtains the vehicle height h', vehicle length l', and vehicle width w' calculated for the vehicle with the vehicle ID.

The determination unit 813 determines whether the matching condition (|h-h'|≦prescribed value H, and |l-l'|≦prescribed value L, and |w-w'|≦prescribed value W) is satisfied. In this case, the matching condition is that the absolute value of the difference in vehicle height is equal to or less than prescribed value H, the absolute value of the difference in vehicle length is equal to or less than prescribed value L, and the absolute value of the difference in vehicle width is equal to or less than prescribed value W. In this way, the vehicle travel trajectory can be complemented without using the speed, acceleration, or traveling direction of the vehicle.

(Computer Configuration)
In the above-mentioned embodiments, a program for realizing the functions of the merging support device 1, 701, the shape discrimination device 11, or the matching device 711 is recorded in a computer-readable recording medium, and the program recorded in the recording medium is read into a computer system such as a microcomputer and executed to perform various processes. Here, the various processes of the CPU of the computer system are stored in the form of a program in a computer-readable recording medium, and the computer reads and executes the program to perform the various processes. In addition, the computer-readable recording medium refers to a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory, etc. In addition, the computer program may be distributed to a computer via a communication line, and the computer that receives the program may execute the program.

In each of the above-mentioned embodiments, an example of the hardware configuration of a computer that executes a program to realize the functions of the merging support device 1, 701, the shape discrimination device 11, or the matching device 711 will be described.

As shown in FIG. 13, the computer included in the merging support device 1, 701, shape discrimination device 11, or matching device 711 includes a CPU 91, a memory 92, a storage/playback device 93, an Input Output Interface (hereinafter referred to as "IO I/F") 94, and a communication interface (hereinafter referred to as "communication I/F") 95.

The memory 92 is a medium such as a Random Access Memory (hereinafter referred to as "RAM") that temporarily stores data used in the programs executed by the merging support device 1, 701, the shape discrimination device 11, or the matching device 711.

The storage/playback device 93 is a device for storing data, etc. on external media such as CD-ROMs, DVDs, and flash memories, and for playing back data, etc. from external media.

The IO I/F 94 is an interface for inputting and outputting information between the merging support device 1, 701 and other devices, or between the shape discrimination device 11, the matching device 711 and other devices.

The communication I/F 95 is an interface that communicates with other devices via a communication line such as the Internet or a dedicated communication line.

Although several embodiments of the present disclosure have been described above, these embodiments are presented as examples and are not intended to limit the scope of the disclosure. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the disclosure. These embodiments and their modifications are considered to be within the scope of the claims and their equivalents, as well as within the scope and gist of the disclosure.

<Additional Notes>
The shape discrimination device, the merging support device, the shape discrimination method, and the program described in the first embodiment can be understood, for example, as follows.

(1) The shape discrimination device 11 according to the first aspect includes a first acquisition unit 111 that acquires first detection information D1 from a first sensor 2A that detects a vehicle VV traveling on a lane LL from a first direction, a second acquisition unit 112 that acquires second detection information D2 from a second sensor 2B that detects the vehicle VV from a second direction different from the first direction, a first calculation unit 113 that calculates a first parameter P1 including at least one of vehicle height, vehicle length, and vehicle width based on the first detection information D1, a second calculation unit 114 that calculates a second parameter P2 including at least one of vehicle height, vehicle length, and vehicle width based on the second detection information D2, and a complementation unit 116 that complements the first parameter P1 based on the second parameter P2.

According to this embodiment, the complementing unit 116 of the shape discrimination device 11 complements the first parameter based on the second parameter.

Therefore, the shape discrimination device 11 complements the first parameter P1 calculated from the first detection information D1 detected from a different direction based on the second parameter P2 calculated from the second detection information D2, thereby enabling the shape of the vehicle VV to be discriminated with greater accuracy.

(2) The shape discrimination device 11 according to the second aspect is the shape discrimination device 11 of (1), in which the first sensor 2A is an area sensor.

According to this embodiment, the shape discrimination device 11 can detect the entire vehicle VV within the sensing range of the first sensor 2A.

(3) The shape discrimination device 11 according to the third aspect is the shape discrimination device 11 according to (1) or (2), and the second direction is the vehicle width direction of the vehicle VV.

Therefore, the shape discrimination device 11 can acquire second detection information D2 of the side of the vehicle VV. This allows the shape discrimination device 11 to discriminate the shape of the vehicle VV as viewed from the side.

(4) The shape discrimination device 11 according to the fourth aspect is any one of the shape discrimination devices 11 according to (1) to (3), and the complementing unit complements the first parameter P1 based on the second parameter P2 for each vehicle to which a vehicle ID has been assigned by matching the first detection information D1 and the second detection information D2.

This allows the shape discrimination device 11 to discriminate the shape of each vehicle VV to which a vehicle ID has been assigned.

(5) The shape discrimination device 11 according to the fifth aspect is any one of the shape discrimination devices 11 according to (1) to (4), and includes a third calculation unit 115 that calculates the speed or vehicle distance of a vehicle VV traveling in a lane based on the first detection information D1 or the second detection information D2.

Therefore, the shape discrimination device 11 can calculate not only the shape of the vehicle VV, but also the speed or inter-vehicle distance of the vehicle VV.

(6) The merging assistance device 1 according to the sixth aspect includes the shape discrimination device 11 described in (5) and an assistance information generation unit 12 that generates merging assistance information DA based on the vehicle speed or vehicle-to-vehicle distance calculated by the third calculation unit 115.

This allows the merging support device 1 to generate more detailed support information.

(7) The shape method according to the eighth aspect acquires first detection information D1 from a first sensor 2A that detects a vehicle VV traveling on a lane LL from a first direction, acquires second detection information D2 from a second sensor 2B that detects the vehicle VV from a second direction different from the first direction, calculates a first parameter P1 including at least one of vehicle height, vehicle length, and vehicle width based on the first detection information D1, calculates a second parameter including at least one of vehicle height, vehicle length, and vehicle width based on the second detection information D2, and complements the first parameter P1 based on the second parameter P2.

According to this embodiment, the shape discrimination device 11 complements the first parameter based on the second parameter.

Therefore, the shape discrimination device 11 complements the first parameter P1 calculated from the first detection information D1 detected from a different direction based on the second parameter P2 calculated from the second detection information D2, thereby enabling the shape of the vehicle VV to be discriminated with greater accuracy.

(8) The program according to the ninth aspect causes the computer of the shape discrimination device 11 to acquire first detection information D1 from a first sensor 2A that detects a vehicle VV traveling on a lane LL from a first direction, acquire second detection information D2 from a second sensor 2B that detects the vehicle VV from a second direction different from the first direction, calculate a first parameter P1 including at least one of vehicle height, vehicle length, and vehicle width based on the first detection information D1, calculate a second parameter including at least one of vehicle height, vehicle length, and vehicle width based on the second detection information D2, and complement the first parameter P1 based on the second parameter P2.

According to this aspect, the program causes the computer of the shape discrimination device 11 to complement the first parameter based on the second parameter.

The program therefore complements the first parameter P1 calculated from the first detection information D1 detected from a different direction with the second parameter P2 calculated from the second detection information D2, thereby enabling the shape of the vehicle VV to be determined with greater accuracy.

1 Merging support device 2A First sensor 2B, 2C Second sensor 2B1, 2B2 Laser scanner 3, 703 Roadside wireless device 11 Shape discrimination device 12, 712 Support information generation unit 91 CPU
92 Memory 93 Storage/playback device 94 IO I/F
95 Communication I/F
100, 700 Merge support system 111 First acquisition unit 112 Second acquisition unit 113 First calculation unit 114 Second calculation unit 115 Third calculation unit 701 Merge support device 702 Area sensor 711 Matching device 811 Acquisition unit 812 Complement unit 813 Determination unit A1 Point AA Predetermined area D1 First detection information D2 Second detection information P1 First parameter P2 Second parameter P3 Third parameter CP Complemented parameter DA Merge support information RR Road VV Vehicle VM Merge vehicle VMa Vehicle-mounted device

Claims (8)

a first acquisition unit that acquires first detection information from a first sensor that detects a vehicle traveling on a lane from a first direction;
a second acquisition unit that acquires second detection information from a second sensor that detects the vehicle from a second direction different from the first direction;
a first calculation unit that calculates a first parameter including at least one of a vehicle height, a vehicle length, and a vehicle width based on the first detection information;
a second calculation unit that calculates a second parameter including at least one of a vehicle height, a vehicle length, and a vehicle width based on the second detection information;
a complementing unit that complements the first parameter based on the second parameter;
Equipped with
the complementing unit calculates an average value or a weighted average value of a parameter included in both the first parameter and the second parameter, among parameters of a vehicle height, a vehicle length, or a vehicle width, and complements the first parameter using the calculated average value or weighted average value.
Shape discrimination device. The shape discrimination device according to claim 1, wherein the first sensor is an area sensor. The shape discrimination device according to claim 1 or claim 2, wherein the second direction is the width direction of the vehicle. The shape discrimination device according to any one of claims 1 to 3, wherein the complementing unit complements the first parameter based on the second parameter for each vehicle to which an identifier has been assigned by matching the first detection information and the second detection information. 4. The shape discrimination device according to claim 3, further comprising a third calculation unit that calculates the speed of a vehicle traveling in the lane or the distance between two vehicles traveling one behind the other in the lane, based on a time series of the second detection information that detects the side of a vehicle traveling in the lane . The shape discrimination device according to claim 5 ;
an assistance information generating unit that generates merging assistance information based on the vehicle speed or the vehicle-to-vehicle distance calculated by the third calculating unit;
A merging assistance device comprising: acquiring first detection information from a first sensor that detects a vehicle traveling in a lane from a first direction;
acquiring second detection information from a second sensor that detects the vehicle from a second direction different from the first direction;
Calculating a first parameter including at least one of a vehicle height, a vehicle length, and a vehicle width based on the first detection information;
Calculating a second parameter including at least one of a vehicle height, a vehicle length, and a vehicle width based on the second detection information;
Complementing the first parameter based on the second parameter;
A shape discrimination method , comprising:
When complementing the first parameter, an average value or a weighted average value of a parameter included in both the first parameter and the second parameter out of a vehicle height, a vehicle length, or a vehicle width is calculated, and the first parameter is complemented using the calculated average value or weighted average value.
Shape discrimination method . The computer of the shape discrimination device
acquiring first detection information from a first sensor that detects a vehicle traveling in a lane from a first direction;
acquiring second detection information from a second sensor that detects the vehicle from a second direction different from the first direction;
Calculating a first parameter including at least one of a vehicle height, a vehicle length, and a vehicle width based on the first detection information;
Calculating a second parameter including at least one of a vehicle height, a vehicle length, and a vehicle width based on the second detection information;
Complementing the first parameter based on the second parameter;
A program for causing a computer to execute the steps of:
When complementing the first parameter, an average value or a weighted average value of a parameter included in both the first parameter and the second parameter out of a vehicle height, a vehicle length, or a vehicle width is calculated, and the first parameter is complemented using the calculated average value or weighted average value.
program .

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