JP7621227B2 - Information processing device, information processing method, and information processing program - Google Patents

Description

This disclosure relates to an information processing device, an information processing method, and an information processing program.

Conventionally, there are behavior prediction devices that predict the behavior of a vehicle. When another vehicle traveling around the vehicle turns at an intersection, the other vehicle may turn after traveling near the center of the road width direction. In this case, the vehicle needs to sense the movement of the other vehicle and drive appropriately. The behavior prediction device described in Patent Document 1 is a device used to provide driving assistance for the vehicle, and predicts that the other vehicle may move in a direction away from the edge of the road. Specifically, the behavior prediction device determines whether an intersection (merging road) exists ahead of the other vehicle in the traveling direction, and if an intersection exists, predicts whether the position of the other vehicle in the road width direction of the road is likely to move from the edge of the road to the center (in the direction away from the edge). In this case, the behavior prediction device determines whether there is an object or a depression that will be an obstacle to the driving of the other vehicle due to the inside wheel difference of the other vehicle when turning at an intersection.

JP 2020-158007 A

For example, when a vehicle is about to turn left at an intersection and there is an obstacle at the intersection, the vehicle will turn left at the intersection taking into consideration the inside wheel difference, etc. By identifying such intersections in advance, it becomes possible to alert the driver when the vehicle is traveling through the intersection.
However, intersections where a driver needs to be careful when driving a vehicle are not limited to those where there are obstacles around. Therefore, it has been desired to identify points where a driver needs to be careful when driving a vehicle.

The present disclosure provides an information processing device, an information processing method, and an information processing program that can identify locations that require caution when driving a vehicle.

An information processing device according to one embodiment includes a first acquisition unit that acquires vehicle information related to the traveling of a vehicle, a second acquisition unit that acquires a degree of deviation of the traveling trajectory from a reference trajectory based on the traveling trajectory of the vehicle in an area including an intersection acquired based on the vehicle information acquired by the first acquisition unit and a reference trajectory of the lane in which the vehicle is traveling in the area, and an identification unit that identifies an intersection where the degree of deviation acquired by the second acquisition unit is equal to or greater than a first threshold value.

According to one aspect, the degree of deviation of the vehicle's travel trajectory from the reference trajectory is obtained based on the vehicle's travel trajectory in an area including an intersection and a reference trajectory of the lane in which the vehicle is travelling in that area, and intersections where the degree of deviation is equal to or greater than a first threshold value are identified, making it possible to identify points where caution is required when travelling the vehicle.

FIG. 1 is a diagram illustrating an information processing system according to an embodiment. FIG. 11 is a first diagram for explaining an example of a vehicle turning at an intersection while taking into account an inside wheel difference. FIG. 2 is a second diagram for explaining an example of a vehicle turning at an intersection while taking into account the inside wheel difference. FIG. 3 is a third diagram for explaining an example of a vehicle turning at an intersection while taking into account the inside wheel difference. FIG. 1 is a block diagram illustrating an information processing device according to an embodiment. 2 is a diagram for explaining an example of a vehicle travel trajectory and a reference trajectory; FIG. 1 is a flowchart illustrating an information processing method according to an embodiment.

One embodiment is described below.

[Overview of information processing system 1]
First, an overview of an information processing system 1 according to an embodiment will be described.
FIG. 1 is a diagram illustrating an information processing system 1 according to an embodiment.
2 to 4 are first to third diagrams for explaining an example of when the vehicle 300 turns at an intersection while taking the inside wheel difference N into consideration.

The information processing system 1 may be configured, for example, as a cautionary point identification system and a driving assistance system that identify cautionary points that require attention when the vehicle 300 is traveling. The information processing system 1 may also be configured, for example, as a road map creation system that registers cautionary points in a road map.
The information processing device 200 constituting the information processing system 1 may be configured as, for example, a cautionary spot identification device, a driving assistance device, a road map creation device, or the like, similarly to the above-mentioned systems.

As shown in FIG. 1, the information processing system 1 includes, for example, a server 100 and an information processing device 200.

The server 100 acquires and stores vehicle information generated by the vehicle 300. The vehicle information may be, for example, information related to the traveling of the vehicle 300. The information related to the traveling of the vehicle 300 may include information related to the operation of the vehicle 300 (operation information). The vehicle information may include position information related to the position of the vehicle 300. As an example, the vehicle information may be CAN information, probe information, etc. The probe information and CAN information are, for example, various information generated by the vehicle 300, information acquired by various sensors (not shown) mounted on the vehicle 300, etc.

The information processing device 200 may be, for example, a server, a desktop, a laptop, a tablet, etc. The information processing device 200 acquires vehicle information, for example, from the server 100 or the vehicle 300.

The information processing device 200 acquires the trajectory (travel trajectory 310) of the movement of the vehicle 300 when it actually travels based on the vehicle information. In this case, the information processing device 200 may acquire the travel trajectory 310 of the area including the intersection where the vehicle 300 traveled. Here, the intersection may be, for example, a concept including a point where a plurality of roads connect (intersection) as well as a point where the vehicle leaves a road, such as when entering a facility from the road. The information processing device 200 acquires the degree of deviation 330 between the travel trajectory 310 of the vehicle 300 and the reference trajectory 320 of the lane on which the vehicle 300 travels in the area including the intersection. The reference trajectory 320 may be, for example, a virtual line (a line tracing the center (approximate center) of the lane) that is the center (approximate center) of the lane, and a road link, etc. The road link may represent the shape of the road by connecting adjacent nodes that are characteristic points such as road intersections. The road link may be a concept including a lane link. The lane link may represent the shape of the lane.

As an example, when the vehicle 300 makes a left turn (or a right turn) at an intersection, depending on the conditions of the road at the destination (e.g., the road width is relatively narrow), the driver may first turn the steering wheel to the right (or left), then reverse and turn left (or right) at the intersection (a temporary reversal operation) (see FIG. 2).
As another example, when the vehicle 300 makes a left turn (or a right turn) at an intersection, the driver may delay the timing of turning the steering wheel to the left (or right) (see FIG. 3).
As another example, when vehicle 300 turns left (or right) at an intersection, the driver may drive vehicle 300 to the right (or left) of the lane in advance, and then turn the steering wheel to the left (or right) at the intersection (see FIG. 4).
As another example, when there is an obstacle at a corner of an intersection, the driver may perform the above-mentioned steering operation to avoid the obstacle.
That is, the driver may drive the vehicle 300 while being cautious of the inner wheel difference N, and may make a right or left turn. In this case, there is a high possibility that the travel path 310 of the vehicle 300 will deviate relatively significantly from the reference path 320. The information processing device 200 identifies an intersection where the degree of deviation 330 between the travel path 310 and the reference path 320 is equal to or greater than a first threshold value as an intersection (point) requiring caution when the vehicle 300 is traveling.

[Details of information processing device 200]
Next, details of the information processing device 200 according to an embodiment will be described.
FIG. 5 is a block diagram for explaining an information processing device 200 according to an embodiment.
FIG. 6 is a diagram for explaining an example of a traveling trajectory 310 and a reference trajectory 320 of the vehicle 300. As shown in FIG.

5, the information processing device 200 includes, for example, a communication unit 221, a storage unit 222, a display unit 223, and a control unit 210. The communication unit 221, the storage unit 222, and the display unit 223 may be, for example, an embodiment of an "output unit". The control unit 210 may function as, for example, a first acquisition unit 211, a second acquisition unit 212, an identification unit 213, a registration unit 214, an output control unit 215, etc. The control unit 210 may be, for example, configured by an arithmetic processing device of the information processing device 200. The control unit 210 (for example, an arithmetic processing device, etc.) may realize the functions of each unit (the first acquisition unit 211, the second acquisition unit 212, the identification unit 213, the registration unit 214, the output control unit 215, etc.) by, for example, appropriately reading and executing various programs, etc. stored in the storage unit 222, etc.

The communication unit 221 can transmit and receive various information to and from, for example, a device (external device) outside the information processing device 200. The external device may be, for example, the server 100 and the vehicle 300.

The storage unit 222 may store, for example, various information and programs. Examples of the storage unit 222 may be a memory, a solid state drive, a hard disk drive, etc. The storage unit 222 may store map information related to a road map.

The display unit 223 is capable of displaying, for example, various characters, symbols, images, etc.

The first acquisition unit 211 acquires vehicle information related to the traveling of the vehicle 300. The first acquisition unit 211 may acquire the vehicle information from the server 100 or the vehicle 300, for example, via the communication unit 221. In this case, the first acquisition unit 211 may acquire multiple pieces of vehicle information generated, for example, by the same or different vehicles 300.

The second acquisition unit 212 acquires the degree of deviation 330 of the driving trajectory 310 from the reference trajectory 320 based on the driving trajectory 310 of the vehicle 300 in an area including an intersection, which is acquired based on the vehicle information acquired by the first acquisition unit 211, and the reference trajectory 320 of the lane in which the vehicle 300 is traveling in that area (see Figure 6).
The travel trajectory 310 of the vehicle 300 may be, for example, a trajectory of the travel position when the vehicle 300 actually travels. The second acquisition unit 212 may acquire the travel trajectory 310 of the vehicle 300 based on, for example, position information included in the vehicle information. Here, when it is estimated that the vehicle 300 is turning at an intersection based on the vehicle information (position information), the second acquisition unit 212 may acquire the travel trajectory 310 of the vehicle 300 in an area including the intersection. Here, the intersection may be, for example, a concept including a point (intersection) where a plurality of roads connect, as well as a point where the vehicle leaves a road, such as when entering a facility from the road.

The area including the intersection may be, for example, an area within a predetermined distance L from a position A where the vehicle 300 is estimated to be turning at the intersection (see FIG. 6). The predetermined distance L may be any distance that is set in advance, such as 10 m, 15 m, 20 m, 25 m, 30 m, 40 m, and 50 m.

In this case, the area including the intersection may be, for example, an area surrounded by a circle having position A as its center and a predetermined distance L as its radius from position A.
Alternatively, the area including the intersection may be, for example, an area within a predetermined distance L from position A in the direction before vehicle 300 reaches position A (the direction of the approach road of vehicle 300 to position A as seen from position A). In this case, the area including the intersection may also include, for example, an area within the predetermined distance L from position A in the traveling direction of vehicle 300 after passing position A.

The second acquisition unit 212 may, for example, compare the vehicle information (position information) with the road network of the position where the vehicle 300 is traveling, and when the vehicle 300 travels along a road link (lane link) and passes a specific node, if the vehicle 300 travels along a road link (lane link) in a direction that is curved from the road link (lane link) before passing through the node, estimate that the specific node is the above-mentioned position A.

In addition, the second acquisition unit 212 may, for example, compare the vehicle information (location information) with the road network of the location where the vehicle 300 is traveling, and when the vehicle 300 leaves a road link (lane link), estimate the departure point to be the above-mentioned location A.

Here, when the vehicle 300 that generated the vehicle information turns left (or right) at an intersection, if the traveling trajectory 310 deviates to the right (or left) from the reference trajectory 320 in the direction of travel of the vehicle 300 in an area including the intersection, the second acquisition unit 212 may acquire the degree of deviation 330 of the traveling trajectory 310 from the reference trajectory 320.

In addition, the second acquisition unit 212 may estimate that the vehicle 300 is turning at an intersection based on at least one of a change in the traveling speed of the vehicle 300 acquired based on the vehicle information and a steering speed of the steering wheel of the vehicle 300 acquired based on the vehicle information.
When the second acquisition unit 212 estimates that the traveling speed of the vehicle 300 is decelerating based on the traveling speed of the vehicle 300 and the acceleration of the vehicle 300 acquired based on the vehicle information, and then estimates that the vehicle 300 is turning left or right at position A by comparing the vehicle information (position information) with the road network as described above, the second acquisition unit 212 may estimate that position A is an intersection.
In addition, if the steering speed of the vehicle 300 is faster than the steering speed when the vehicle 300 is traveling in a straight line and on a curve, etc. (if a steering speed exceeding the standard steering speed of the steering wheel when the vehicle 300 is traveling in a straight line and on a curve, etc. is recorded), and if a steering speed faster than the standard is detected at a point, the second acquisition unit 212 may estimate that the vehicle 300 is turning at position A by comparing the vehicle information (position information) with the road network as described above, and may estimate that position A is an intersection.

In addition, if, based on the vehicle information, the second acquisition unit 212 finds that the steering angle of the steering wheel of the vehicle 300 is greater than the steering angle when the vehicle 300 is traveling in a straight line and on a curve, etc. (if a steering angle exceeding a reference steering angle of the steering wheel when the vehicle 300 is traveling in a straight line and on a curve, etc. is recorded), and further, at the point where a steering angle greater than the reference is detected, if it is estimated that the vehicle 300 is turning at position A by comparing the vehicle information (position information) with the road network as described above, the second acquisition unit 212 may estimate position A to be an intersection.
In addition, when the turn indicator of the vehicle 300 (for example, a turn indication to the left (or right)) is operated based on the vehicle information, and further when it is estimated that the vehicle 300 is turning to the left (or right) at position A by comparing the vehicle information (position information) with the road network as described above at the point where the turn indicator is operated, the second acquisition unit 212 may estimate that position A is an intersection.
In addition, the second acquisition unit 212 may estimate that the vehicle 300 is turning at an intersection by combining one or more of the above-mentioned driving speed of the vehicle 300, the steering speed of the steering wheel of the vehicle 300, the steering angle of the steering wheel of the vehicle 300, and the operation of the turn signal of the vehicle 300.

The lane reference trajectory 320 may be, for example, a trajectory (e.g., a virtual line) formed at a position that is the center (approximate center) of each lane in the width direction. The lane reference trajectory 320 may also be, for example, a road link (lane link) corresponding to each lane in a road network. A road network is represented by connecting nodes that are characteristic points such as road intersections with links (road links (lane links)) that follow the shape of the road.

The second acquisition unit 212 acquires the degree of deviation 330 between the travel trajectory 310 of the vehicle 300 and the reference trajectory 320 of the lane on which the vehicle 300 travels in an area including an intersection. The degree of deviation 330 may be, for example, the distance between the reference trajectory 320 and the travel trajectory 310 from the start point S to the end point E, assuming that the point where the travel trajectory 310 starts to deviate from the reference trajectory 320 is a start point S, and the point where the travel trajectory 310 and the reference trajectory 320 overlap again (approximately overlap) is an end point E. The second acquisition unit 212 may be, for example, the distance of the travel trajectory 310 from the reference trajectory 320 at the point where the travel trajectory 310 is farthest from the reference trajectory 320. The second acquisition unit 212 may also be, for example, the average distance by which the travel trajectory 310 is away from the reference trajectory 320 from the start point S to the end point E.
Here, as in the example described above, the second acquisition unit 212 may acquire the degree of deviation 330 of the driving trajectory 310 from the reference trajectory 320 when it is estimated that the vehicle 300 is turning at an intersection based on at least one of the change in the driving speed of the vehicle 300 acquired based on the vehicle information and the steering speed of the steering wheel of the vehicle 300 acquired based on the vehicle information.

In the above-mentioned case, the second acquisition unit 212 may acquire the degree of deviation 330 of the running trajectory 310 from the reference trajectory 320 by using the wheelbase of the vehicle 300 specified based on the vehicle information. Information on the wheelbase of the vehicle 300 may be stored, for example, in the storage unit 222, or may be stored in the server 100 or the like outside the information processing device 200. The second acquisition unit 212 may acquire information on the wheelbase of the vehicle 300 from the storage unit 222 or the server 100 or the like. In general, it is considered that the degree of deviation 330 between the reference trajectory 320 and the running trajectory 310 is greater in a vehicle 300 having a relatively long wheelbase than in a vehicle 300 having a relatively short wheelbase. As an example, the second acquisition unit 212 can acquire a general degree of deviation 330 between the reference trajectory 320 and the running trajectory 310 regardless of the type of vehicle 300 for which vehicle information is generated, by standardizing the degree of deviation 330 between the reference trajectory 320 and the running trajectory 310 by the wheelbase of the vehicle 300, or by multiplying the degree of deviation 330 between the reference trajectory 320 and the running trajectory 310 by a coefficient corresponding to the wheelbase (length) of the vehicle 300.
In addition, the above-mentioned coefficients may be values that are set in stages according to the wheelbase (length) of the vehicle 300, and a relatively small value (or a large value) may be set when the wheelbase is relatively long, and a relatively large value (or a small value) may be set when the wheelbase is relatively short.

The identification unit 213 identifies an intersection where the degree of deviation 330 acquired by the second acquisition unit 212 is equal to or greater than the first threshold. In the example shown in FIG. 6, the portion where the degree of deviation 330 is equal to or greater than the first threshold is indicated by the symbol T. The identification unit 213 may identify an intersection where the degree of deviation 330 of the traveling trajectory 310 from the reference trajectory 320 is equal to or greater than the first threshold at any point between the start point S and the end point E. Alternatively, the identification unit 213 may identify an intersection where the maximum value (maximum deviation degree) or average value (average deviation degree) of the degree of deviation 330 of the traveling trajectory 310 from the reference trajectory 320 is equal to or greater than the first threshold. The first threshold is set to identify an intersection as one requiring attention when the vehicle 300 travels, and may be appropriately set by performing experiments, calculations, etc. in advance. When the identification unit 213 identifies an intersection where the degree of deviation 330 is equal to the first threshold value, the information processing device 200 may estimate that the vehicle 300 was traveling while being cautious about the inner wheel difference N.

The identification unit 213 may identify an intersection where the degree of deviation 330 is equal to or greater than the first threshold value when the number of times the degree of deviation 330 becomes equal to or greater than the second threshold value based on the vehicle information of the multiple vehicles 300. That is, when the degree of deviation 330 is identified as equal to or greater than the first threshold value multiple times equal to or greater than the second threshold value at the same intersection based on the multiple vehicle information, the identification unit 213 may identify the intersection as an intersection requiring caution when the vehicle 300 travels therethrough. In other words, when the occurrence frequency of travel while being cautious about the inner wheel difference N is equal to the second threshold value, the identification unit 213 may identify the intersection where the travel took place. The second threshold value may be set to an appropriate value, for example.
For example, when an intersection is identified by the identification unit 213 as described above, the information processing device 200 may estimate that there is a high risk of a hit-and-run accident due to the inside wheel difference N of the vehicle 300 at that intersection.

The identification unit 213 may identify an intersection where the degree of deviation 330 is equal to or greater than a first threshold value when there is a feature that is an obstacle to driving in an area including the intersection based on feature information regarding the presence or absence of features arranged on the road. The feature information may be included in the vehicle information, for example, or may be included in the map information stored in the storage unit 222. The feature may be, for example, a road shoulder, a drain, a utility pole, a sign, a sidewalk, a dividing line, a guardrail, or other object (obstacle) that may be an obstacle when the vehicle 300 drives, or an object that may not be an obstacle. For example, when a feature is present at the intersection and when a feature is present at a corner when the vehicle 300 turns at the intersection, the identification unit 213 may identify the intersection as an intersection that requires caution when the vehicle 300 drives the intersection when the degree of deviation 330 between the driving trajectory 310 and the reference trajectory 320 in the area including the intersection is equal to or greater than a first threshold value.

The identification unit 213 may identify an intersection where the degree of deviation 330 is equal to or greater than a first threshold value when the presence of a moving object that may be an obstacle to driving is estimated in an area including an intersection based on at least one of the driving time period of the vehicle 300 identified based on the vehicle information and the obstacle detection status for the vehicle 300 acquired based on the vehicle information.
In addition, during the time periods during which the vehicle 300 travels (travel time periods), for example, during commute times for work and school, there is a high possibility that many pedestrians, bicycles, and other moving objects travel on the roads. In such cases, there is a high possibility that the pedestrians, bicycles, and other moving objects will be an obstacle to the travel of the vehicle 300.
In addition, moving objects such as pedestrians, bicycles, and parked vehicles may be detected by an obstacle detection sensor (not shown) mounted on the vehicle 300. As an example, at an intersection near a train station, a school, or the like, there is a high possibility that a large number of moving objects such as pedestrians, bicycles, and parked vehicles will be detected. For example, when the vehicle information includes information on the detection status of an obstacle by an obstacle detection sensor or the like, the identification unit 213 may identify an intersection where the number of times an obstacle is detected is relatively high based on the vehicle information. In this case, the identification unit 213 may identify, for example, an intersection where the number of times an obstacle is detected is equal to or greater than a third threshold. The third threshold may be set to an appropriate value, for example.
The identification unit 213 may, for example, estimate an intersection where there is a relatively large number of moving objects that may be an obstacle to the travel of the vehicle 300 based on vehicle information (an intersection where there is a possibility of a relatively large number of moving objects), and if the degree of deviation 330 between the travel trajectory 310 and the reference trajectory 320 in an area including the intersection is equal to or greater than a first threshold value, identify the intersection as an intersection that requires caution when the vehicle 300 is travelling.

The identification unit 213 may identify an intersection where the degree of deviation 330 is equal to or greater than a first threshold value when it is determined based on the vehicle information that the gear of the vehicle 300 is changed from drive (forward) to reverse (backward) when the turn indicator of the vehicle 300 is operated (the turn indicator is on).
In this case, the information processing device 200 may estimate that the vehicle 300 has made too large a turn and is unable to complete the turn at the intersection, and is then moving backwards and moving forward after changing direction. In other words, the information processing device 200 may estimate that the trajectory of the vehicle 300 is one in which the vehicle 300 has been overly cautious about the inner wheel difference N.

The registration unit 214 may register the intersection identified by the identification unit 213 in the road map. The registration unit 214 can identify the position (e.g., longitude and latitude) of the intersection identified by the identification unit 213 based on the vehicle information (position information). In addition, the position information (e.g., longitude and latitude) may be recorded in the road map based on the road map stored in the storage unit 222. The registration unit 214 may identify the position of the intersection identified by the identification unit 213 in the road map by associating the position of the intersection with the position on the road map based on the position information of the intersection identified by the identification unit 213 and the position information recorded in the road map. The registration unit 214 registers the intersection identified in the road map as an intersection requiring attention when the vehicle 300 is traveling.

When the registration unit 214 registers an intersection identified by the identification unit 213 on a road map based on map information, the registration unit 214 may, for example, modify the road link (lane link) of the intersection (or an area including the intersection) for an autonomous vehicle so that the trajectory takes into account the inner wheel difference N.
Furthermore, when the registration unit 214 registers an intersection identified by the identification unit 213 in a road map based on map information, the registration unit 214 may use the intersection as an index of how easy (or difficult) it is to turn at the intersection, for example.

The output control unit 215 may, for example, control the output unit to output the intersection identified by the identification unit 213. An embodiment of the output unit may be, for example, the communication unit 221, the storage unit 222, and the display unit 223, as described above.
That is, the output control unit 215 may control the communication unit 221 to transmit information about the intersection identified by the identification unit 213 to an external device (for example, the server 100 and the vehicle 300, etc.).
The output control unit 215 may, for example, control the storage unit 222 to store information about the intersection identified by the identification unit 213 .
The output control unit 215 may, for example, control the display unit 223 to display the intersection identified by the identification unit 213 .

Furthermore, the output control unit 215 may control the output unit to output, for example, a road map on which the intersection identified by the identification unit 213 is registered.
That is, the output control unit 215 may control the communication unit 221 to transmit information about a road map in which an intersection is registered to an external device (for example, the server 100 and the vehicle 300, etc.).
The output control unit 215 may, for example, control the display unit 223 to display a road map on which intersections are registered.

[Information processing method]
Next, an information processing method according to an embodiment will be described.
FIG. 7 is a flowchart illustrating an information processing method according to an embodiment.

In step ST101, the first acquisition unit 211 acquires vehicle information related to the traveling of the vehicle 300. The first acquisition unit 211 may acquire the vehicle information from the server 100 or the vehicle 300, for example, via the communication unit 221.

In step ST102, the second acquisition unit 212 acquires the degree of deviation 330 of the driving trajectory 310 from the reference trajectory 320 based on the driving trajectory 310 of the vehicle 300 in an area including an intersection acquired based on the vehicle information acquired in step ST101 and a reference trajectory 320 in that area.
Furthermore, the second acquisition unit 212 may estimate that the vehicle 300 is turning at an intersection, for example, based on at least one of a change in the traveling speed of the vehicle 300 and a steering speed of the steering wheel of the vehicle 300. In this case, the second acquisition unit 212 may acquire a degree of deviation 330 of the traveling trajectory 310 from the reference trajectory 320, for example, when it is estimated that the vehicle 300 is turning at an intersection.
Furthermore, the second acquisition unit 212 may acquire the degree of deviation 330 of the traveling trajectory 310 from the reference trajectory 320 by using, for example, the wheel base of the vehicle 300 .

In step ST103, the identification unit 213 identifies an intersection where the degree of deviation 330 acquired in step ST102 is equal to or greater than a first threshold. In this case, the identification unit 213 may identify an intersection where the degree of deviation 330 is equal to or greater than the first threshold when the number of times the degree of deviation 330 becomes the first threshold is equal to or greater than a second threshold, based on the vehicle information of the multiple vehicles 300.
Furthermore, when there is a feature that is an obstacle to travel in an area including an intersection based on feature information, the identifying unit 213 may identify the intersection where the degree of deviation 330 is equal to or greater than a first threshold value.
In addition, the identification unit 213 may identify an intersection where the degree of deviation 330 is equal to or greater than a first threshold value when the presence of a moving object that may be an obstacle to driving is estimated in an area including an intersection based on at least one of the driving time period of the vehicle 300 and the detection status of an obstacle for the vehicle 300.

In step ST104, the registration unit 214 registers the intersection identified in step ST103 in a road map. For example, the registration unit 214 may register the intersection identified in step ST103 in a road map based on the map information stored in the memory unit 222, and store the road map (map information) after registration in the memory unit 222.

Each unit of the information processing device 200 described above may be realized as a function of a processing unit of a computer, etc. That is, the first acquisition unit 211, the second acquisition unit 212, the identification unit 213, the registration unit 214, and the output control unit 215 (control unit 210) of the information processing device 200 may be realized as a first acquisition function, a second acquisition function, an identification function, a registration function, and an output control function (control function) by the processing unit of a computer, etc.
The information processing program can cause a computer to realize each of the above-mentioned functions. The information processing program may be recorded in a non-transitory computer-readable recording medium, such as a memory, a solid-state drive, a hard disk drive, or an optical disk.
As described above, each unit of the information processing device 200 may be realized by a processing unit of a computer or the like. The processing unit or the like is, for example, configured by an integrated circuit or the like. Therefore, each unit of the information processing device 200 may be realized as a circuit constituting the processing unit or the like. That is, the first acquisition unit 211, the second acquisition unit 212, the identification unit 213, the registration unit 214, and the output control unit 215 (control unit 210) of the information processing device 200 may be realized as a first acquisition circuit, a second acquisition circuit, an identification circuit, a registration circuit, and an output control circuit (control circuit) constituting the processing unit or the like of a computer.
The communication unit 221, the storage unit 222, and the display unit 223 (output unit) of the information processing device 200 may be realized as a communication function, a storage function, and a display function (output function) including the functions of an arithmetic processing device, etc. The communication unit 221, the storage unit 222, and the display unit 223 (output unit) of the information processing device 200 may be realized as a communication circuit, a storage circuit, and a display circuit (output circuit) by being configured, for example, by an integrated circuit, etc. The communication unit 221, the storage unit 222, and the display unit 223 (output unit) of the information processing device 200 may be realized as a communication device, a storage device, and a display device (output device) by being configured, for example, by being configured by a plurality of devices.

The information processing device 200 can be configured by combining one or any two or more of the above-mentioned units.
In this disclosure, the term "information" is used, but the term "information" can be replaced with "data" and the term "data" can be replaced with "information."

[Aspects and Effects of the Present Embodiment]
Next, one aspect of this embodiment and the effects of each aspect will be described. Note that this embodiment is not limited to each aspect described below, and may be realized by appropriately combining each of the above-mentioned parts. Also, the effects described below are examples, and the effects of each aspect are not limited to those described below.

(Aspect 1)
An information processing device of one embodiment includes a first acquisition unit that acquires vehicle information regarding the vehicle's driving, a second acquisition unit that acquires a degree of deviation of the driving trajectory from a reference trajectory based on the vehicle's driving trajectory in an area including an intersection and a reference trajectory of the lane in which the vehicle is driving in the area, the degree of deviation being acquired by the second acquisition unit being equal to or greater than a first threshold value.
This allows the information processing device to identify a location (intersection) where caution is required when driving the vehicle. That is, the information processing device can identify a location (intersection) where caution is required when driving the vehicle while paying attention to the inside wheel difference when the vehicle turns left (right).
The information processing device can identify locations (intersections) where the vehicle needs to be careful about the wheel turning difference while traveling, for example, in the following situations (1) to (9), by identifying the degree of deviation between the traveling trajectory and the reference trajectory.
(1) When there is a road shoulder, gutter, utility pole, or obstacle on the left (right) corner of the intersection. (2) When there is no dividing line, guardrail, or sidewalk on the left (right) corner of the intersection. (3) When there are pedestrians, bicycles, or parked vehicles. (4) When the exit road at the intersection is relatively narrow. (5) When making a sharp left (right) turn at an intersection. (6) When the vehicle has a relatively long wheelbase. (7) When a bicycle, motorcycle, or other vehicle is traveling behind the vehicle and the vehicle needs to be moved to the left side of the lane. (8) When exiting a mechanical parking lot. (9) When entering narrow streets or parking lots where it is difficult for vehicles to enter.

(Aspect 2)
In one embodiment of the information processing device, the identification unit may identify an intersection where the degree of deviation is equal to or greater than a first threshold value when the number of times the degree of deviation becomes the first threshold value is equal to or greater than a second threshold value, based on vehicle information of a plurality of vehicles.
This enables the information processing device to identify intersections where the frequency with which vehicles are driving while paying attention to the wheel turning difference between the inside and outside of the intersections is equal to or greater than the second threshold value.

(Aspect 3)
In one embodiment of the information processing device, the identification unit may identify an intersection where the degree of deviation is equal to or greater than a first threshold value when there is a feature that is an obstacle to driving in an area including the intersection, based on feature information regarding the presence or absence of features on the road.
This enables the information processing device to identify an intersection where the presence of a feature requires the vehicle to pay attention to the wheel turning difference when traveling.

(Aspect 4)
In one embodiment of the information processing device, the identification unit may identify an intersection where the degree of deviation is equal to or greater than a first threshold value when the presence of a moving object that may be an obstacle to driving is estimated in an area including the intersection based on at least one of the vehicle's driving time period identified based on the vehicle information and the obstacle detection status for the vehicle obtained based on the vehicle information.
This enables the information processing device to identify an intersection where the vehicle needs to pay attention to the wheel radius when traveling due to the presence of a moving object that is an obstacle to the vehicle's travel.

(Aspect 5)
In the information processing device of one aspect, the second acquisition unit may acquire the degree of deviation of the traveling trajectory from the reference trajectory by using a wheel base of the vehicle identified based on the vehicle information.
This enables the information processing device to identify intersections where the vehicle needs to pay attention to the wheel difference between the inside and outside of the intersections due to the relatively long wheelbase of the vehicle.

(Aspect 6)
In one embodiment of the information processing device, the second acquisition unit may acquire the degree of deviation of the driving trajectory from a reference trajectory when it is estimated that the vehicle is turning at an intersection based on at least one of a change in the vehicle's driving speed acquired based on the vehicle information and a steering speed of the vehicle's steering wheel acquired based on the vehicle information.
This allows the information processing device to obtain the deviation degree at an intersection when it is estimated that there is a high possibility that the vehicle is turning at the intersection. In other words, the information processing device can more reliably identify the intersection.

(Aspect 7)
The information processing device of one aspect may include a storage unit that stores map information related to a road map, and a registration unit that registers the intersection identified by the identification unit in the road map.
As a result, the information processing device can provide the driver with a road map in which intersections where the vehicle needs to be careful about the inside wheel difference while driving are registered, which can be useful for the driver's driving. In this case, the information processing device can alert the user to intersections where the vehicle needs to be careful about the inside wheel difference while driving when providing route guidance, etc., and can provide driving support for the vehicle. In addition, the information processing device can correct the road link (lane link) of an intersection (area including the intersection) where the vehicle needs to be careful about the inside wheel difference while driving, thereby allowing the autonomous vehicle to travel a trajectory that takes the inside wheel difference into consideration (a trajectory according to the road link (lane link)) when turning at the intersection.

(Aspect 8)
In one aspect of the information processing method, a computer executes the following steps: a first acquisition step of acquiring vehicle information regarding the vehicle's travel; a second acquisition step of acquiring the degree of deviation of the travel trajectory from a reference trajectory based on the vehicle's travel trajectory in an area including an intersection and a reference trajectory of the lane in which the vehicle is traveling in the area, the degree of deviation being acquired by the second acquisition step being equal to or greater than a first threshold value.As a result, the information processing method can achieve the same effects as the information processing device of the aspect described above.

(Aspect 9)
One embodiment of an information processing program causes a computer to realize a first acquisition function of acquiring vehicle information regarding the vehicle's travel, a second acquisition function of acquiring the degree of deviation of the travel trajectory from a reference trajectory based on the vehicle's travel trajectory in an area including an intersection and a reference trajectory of the lane in which the vehicle is traveling in the area, the reference trajectory being acquired based on the vehicle information acquired by the first acquisition function, and an identification function of identifying an intersection where the degree of deviation acquired by the second acquisition function is equal to or greater than a first threshold value.
As a result, the information processing program can achieve the same effects as the information processing device according to the above-described aspect.

REFERENCE SIGNS LIST 1 Information processing system 100 Server 200 Information processing device 210 Control unit 211 First acquisition unit 212 Second acquisition unit 213 Identification unit 214 Registration unit 215 Output control unit 221 Communication unit 222 Storage unit 223 Display unit 300 Vehicle 310 Traveling trajectory 320 Reference trajectory 330 Deviation

Claims (8)

A first acquisition unit that acquires vehicle information related to a traveling of the vehicle;
a second acquisition unit that acquires a degree of deviation of a travel trajectory from a reference trajectory based on a travel trajectory of the vehicle in an area including an intersection and a reference trajectory of a lane in which the vehicle is traveling in the area, the reference trajectory being acquired based on the vehicle information acquired by the first acquisition unit;
an identification unit that identifies an intersection where the degree of deviation acquired by the second acquisition unit is equal to or greater than a first threshold value ,
The second acquisition unit acquires a degree of deviation of a traveling trajectory from a reference trajectory by using a wheel base of the vehicle identified based on the vehicle information.
Information processing device. The information processing device according to claim 1 , wherein the identification unit is configured to identify an intersection where the degree of deviation is equal to or greater than the first threshold when the number of times the degree of deviation becomes equal to or greater than a second threshold based on vehicle information of a plurality of vehicles. The information processing device according to claim 1 or 2, wherein the identification unit is configured to identify an intersection where a degree of deviation is equal to or greater than a first threshold value when there is a feature that is an obstacle to driving in an area including the intersection based on feature information regarding the presence or absence of features on the road. The information processing device according to any one of claims 1 to 3, wherein the identification unit identifies an intersection where the degree of deviation is equal to or greater than a first threshold value when the presence of a moving object that is an obstacle to driving is estimated in an area including an intersection based on at least one of the vehicle's driving time period identified based on the vehicle information and the obstacle detection status for the vehicle obtained based on the vehicle information. The second acquisition unit acquires a degree of deviation of the traveling trajectory from a reference trajectory when it is estimated that the vehicle is turning at an intersection based on at least one of a change in the traveling speed of the vehicle acquired based on the vehicle information and a steering speed of the steering wheel of the vehicle acquired based on the vehicle information.
The information processing device according to any one of claims 1 to 4 . A storage unit for storing map information relating to a road map;
a registration unit that registers the intersection identified by the identification unit on the road map;
The information processing device according to any one of claims 1 to 5, comprising: The computer
A first acquisition step of acquiring vehicle information related to a traveling of the vehicle;
a second acquisition step of acquiring a degree of deviation of the travel trajectory from a reference trajectory based on a travel trajectory of the vehicle in an area including an intersection and a reference trajectory of a lane in which the vehicle is traveling in the area, the reference trajectory being acquired based on the vehicle information acquired in the first acquisition step;
a specifying step of specifying an intersection where the degree of deviation obtained by the second obtaining step is equal to or greater than a first threshold value ;
The second obtaining step obtains a degree of deviation of the traveling trajectory from a reference trajectory by using a wheel base of the vehicle identified based on the vehicle information.
Information processing methods. On the computer,
A first acquisition function for acquiring vehicle information related to vehicle travel;
a second acquisition function that acquires a degree of deviation of a travel trajectory from a reference trajectory based on a travel trajectory of a vehicle in an area including an intersection and a reference trajectory of a lane in which the vehicle is traveling in the area, the reference trajectory being acquired based on the vehicle information acquired by the first acquisition function;
a specifying function for specifying an intersection where the degree of deviation obtained by the second obtaining function is equal to or greater than a first threshold value ,
The second acquisition function acquires a degree of deviation of a traveling trajectory from a reference trajectory by using a wheel base of the vehicle identified based on the vehicle information.
Information processing program.

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