JP7466489B2 - Vehicle group determination device, merging support device, vehicle group determination method, and program - Google Patents

Description

This disclosure relates to a vehicle group determination device, a merging support device, a vehicle group determination method, and a program.

When driving on a road, a vehicle can drive appropriately by understanding the status of vehicles other than the vehicle itself that are driving around the vehicle. For example, in a merging section on a highway, a vehicle traveling on the merging road (hereinafter, merging vehicle) needs to merge into the mainstream road while checking the status of vehicles traveling on the mainstream road (hereinafter, mainstream vehicle).
For this reason, a system that assists driving operations in merging sections needs to accurately identify the status of vehicles in the mainstream.

As a device for grasping the status of vehicles on the road, for example, a traffic information acquisition device such as that disclosed in Patent Document 1 is known.

JP 2018-010506 A

In Patent Document 1, in order to identify low speed sections of a vehicle group, a travel trajectory drawn by the passing times of vehicles at a plurality of points aligned in the vehicle travel direction is obtained.
However, the driving trajectory acquired by the device disclosed in Patent Document 1 may not be able to detect vehicle behavior that avoids traffic anomalies, which are abnormal traffic conditions on the road that are desirable to understand and avoid in order to drive safely.

The present disclosure has been made to solve the above problem, and aims to provide a vehicle group determination device, a merging support device, a vehicle group determination method, and a program that can detect the behavior of vehicles that avoid traffic abnormalities.

In order to solve the above problem, the vehicle group determination device according to the present disclosure includes an acquisition unit that acquires detection information from a roadside sensor that detects vehicles traveling on a road, an orientation vector detection unit that detects the behavior of an orientation vector, which is a vector that indicates the direction in which the multiple vehicles are traveling, based on the detection information, and an abnormal vehicle group determination unit that determines an abnormal vehicle group based on the behavior of the orientation vector.

The vehicle group determination method disclosed herein acquires detection information from a roadside sensor that detects vehicles traveling on a road, detects the behavior of an orientation vector, which is a vector that indicates the direction in which multiple vehicles are traveling, based on the detection information, and determines an abnormal vehicle group based on the behavior of the orientation vector.

The program disclosed herein causes a computer of a vehicle group determination device to acquire detection information from a roadside sensor that detects vehicles traveling on a road, detect the behavior of an orientation vector, which is a vector that indicates the direction in which multiple vehicles are traveling, based on the detection information, and determine an abnormal vehicle group based on the behavior of the orientation vector.

The vehicle group determination device, merging support device, vehicle group determination method, and program disclosed herein can detect vehicle behavior that avoids traffic abnormalities.

1 is an overall view of a merging assistance system according to an embodiment of the present disclosure. 1 is a block diagram of a vehicle group determination device according to an embodiment of the present disclosure. 1 is a diagram illustrating an example of image data acquired by a vehicle group determination device according to an embodiment of the present disclosure. 1 is a diagram illustrating an example of image data acquired by a vehicle group determination device according to an embodiment of the present disclosure. 11 is a table showing an example of vehicle information acquired by a vehicle group determination device according to an embodiment of the present disclosure in association with each vehicle ID. 4 is a flowchart of a vehicle group determination method according to an embodiment of the present disclosure. FIG. 13 is an overall view of a merging assistance system according to a modified example of an embodiment of the present disclosure. 11A and 11B are diagrams illustrating an example of image data acquired by a vehicle group determination device according to a modified example of an embodiment of the present disclosure. 4 is an example of a hardware configuration of a computer included in a vehicle group determination 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.

<Embodiment>
A vehicle group determination 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, the road RR may be a main road such as an expressway.
For example, the merging road RM may be a ramp that merges onto a main road such as an expressway.

As shown in FIG. 1, the merging support system 100 includes a merging support device 1, a roadside sensor 2, a roadside wireless device 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 FIG. 1, each vehicle travels in the direction indicated by the arrow.
For example, the merging vehicle VM according to this embodiment may be an autonomous vehicle.

Hereinafter, the direction in which the road RR extends and in which the vehicles travel will also be referred to as the X direction.
Further, 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.

(Configuration of the merging support device)
As shown in FIG. 2 , the merging assistance device 1 includes a vehicle group determination device 11 and an assistance information generation unit 12 .
The merging assistance device 1 is communicably connected to the roadside sensor 2 via a dedicated communication line or a public communication line.
The merging assistance device 1 is communicably connected to the roadside wireless device 3 via a dedicated communication line or a public communication line.
For example, the merging support device 1 may be installed on a road RR, which is a main road of a road (such as a highway), in the vicinity of a merging section where a merging road RM merges, or may be set in a remote location away from the merging section.
For example, a computer may function as the merging assistance device 1 by executing a program described below.

(Configuration of vehicle group determination device)
The vehicle group determination device 11 includes an acquisition unit 111 , an orientation vector detection unit 112 , and an abnormal vehicle group determination unit 115 .
For example, the vehicle group determination device 11 may further include an acceleration detection unit 113 and a vehicle speed detection unit 114 .
For example, a computer may function as the vehicle group determination device 11 by executing a program described below.

The acquisition unit 111 acquires detection information DD from a roadside sensor 2 that detects a vehicle VV traveling on a road RR.
For example, the detection information DD may include image data D1 of a predetermined area AA of a road RR that includes a plurality of vehicles VV.
For example, the predetermined area AA may be set immediately before the merging section of the road RR and the merging road RM.

For example, the acquisition unit 111 may individually identify multiple vehicles VV included in the image data D1, and assign a vehicle ID to each identified vehicle VV that enables the vehicle VV to be distinguished from other vehicles VV.
For example, the acquisition unit 111 may perform matching processing for each vehicle VV between multiple image data D1 at different times, and assign the same vehicle ID to vehicles VV that can be identified.
For example, the acquisition unit 111 may determine the order in which multiple vehicles VV pass through a specified area AA from the changes over time between multiple image data D1 acquired at different times, and assign vehicle IDs to the vehicles in the chronological order in which they pass through the specified area AA.

The orientation vector detection unit 112 detects the behavior of an orientation vector D2, which is a vector indicating the direction in which the multiple vehicles VV are traveling, based on the detection information DD.
For example, the orientation vector detection unit 112 may detect the behavior of the orientation vector D2 across multiple vehicles VV based on the detection information DD.
For example, the orientation vector detection unit 112 may acquire the orientation vector D2 of each vehicle VV based on the detection information DD.
For example, the orientation vector detection unit 112 may individually identify multiple vehicles VV contained in the image data D1, and obtain the orientation vector D2 of each vehicle VV from the changes in the position of each vehicle over time between multiple image data D1 acquired at different times.
For example, the orientation vector detection unit 112 may identify the orientation vector angle θ from each acquired orientation vector D2.
For example, the orientation vector detection unit 112 may associate the behavior of the detected orientation vector D2, the acquired orientation vector D2, and the identified orientation vector angle θ with a vehicle ID assigned to each vehicle VV.

Here, the orientation vector D2 of each vehicle VV is a vector that indicates the direction in which each vehicle VV is traveling.
The azimuth vector angle θ is the angle at which the azimuth vector D2 is inclined with respect to the X direction.
For example, as shown in FIG. 3, when a road RR has lanes L1 and L2 on one side of the road, the orientation vector D2 of a vehicle VV traveling along lane L1 and moving toward lane L2 to avoid lane L1 is inclined at an orientation vector angle θ with respect to the X direction from lane L1 toward lane L2.
On the other hand, when the vehicle VV is traveling straight along the lane L1, the orientation vector D2 of the vehicle VV is a vector pointing in the X direction, and the orientation vector angle θ of the vehicle VV is 0°.

For example, the orientation vector detection unit 112 may detect an orientation vector D2 having an orientation vector angle θ whose absolute value is greater than a predetermined angle r as the behavior of the orientation vector D2 across multiple vehicles VV.
That is, if the predetermined angle r is a positive number, the orientation vector detection unit 112 may detect an orientation vector D2 having an orientation vector angle θ such that θ<−r or r<θ.
For example, the orientation vector detection unit 112 may set the predetermined angle r=10°, and detect an orientation vector D2 having an orientation vector angle θ such that θ<−10° or 10°<θ.

As shown in Figure 3, for example, when an emergency vehicle VA such as an ambulance, emergency vehicle, or police vehicle approaches from behind in lane L1, the vehicle VV traveling in lane L1 will move toward lane L2 to avoid the emergency vehicle VA, and the vehicle VV traveling in lane L2 will move away from lane L1, so the azimuth vector angle θ of each vehicle VV may tilt.
As shown in FIG. 4, for example, when a wrong-way vehicle VB approaches from the front on lane L1, the vehicle VV traveling in lane L1 moves toward lane L2 to avoid the wrong-way vehicle VB, and the vehicle VV traveling in lane L2 moves away from lane L1, so that the azimuth vector angle θ of each vehicle VV may tilt.

The acceleration detection unit 113 detects the behavior of the acceleration D3 across multiple vehicles VV based on the detection information DD.
For example, the acceleration detection unit 113 may acquire the acceleration D3 of each vehicle VV across multiple vehicles VV.
For example, the acceleration detection unit 113 may associate the acquired acceleration D3 and the behavior of the detected acceleration D3 with a vehicle ID assigned to each vehicle VV.
For example, the acceleration detection unit 113 may individually identify multiple vehicles VV contained in the image data D1 and obtain the acceleration D3 of each vehicle VV from the change over time in the position of each vehicle VV between multiple image data D1 acquired at different times.
For example, the acceleration detection unit 113 may compare the acquired acceleration D3 with a predetermined acceleration −α stored in advance in the vehicle group determination device 11.

For example, the acceleration detection unit 113 may detect an acceleration D3 smaller than a predetermined acceleration −α as the behavior of the acceleration D3 across multiple vehicles VV.
Here, for example, when an emergency vehicle VA such as an ambulance, an emergency vehicle, or a police vehicle approaches from behind on the lane L1, the vehicle VV traveling on the lane L1 may significantly decelerate in order to avoid the emergency vehicle VA. In order to detect the acceleration D3 of such a decelerating vehicle VV, the acceleration detection unit 113 may detect an acceleration D3 that is smaller than a predetermined acceleration −α, which is a negative value.
Similarly, for example, when a wrong-way vehicle VB approaches from the front on the lane L1, the vehicle VV traveling on the lane L1 may significantly decelerate in order to avoid the wrong-way vehicle VB. In order to detect the acceleration D3 of such a decelerating vehicle VV, the acceleration detection unit 113 may detect an acceleration D3 that is smaller than a predetermined acceleration −α, which is a negative value.
In these cases, for example, the predetermined acceleration -α may be set to -2.0 m/s^2.

The vehicle speed detection unit 114 detects the behavior of vehicle speeds D4 across multiple vehicles VV based on the detection information DD.
For example, the vehicle speed detection unit 114 may acquire the vehicle speed D4 of each vehicle VV across multiple vehicles VV.
For example, the vehicle speed detection unit 114 may associate the acquired vehicle speed D4 and the behavior of the detected vehicle speed D4 with a vehicle ID assigned to each vehicle VV.
For example, the vehicle speed detection unit 114 may individually identify multiple vehicles VV contained in the image data D1, and obtain the vehicle speed D4 of each vehicle VV from the change over time in the position of each vehicle VV between multiple image data D1 acquired at different times.

For example, the vehicle speed detection unit 114 may detect a vehicle speed D4 that is smaller than the average vehicle speed by a predetermined value β as the behavior of the vehicle speed D4 across multiple vehicles VV.
The average vehicle speed may be the average vehicle speed of all vehicles that have passed through the specified area AA, for example, the average vehicle speed of all vehicles that have passed through the specified area AA over a specified period of time prior to the time when the vehicle speed D4 to be detected was detected.
For example, the vehicle speed detection unit 114 may obtain the difference from the average vehicle speed for each vehicle VV, that is, the average vehicle speed - the vehicle speed D4. In this case, the vehicle speed detection unit 114 may detect a vehicle speed D4 such that the difference from the average vehicle speed > a predetermined value β. Note that the predetermined value β is a positive number.

Here, for example, when an emergency vehicle VA such as an ambulance, emergency vehicle, or police vehicle approaches from behind on the lane L1, the vehicle VV traveling on the lane L1 may travel at a speed significantly slower than the normal average vehicle speed in the predetermined area AA in order to avoid the emergency vehicle VA. In order to detect the vehicle speed D4 of the vehicle VV traveling at such a slow speed, the vehicle speed detection unit 114 may detect a vehicle speed D4 that is even slower than the average vehicle speed by a predetermined value β.
Similarly, for example, when a wrong-way vehicle VB approaches from the front on the lane L1, the vehicle VV traveling on the lane L1 may travel at a speed significantly slower than the normal average vehicle speed in the predetermined area AA in order to avoid the wrong-way vehicle VB. In order to detect the vehicle speed D4 of the vehicle VV traveling at such a slow speed, the vehicle speed detection unit 114 may detect a vehicle speed D4 that is even slower than the average vehicle speed by a predetermined value β.

The abnormal vehicle group determination unit 115 determines an abnormal vehicle group GA based on the behavior of the orientation vector D2 detected by the orientation vector detection unit 112. An abnormal vehicle group refers to a plurality of vehicles that are traveling in a manner different from the normally expected traveling manner.
For example, the abnormal vehicle group determination unit 115 may determine that a plurality of vehicles VV having the orientation vector D2 detected by the orientation vector detection unit 112 are the same abnormal vehicle group GA. In this case, the abnormal vehicle group determination unit 115 may determine that a plurality of vehicles VV having consecutive vehicle IDs are the same abnormal vehicle group GA.

For example, as shown in FIG. 3, for multiple vehicles VV exhibiting behavior to avoid an emergency vehicle VA, the abnormal vehicle group determination unit 115 may determine that the vehicle group is an abnormal vehicle group GA if the absolute value of the azimuth vector angle θ is greater than a predetermined angle r.
For example, as shown in FIG. 4, for multiple vehicles VV exhibiting behavior to avoid a wrong-way vehicle VB, the abnormal vehicle group determination unit 115 may determine that the vehicles VV are an abnormal vehicle group GA if the absolute value of the orientation vector angle θ is greater than a predetermined angle r.
In the case shown in Figures 3 and 4, the vehicle group orientation vector DG2, which is the average orientation vector of the multiple vehicles VV included in the abnormal vehicle group GA, is also inclined with respect to the X direction.

For example, if an orientation vector D2 having an orientation vector angle θ as shown in FIG. 5 is obtained for each vehicle VV and a predetermined angle r = 10° is set, the abnormal vehicle group determination unit 115 may determine that a group of vehicles VV associated with the portion surrounded by group G1 is an abnormal vehicle group GA.

For example, the abnormal vehicle group determination unit 115 may determine an abnormal vehicle group GA based on the behavior of the acceleration D3 detected by the acceleration detection unit 113.
For example, the abnormal vehicle group determination unit 115 may determine that a plurality of vehicles VV having an acceleration D3 detected by the acceleration detection unit 113 are the same abnormal vehicle group GA. In this case, the abnormal vehicle group determination unit 115 may determine that a plurality of vehicles VV having consecutive vehicle IDs are the same abnormal vehicle group GA.

For example, when the acceleration D3 as shown in FIG. 5 is acquired for each vehicle VV and the predetermined acceleration -α = -2.0 m/s^2 is set, the abnormal vehicle group determination unit 115 may determine that the group of vehicles VV associated with the portion surrounded by group G2 is an abnormal vehicle group GA.

For example, the abnormal vehicle group determination unit 115 may determine an abnormal vehicle group GA based on the behavior of the vehicle speed D4 detected by the vehicle speed detection unit 114.
For example, the abnormal vehicle group determination unit 115 may determine that a plurality of vehicles VV having a vehicle speed D4 detected by the vehicle speed detection unit 114 are the same abnormal vehicle group GA. In this case, the abnormal vehicle group determination unit 115 may determine that a plurality of vehicles VV having consecutive vehicle IDs are the same abnormal vehicle group GA.

The vehicle group determination device 11 may determine that the vehicle group behavior of multiple vehicles VV that are not determined to be an abnormal vehicle group GA is normal.

(Configuration of the support information generating unit)
The assistance information generating unit 12 generates merging assistance information DA based on the abnormal vehicle group GA.
For example, when the vehicle group determination device 11 determines an abnormal vehicle group GA, the assistance information generation unit 12 may create information to the effect that the abnormal vehicle group GA is approaching a merging section, and include the information in the merging assistance information DA.

For example, the assistance information generator 12 may include information indicating the position of the abnormal vehicle group GA on the road RR in the merging assistance information DA.
For example, the support information generator 12 may include the characteristics of the abnormal vehicle group GA in the merging support information DA. In this case, the characteristics of the abnormal vehicle group GA may include information indicating which of the behaviors of the orientation vector D2, the acceleration D3, and the vehicle speed D4 is based on which the abnormal vehicle group GA is determined.

(Roadside sensor configuration)
The roadside sensor 2 detects a vehicle VV traveling on a road RR.
For example, the roadside sensor 2 may capture an image overlooking a predetermined area AA of the road RR and obtain detection information DD including image data D1 of the predetermined area AA of the road RR that includes a plurality of vehicles VV.
For example, the roadside sensor 2 may be set so that the predetermined area AA is an area that can accommodate a plurality of vehicles VV traveling on the road RR in the X direction.
For example, the roadside sensor 2 may be set so that the specified area AA is an area that includes multiple lanes LL in the Y direction.
For example, the roadside sensor 2 may repeatedly capture images at a predetermined time and acquire multiple image data D1 at different times.
For example, the roadside sensor 2 may include an area sensor such as a LiDAR (Light Detection and Ranging) or a camera.
For example, the roadside sensor 2 may provide the acquired detection information DD 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 wireless device 3 may transmit the acquired merging assistance information DA to an in-vehicle device VMa mounted on a merging vehicle VM traveling on the merging road RM to notify the driver or the like.
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 assistance information DA to an on-board unit VMa mounted on the merging vehicle VM, or may transmit the information to a display board or the like erected on the roadside, and notify the merging vehicle VM traveling on the merging road RM of the merging assistance information DA by display or audio via a display board, speaker, etc.

(motion)
The operation of the vehicle group determination device 11 of this embodiment will be described.
The operation of the vehicle group determination device 11 corresponds to the vehicle group determination method of this embodiment.

First, as shown in FIG. 6, the acquisition unit 111 acquires detection information DD from a roadside sensor 2 that detects a vehicle VV traveling on a road RR (ST01: step of acquiring detection information).

After performing ST01, the orientation vector detection unit 112 detects the behavior of the orientation vector D2, which is a vector indicating the direction in which the multiple vehicles VV are traveling, based on the detection information DD (ST02: step of detecting the behavior of the orientation vector).
For example, the orientation vector detection unit 112 may detect the behavior of the orientation vector D2 across multiple vehicles VV based on the detection information DD.
For example, the orientation vector detection unit 112 may detect an orientation vector D2 having an orientation vector angle θ whose absolute value is greater than a predetermined angle r as the behavior of the orientation vector D2 across multiple vehicles VV.
If the absolute value of the azimuth vector angle θ of the azimuth vector D2 is greater than the predetermined angle r (ST02: Yes), proceed to ST06.
If the absolute value of the azimuth vector angle θ of the azimuth vector D2 is not greater than the predetermined angle r (ST02: No), proceed to ST03.

In ST03, the acceleration detection unit 113 detects the behavior of acceleration D3 across multiple vehicles VV based on the detection information DD (ST03: step of detecting acceleration behavior).
For example, the acceleration detection unit 113 may detect an acceleration D3 that is smaller than a predetermined acceleration −α as the behavior of the acceleration detection unit 113 across multiple vehicles VV.
If the acceleration D3 is smaller than the predetermined acceleration −α (ST03: Yes), proceed to ST06.
If the acceleration D3 is not smaller than the predetermined acceleration -α (ST03: No), proceed to ST04.

In ST04, the vehicle speed detection unit 114 detects the behavior of the vehicle speed D4 across multiple vehicles VV based on the detection information DD (ST04: step of detecting vehicle speed behavior).
For example, the vehicle speed detection unit 114 may detect a vehicle speed D4 that is smaller than the average vehicle speed by a predetermined value β as the behavior of the vehicle speed D4 across multiple vehicles VV.
If the vehicle speed D4 is smaller than the average vehicle speed by the predetermined value β (ST04: Yes), proceed to ST06.
If the vehicle speed D4 is not smaller than the average vehicle speed by the predetermined value β (ST04: No), proceed to ST05.

In ST05, the vehicle group determination device 11 determines that the vehicle group behavior of the multiple vehicles VV that were not determined to be an abnormal vehicle group GA is normal (ST05: step of determining that vehicle group behavior is normal).
After performing ST05, the process returns to ST01 and repeats each step.

In ST06, the abnormal vehicle group determination unit 115 determines an abnormal vehicle group GA based on the behavior of the orientation vector D2 detected by the orientation vector detection unit 112 (ST06: step of determining an abnormal vehicle group).

For example, after performing ST02, the abnormal vehicle group determination unit 115 determines whether the orientation vector D2 (whose absolute value of the orientation vector angle θ is greater than a predetermined angle r) detected by the orientation vector detection unit 112 spans multiple vehicles V. If it is determined that the orientation vector D2 spans multiple vehicles V, the abnormal vehicle group determination unit 115 may determine that the multiple vehicles V related to the determination are an abnormal vehicle group GA (ST06-1).
Incidentally, spanning multiple vehicles VV means, as described above, that the vehicle group orientation vector DG2, which is the determined average orientation vector of the multiple vehicles VV, is inclined with respect to the X direction and is abnormal.

For example, the abnormal vehicle group determination unit 115 may determine that multiple vehicles VV having an orientation vector D2 detected by the orientation vector detection unit 112 (wherein the absolute value of the orientation vector angle θ is greater than a predetermined angle r) are the same abnormal vehicle group GA. In this case, the abnormal vehicle group determination unit 115 may determine that multiple vehicles VV with consecutive vehicle IDs are the same abnormal vehicle group GA.

For example, in ST06, the abnormal vehicle group determination unit 115 may determine an abnormal vehicle group GA based on the behavior of the acceleration D3 detected by the acceleration detection unit 113.

For example, after performing ST03, the abnormal vehicle group determination unit 115 determines whether the acceleration D3 (which is smaller than the predetermined acceleration -α) detected by the acceleration detection unit 113 applies to multiple vehicles VV.
If it is determined that the abnormality extends to multiple vehicles VV, the abnormal vehicle group determination unit 115 may determine that the multiple vehicles VV related to the determination are an abnormal vehicle group GA (ST06-2).
Incidentally, spanning multiple vehicles VV means that the vehicle group acceleration, which is the average acceleration of the multiple vehicles VV, is abnormal.

For example, the abnormal vehicle group determination unit 115 may determine that multiple vehicles VV having an acceleration D3 (smaller than the predetermined acceleration -α) detected by the acceleration detection unit 113 are the same abnormal vehicle group GA. In this case, the abnormal vehicle group determination unit 115 may determine that multiple vehicles VV with consecutive vehicle IDs are the same abnormal vehicle group GA.

For example, in ST06, the abnormal vehicle group determination unit 115 may determine an abnormal vehicle group GA based on the behavior of the vehicle speed D4 detected by the vehicle speed detection unit 114.

For example, after performing ST04, the abnormal vehicle group determination unit 115 determines whether the vehicle speed D4 detected by the vehicle speed detection unit 114 (which is smaller than the average vehicle speed and the predetermined value β) applies to multiple vehicles VV.
If it is determined that the abnormality extends to multiple vehicles VV, the abnormal vehicle group determination unit 115 may determine that the multiple vehicles VV related to the determination are an abnormal vehicle group GA (ST06-3).
Incidentally, spanning multiple vehicles VV means that the vehicle group speed, which is the average speed of the multiple vehicles VV, is abnormal.

For example, the abnormal vehicle group determination unit 115 may determine that multiple vehicles VV having a vehicle speed D4 (which is smaller than the average vehicle speed by a predetermined value β) detected by the vehicle speed detection unit 114 are the same abnormal vehicle group GA. In this case, the abnormal vehicle group determination unit 115 may determine that multiple vehicles VV with consecutive vehicle IDs are the same abnormal vehicle group GA.

After performing ST06, return to ST01 and repeat each step again.

(Action and Effects)
According to this embodiment, the vehicle group determination device 11 determines an abnormal vehicle group GA based on the behavior of the orientation vector D2 across multiple vehicles VV.
Therefore, the vehicle group determination device 11 can identify multiple vehicles VV that tend to move in a direction different from the direction along the road RR in order to avoid the traffic abnormality. By identifying multiple vehicles, it is possible to determine an abnormality without relying on the driving technique of each individual vehicle, as compared to a case where the determination is made based on only one vehicle.
Therefore, the vehicle group determination device 11 can detect the behavior of the vehicle VV to avoid a traffic abnormality.

According to this embodiment, the orientation vector detection unit 112 detects an orientation vector D2 having an orientation vector angle θ whose absolute value is greater than a predetermined angle r as the behavior of the orientation vector D2, and therefore the vehicle group determination device 11 can detect an orientation vector D2 that is pointing in a direction deviating from the specified direction.
Therefore, the vehicle group determination device 11 can detect the behavior of the abnormal orientation vector D2.

According to this embodiment, the vehicle group determination device 11 determines an abnormal vehicle group GA based on the behavior of the acceleration D3 across multiple vehicles VV.
Therefore, the vehicle group determination device 11 can identify multiple vehicles VV that are tending to decelerate, for example by applying the brakes, while traveling on the road RR in an attempt to avoid a traffic abnormality.
Therefore, the vehicle group determination device 11 can detect the behavior of the vehicle VV to avoid a traffic abnormality.

According to this embodiment, the acceleration detection unit 113 detects the acceleration D3 that is smaller than the predetermined acceleration -α as the behavior of the acceleration D3.
This allows the vehicle group determination device 11 to detect acceleration D3 that deviates from a predetermined acceleration.
Therefore, the vehicle group determination device 11 can detect the behavior of the abnormal acceleration D3.

According to this embodiment, the vehicle group determination device 11 determines an abnormal vehicle group GA based on the behavior of the vehicle speed D4 across multiple vehicles VV.
Therefore, the vehicle group determination device 11 can identify multiple vehicles VV that tend to travel at a speed slower than normal in an attempt to avoid a traffic abnormality.
Therefore, the vehicle group determination device 11 can detect the behavior of the vehicle VV to avoid a traffic abnormality.

According to this embodiment, the vehicle speed detection unit 114 detects a vehicle speed D4 that is smaller than the average vehicle speed by a predetermined value β as the behavior of the vehicle speed D4.
This enables the vehicle group determination device 11 to identify a vehicle speed D4 that deviates from the average vehicle speed.
Therefore, the vehicle group determination device 11 can detect the behavior of the abnormal vehicle speed D4.

According to this embodiment, the merging assistance device 1 generates the merging assistance information DA based on the abnormal vehicle group GA that is trying to avoid the traffic abnormality.
Therefore, the merging assistance device 1 can assist the vehicle in traveling on the merging road in response to a traffic abnormality on the main road.

(Modification)
In one example of the embodiment described above, the roadside sensor 2 captures images overlooking a specified area AA of the road RR, but the roadside sensor 2 may be configured in any manner as long as it can acquire image data D1 that can be used to determine an abnormal vehicle group GA.
For example, the vehicle group determination device 11 may include a roadside sensor 2 a as a modified example of the roadside sensor 2 .
For example, the roadside sensor 2a may include a line sensor that detects each vehicle VV traveling across the road RR from the roadside at a point A1, as shown in FIG.

For example, the roadside sensor 2a may include a laser scanner 2a1 and a laser scanner 2a2 that emit a laser from the roadside of the road RR so as to cross each vehicle traveling. In this case, the laser scanner 2a1 and the laser scanner 2a2 that scan the laser in the height direction may be installed at a predetermined sensor interval upstream and downstream in the X direction near the point A1.

For example, each of the laser scanners 2a1 and 2a2 may scan with a laser within a plane perpendicular to the X direction.
For example, each of the laser scanners 2a1 and 2a2 may be provided on the side of the road RR at approximately the same height as each of the vehicles VV. In this case, each of the laser scanners 2a1 and 2a2 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 2a1 and 2a2 may be capable of measuring the distance to each vehicle.

For example, as shown in FIG. 8, the roadside sensor 2a may acquire image data D1 that can identify the vehicle distance, vehicle height, vehicle length, etc., for each vehicle VV.
For example, the roadside sensor 2a may be able to obtain the orientation vector D2, acceleration D3, and vehicle speed D4 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.

In the example of the embodiment described above, the vehicle group determination device 11 is provided in the merging assistance device 1, but the vehicle group determination device 11 may be configured in any manner as long as it can determine an abnormal vehicle group GA.
As a modified example, the vehicle group determination device 11 may be provided separately from the merging assistance device 1 .
As another modification, the vehicle group determination device 11 may be provided on a merging road and a non-merging road. In this case, the vehicle group determination device 11 may provide information on the identified abnormal vehicle group GA to a monitoring panel of a control center or the like, or to an on-board device of a vehicle in front, behind, or in the vicinity.

In one example of the above-mentioned embodiment, the vehicle group determination device 11 detects the behavior of the orientation vector D2, the behavior of the acceleration D3, and the behavior of the vehicle speed D4, and determines whether an abnormal vehicle group GA is present, but the implementation may be in any manner as long as it is possible to determine whether an abnormal vehicle group GA is present.
As a modified example, the vehicle group determination device 11 may detect only the behavior of the orientation vector D2 and determine an abnormal vehicle group GA. In this case, the vehicle group determination device 11 does not need to detect the behavior of the acceleration D3 and the behavior of the vehicle speed D4.
As another modified example, the vehicle group determination device 11 may detect only the behavior of the orientation vector D2 and the behavior of the acceleration D3 to determine an abnormal vehicle group GA. In this case, the vehicle group determination device 11 does not need to detect the behavior of the vehicle speed D4.
As yet another modified example, the vehicle group determination device 11 may detect only the behavior of the orientation vector D2 and the behavior of the vehicle speed D4 to determine an abnormal vehicle group GA. In this case, the vehicle group determination device 11 does not need to detect the behavior of the acceleration D3.

In one example of the above-mentioned embodiment, the vehicle group determination device 11 detects the behavior of the orientation vector D2, the behavior of the acceleration D3, and the behavior of the vehicle speed D4 to determine whether there is an abnormal vehicle group, but this may be performed in any order as long as it can determine whether there is an abnormal vehicle group GA.
As a modified example, the vehicle group determination device 11 may first detect the behavior of the orientation vector D2, then detect the behavior of the vehicle speed D4, and finally detect the behavior of the acceleration D3.
As another modified example, the vehicle group determination device 11 may first detect the behavior of the vehicle speed D4, then detect one of the behavior of the orientation vector D2 and the behavior of the acceleration D3, and finally detect the other of the behavior of the orientation vector D2 and the behavior of the acceleration D3.
As yet another modified example, the vehicle group determination device 11 may first detect the behavior of the acceleration D3, then detect one of the behavior of the vehicle speed D4 and the behavior of the orientation vector D2, and finally detect the other of the behavior of the vehicle speed D4 and the behavior of the orientation vector D2.
As yet another modified example, the vehicle group determination device 11 may simultaneously detect the behavior of the orientation vector D2, the behavior of the acceleration D3, and the behavior of the vehicle speed D4.

In one example of the above-mentioned embodiment, the vehicle group determination device 11 detects an orientation vector D2 having an orientation vector angle θ whose absolute value is greater than a predetermined angle r, and determines an abnormal vehicle group GA from the detected orientation vector D2, but the method may be implemented in any manner as long as it is possible to determine an abnormal vehicle group GA.
As a modified example, the orientation vector detection unit 112 may detect the orientation vector D2 of each vehicle VV as the behavior of the orientation vector D2 across multiple vehicles VV, regardless of the magnitude of the orientation vector angle θ. In this case, the vehicle group determination device 11 may identify a vehicle group across multiple vehicles VV from which the orientation vector D2 has been detected, and determine as an abnormal vehicle group GA a vehicle group in which the absolute value of the orientation vector angle of the vehicle group orientation vector DG2 of the identified vehicle group exceeds a predetermined angle.

In one example of the above-mentioned embodiment, the vehicle group determination device 11 detects an acceleration D3 that is smaller than a predetermined acceleration -α, and determines an abnormal vehicle group GA from the detected acceleration D3, but the method may be implemented in any manner as long as it can determine an abnormal vehicle group GA.
As a modified example, the acceleration detection unit 113 may detect the acceleration D3 of each vehicle VV as the behavior of the acceleration D3 across the multiple vehicles VV, regardless of the magnitude of the acceleration D3. In this case, the vehicle group determination device 11 may identify a vehicle group across the multiple vehicles VV for which the acceleration D3 has been detected, and determine a vehicle group whose identified vehicle group acceleration is smaller than a predetermined acceleration as an abnormal vehicle group GA. Here, the vehicle group acceleration may be the average acceleration of the multiple vehicles VV included in the vehicle group.

In one example of the above-mentioned embodiment, the vehicle group determination device 11 detects a vehicle speed D4 that is even smaller than a predetermined value β from the average vehicle speed, and determines an abnormal vehicle group GA from the detected vehicle speed D4, but the device may be implemented in any manner as long as it can determine an abnormal vehicle group GA.
As a modified example, the vehicle speed detection unit 114 may detect the vehicle speed D4 of each vehicle VV as the behavior of the vehicle speed D4 across the multiple vehicles VV, regardless of the magnitude of the vehicle speed D4. In this case, the vehicle group determination device 11 may identify a vehicle group across the multiple vehicles VV for which the vehicle speed D4 has been detected, and determine as an abnormal vehicle group GA a vehicle group whose vehicle group speed is smaller than the average vehicle speed by a predetermined value. Here, the vehicle group speed may be the average vehicle speed of the multiple vehicles VV included in the vehicle group.

In this embodiment, the abnormal vehicle group determination unit 115 determines an abnormal vehicle group GA, but additional information may be added to the determined abnormal vehicle group GA.
As a modified example, the abnormal vehicle group determination unit 115 may detect a wrong-way vehicle VB based on the detection information DD, and may add information to the determined abnormal vehicle group GA that the wrong-way vehicle VB is the cause as additional information. In this case, the abnormal vehicle group determination unit 115 may detect, as the wrong-way vehicle VB, a vehicle whose vehicle speed D4 is a negative value or a vehicle whose position movement is in the opposite direction to the X direction based on the detection information DD.
As another variant, the abnormal vehicle group determination unit 115 may separately acquire detection information of a wrong-way driving vehicle VB detected by a wrong-way driving detection device or the like installed on the road RR, and add additional information to the determined abnormal vehicle group GA indicating that the wrong-way driving vehicle VB is the cause.

(Computer Configuration)
In each of the above-mentioned embodiments, a program for realizing the functions of the merging assistance device 1 or the vehicle group determination device 11 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-described embodiments, an example of the hardware configuration of a computer that executes a program to realize the functions of the merging assistance device 1 or the vehicle group determination device 11 will be described.

As shown in FIG. 9, the computer provided in the merging assistance device 1 or the vehicle group determination device 11 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 and the like used by the programs executed by the merging assistance device 1 or the vehicle group determination device 11 .
The storage/playback device 93 is a device for storing data in external media such as CD-ROMs, DVDs, and flash memories, and for playing back data from external media.
The IO I/F 94 is an interface for inputting and outputting information between the merging assistance device 1 and other devices, or between the vehicle group determination device 11 and other devices.
The communication I/F 95 is an interface for communicating 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 vehicle group determination device, the merging support device, the vehicle group determination method, and the program described in each embodiment can be understood, for example, as follows.

(1) The vehicle group determination device 11 according to the first aspect includes an acquisition unit 111 that acquires detection information DD from a roadside sensor 2 that detects vehicles VV traveling on a road RR, an orientation vector detection unit 112 that detects the behavior of an orientation vector D2, which is a vector indicating the direction in which the multiple vehicles VV are traveling, based on the detection information DD, and an abnormal vehicle group determination unit 115 that determines an abnormal vehicle group GA based on the behavior of the orientation vector D2.

According to this aspect, the vehicle group determination device 11 determines an abnormal vehicle group GA based on the behavior of the orientation vector D2 across multiple vehicles VV.
Therefore, the vehicle group determination device 11 can identify multiple vehicles VV that tend to move in a direction different from the direction along the road RR in order to avoid the traffic abnormality. By identifying multiple vehicles VV, it is possible to determine an abnormality without relying on the driving technique of each individual vehicle, as compared to a case where the determination is made based on only one vehicle.
Therefore, the vehicle group determination device 11 can detect the behavior of the vehicle VV to avoid a traffic abnormality.

(2) The vehicle group determination device 11 according to the second aspect is the vehicle group determination device 11 of (1), in which the orientation vector detection unit 112 detects the orientation vector D2 having an orientation vector angle θ whose absolute value is greater than a predetermined angle r as the behavior of the orientation vector D2.

According to this aspect, the vehicle group determination device 11 can detect the orientation vector D2 that faces in a direction deviating from a predetermined orientation.
Therefore, the vehicle group determination device 11 can detect the behavior of the abnormal orientation vector D2.

(3) The vehicle group determination device 11 according to the third aspect is the vehicle group determination device 11 according to (1) or (2), and further includes an acceleration detection unit 113 that detects the behavior of the acceleration D3 across the multiple vehicles VV based on the detection information DD, and the abnormal vehicle group determination unit 115 determines the abnormal vehicle group GA based on the behavior of the acceleration D3.

According to this aspect, the vehicle group determination device 11 determines an abnormal vehicle group GA based on the behavior of the acceleration D3 across multiple vehicles VV.
Therefore, the vehicle group determination device 11 can identify multiple vehicles VV that are tending to decelerate, for example by applying the brakes, while traveling on the road RR in an attempt to avoid a traffic abnormality.
Therefore, the vehicle group determination device 11 can detect the behavior of the vehicle VV to avoid a traffic abnormality.

(4) The vehicle group determination device 11 according to the fourth aspect is the vehicle group determination device 11 of (3), in which the acceleration detection unit 113 detects the acceleration D3 that is smaller than a predetermined acceleration -α as the behavior of the acceleration D3.

According to this aspect, the vehicle group determination device 11 can detect the acceleration D3 that deviates from a predetermined acceleration.
Therefore, the vehicle group determination device 11 can detect the behavior of the abnormal acceleration D3.

(5) The vehicle group determination device 11 according to the fifth aspect is any one of the vehicle group determination devices 11 according to (1) to (4), and further includes a vehicle speed detection unit 114 that detects the behavior of the vehicle speed D4 across the multiple vehicles VV based on the detection information DD, and the abnormal vehicle group determination unit 115 determines the abnormal vehicle group GA based on the behavior.

According to this aspect, the vehicle group determination device 11 determines an abnormal vehicle group GA based on the behavior of the vehicle speed D4 across multiple vehicles VV.
Therefore, the vehicle group determination device 11 can identify multiple vehicles VV that tend to travel at a speed slower than normal in an attempt to avoid a traffic abnormality.
Therefore, the vehicle group determination device 11 can detect the behavior of the vehicle VV to avoid a traffic abnormality.

(6) The vehicle group determination device 11 according to the sixth aspect is the vehicle group determination device 11 of (5), in which the vehicle speed detection unit 114 detects the vehicle speed D4 that is smaller than the average vehicle speed by a predetermined value β as the behavior of the vehicle speed D4.

According to this aspect, the vehicle group determination device 11 can identify a vehicle speed D4 that deviates from the average vehicle speed.
Therefore, the vehicle group determination device 11 can detect the behavior of the abnormal vehicle speed D4.

(7) The merging support device 1 according to the seventh aspect includes a vehicle group determination device 11 according to any one of (1) to (6) and a support information generation unit 12 that generates merging support information DA based on the abnormal vehicle group GA.

According to this aspect, the merging assistance device 1 generates the merging assistance information DA based on the abnormal vehicle group GA that is trying to avoid the traffic abnormality.
Therefore, the merging assistance device 1 can assist the vehicle in traveling on the merging road in response to a traffic abnormality on the main road.

(8) The vehicle group determination method according to the eighth aspect obtains detection information DD from a roadside sensor 2 that detects vehicles VV traveling on a road RR, detects the behavior of an orientation vector D2, which is a vector indicating the direction in which the multiple vehicles VV are traveling, based on the detection information DD, and determines an abnormal vehicle group GA based on the behavior of the orientation vector D2.

According to this aspect, the vehicle group determination method determines an abnormal vehicle group GA based on the behavior of the orientation vector D2 across multiple vehicles VV.
Therefore, the vehicle group determination method can identify multiple vehicles VV that tend to move in a direction different from the direction along the road RR in order to avoid a traffic abnormality. By identifying multiple vehicles VV, it is possible to determine an abnormality without relying on the driving technique of each individual vehicle, as compared to a case where a determination is made based on only one vehicle.
Therefore, the vehicle group determination method can detect the behavior of the vehicle VV to avoid a traffic anomaly.

(9) The program according to the ninth aspect causes the computer of the vehicle group determination device 11 to acquire detection information DD from a roadside sensor 2 that detects vehicles VV traveling on a road RR, detect the behavior of an orientation vector D2, which is a vector indicating the direction in which the multiple vehicles VV are traveling, based on the detection information DD, and determine an abnormal vehicle group GA based on the behavior of the orientation vector D2.

According to this aspect, the program causes the computer of the vehicle group determination device 11 to determine an abnormal vehicle group GA based on the behavior of the orientation vector D2 across multiple vehicles VV.
For this reason, the program causes the computer of the vehicle group determination device 11 to identify multiple vehicles VV that are trying to avoid the traffic abnormality and tend to move in a direction that deviates from the movement along the road RR. By identifying multiple vehicles VV, it is possible to determine an abnormality without relying on the driving technique of each individual vehicle, as compared to a case where the determination is made based on only one vehicle.
The program can thus detect the behavior of the vehicle VV to avoid traffic anomalies.

Reference Signs List 1 Merging support device 2 Roadside sensor 2a Roadside sensor 2a1 Laser scanner 2a2 Laser scanner 3 Roadside wireless device 11 Vehicle group determination device 12 Support information generation unit 91 CPU
92 Memory 93 Storage/playback device 94 IO I/F
95 Communication I/F
100 Merging support system 111 Acquisition unit 112 Orientation vector detection unit 113 Acceleration detection unit 114 Vehicle speed detection unit 115 Abnormal vehicle group determination unit A1 Point AA Predetermined area D1 Image data D2 Orientation vector D3 Acceleration D4 Vehicle speed DA Merging support information DD Detection information DG2 Vehicle group orientation vector G1 Group G2 Group GA Abnormal vehicle group L1 Lane L2 Lane LL Lane r Predetermined angle RM Merging road RR Road VV Vehicle VA Emergency vehicle VB Wrong-way vehicle VM Merging vehicle VMa Vehicle-mounted device -α: Predetermined acceleration β Predetermined value θ Orientation vector angle

Claims (13)

an acquisition unit that acquires detection information from a roadside sensor that detects vehicles traveling on a road;
an orientation vector detection unit that detects behavior of an orientation vector, which is a vector indicating a direction in which the plurality of vehicles are traveling, based on the detection information;
an acceleration detection unit that detects an acceleration behavior across the plurality of vehicles based on the detection information;
an abnormal vehicle group determination unit that determines an abnormal vehicle group based on the behavior of the orientation vector and the behavior of the acceleration ;
Equipped with
The acceleration detection unit detects, as the acceleration behavior, an acceleration smaller than a predetermined acceleration . The vehicle group determination device according to claim 1, wherein the orientation vector detection unit detects the orientation vector having an orientation vector angle whose absolute value is greater than a predetermined angle as the behavior of the orientation vector. A vehicle speed detection unit detects a vehicle speed behavior across the plurality of vehicles based on the detection information,
The vehicle group determination device according to claim 1 or 2 , wherein the abnormal vehicle group determination unit determines the abnormal vehicle group based on the vehicle speed behavior. The vehicle group determination device according to claim 3 , wherein the vehicle speed detection unit detects, as the vehicle speed behavior, a vehicle speed that is lower than an average vehicle speed by a predetermined value. an acquisition unit that acquires detection information from a roadside sensor that detects vehicles traveling on a road;
an orientation vector detection unit that detects behavior of an orientation vector, which is a vector indicating a direction in which the plurality of vehicles are traveling, based on the detection information;
a vehicle speed detection unit that detects the vehicle speed behavior of the plurality of vehicles based on the detection information;
an abnormal vehicle group determination unit that determines an abnormal vehicle group based on the behavior of the orientation vector and the behavior of the vehicle speed;
Equipped with
The vehicle speed detection unit detects, as the vehicle speed behavior, a vehicle speed that is smaller than an average vehicle speed by a predetermined value. The vehicle group determination device according to any one of claims 1 to 5 ,
an assistance information generating unit that generates merging assistance information based on the abnormal vehicle group;
A merging assistance device comprising: a vehicle group determination device including: an acquisition unit that acquires detection information from a roadside sensor that detects vehicles traveling on a road; an orientation vector detection unit that detects behavior of an orientation vector, which is a vector that indicates the direction in which the plurality of vehicles are traveling, based on the detection information; and an abnormal vehicle group determination unit that determines an abnormal vehicle group based on the behavior of the orientation vector;
an assistance information generating unit that generates merging assistance information based on the abnormal vehicle group;
A merging assistance device comprising: An acquisition unit of the vehicle group determination device acquires detection information from a roadside sensor that detects vehicles traveling on a road,
an orientation vector detection unit of the vehicle group determination device detects behavior of an orientation vector, which is a vector indicating a direction in which the plurality of vehicles are traveling, based on the detection information;
an acceleration detection unit of the vehicle group determination device detects an acceleration behavior of the plurality of vehicles based on the detection information;
an abnormal vehicle group determination unit of the vehicle group determination device determines an abnormal vehicle group based on the behavior of the orientation vector and the behavior of the acceleration ;
The vehicle group determination method , wherein the acceleration detection unit detects, as the acceleration behavior, the acceleration being smaller than a predetermined acceleration . An acquisition unit of the vehicle group determination device acquires detection information from a roadside sensor that detects vehicles traveling on a road,
an orientation vector detection unit of the vehicle group determination device detects behavior of an orientation vector, which is a vector indicating a direction in which the plurality of vehicles are traveling, based on the detection information;
a vehicle speed detection unit of the vehicle group determination device detects vehicle speed behavior across the plurality of vehicles based on the detection information;
an abnormal vehicle group determination unit of the vehicle group determination device determines an abnormal vehicle group based on the behavior of the orientation vector and the behavior of the vehicle speed;
The vehicle speed detection unit detects, as the vehicle speed behavior, a vehicle speed that is smaller than an average vehicle speed by a predetermined value.
A method for determining a group of vehicles. An acquisition unit of the merging support device acquires detection information from a roadside sensor that detects vehicles traveling on a road,
an orientation vector detection unit of the merging support device detects behavior of an orientation vector, which is a vector indicating an orientation in which the plurality of vehicles are traveling, based on the detection information;
an abnormal vehicle group determination unit of the merging assistance device determines an abnormal vehicle group based on the behavior of the orientation vector;
An assistance information generating unit of the merging assistance device generates merging assistance information based on the abnormal vehicle group.
A method for determining a group of vehicles. The vehicle group determination device's computer
Obtaining detection information from roadside sensors that detect vehicles traveling on the road,
Detecting behavior of a direction vector, which is a vector indicating a direction in which the plurality of vehicles are traveling, based on the detection information;
Detecting an acceleration behavior across the plurality of vehicles based on the detection information;
determining an abnormal vehicle group based on the behavior of the orientation vector and the behavior of the acceleration ;
A program for executing the program to detect, as the behavior of the acceleration, the acceleration that is smaller than a predetermined acceleration . The vehicle group determination device's computer
Obtaining detection information from roadside sensors that detect vehicles traveling on the road,
Detecting behavior of a direction vector, which is a vector indicating a direction in which the plurality of vehicles are traveling, based on the detection information;
Detecting vehicle speed behavior across the plurality of vehicles based on the detection information;
determining an abnormal vehicle group based on the behavior of the orientation vector and the behavior of the vehicle speed;
As the vehicle speed behavior, a vehicle speed that is smaller than an average vehicle speed by a predetermined value is detected.
A program to make that happen. The merging assistance device's computer
Obtaining detection information from roadside sensors that detect vehicles traveling on the road,
Detecting behavior of a direction vector, which is a vector indicating a direction in which the plurality of vehicles are traveling, based on the detection information;
determining an abnormal vehicle group based on the behavior of the orientation vector;
Generate merging assistance information based on the abnormal vehicle group.
A program to make that happen.

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