Information processing device, information processing method, and information processing program

Abstract

To provide an information processing device capable of estimating the presence of obstacles, an information processing method, and an information processing program.SOLUTION: The information processing device includes: a first acquisition unit that acquires a piece of vehicle information including vehicle traveling information concerning the traveling of a vehicle; a second acquisition unit that acquires at least one traveling state of the vehicle, based on the vehicle traveling information acquired by the first acquisition unit, out of the following: when the steering angle changes toward the center of the road while the vehicle is running; when the vehicle has an operation of a direction indicator in the direction of the center of the road, when a change of slow down the running speed of the vehicle; and when the distance between the vehicle and a vehicle running ahead or behind becomes narrower; and a first estimation unit that estimates the presence of obstacles based on the traveling state of the vehicle acquired by the second acquisition unit.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] For example, when a vehicle driver sees an obstacle such as a parked vehicle ahead of the lane in which the vehicle is traveling, the driver may need to perform a driving maneuver to avoid the obstacle. In this case, if the driver knows in advance that the obstacle exists, the driver may be able to perform a driving maneuver with plenty of time to maneuver, and thus may be able to avoid an accident or the like.

[0003] Patent Document 1 discloses a device that supports the driving of a vehicle by recognizing an obstacle blocking the lane ahead of the vehicle. The device acquires point cloud data of the surrounding environment using a LiDAR mounted on the vehicle and recognizes the presence of an obstacle. In this case, the device recognizes an area where the lane is blocked by a parked vehicle that is an obstacle to the driving of the vehicle. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2021-009655 Summary of the Invention [Problem to be solved by the invention]

[0005] As described above, the device disclosed in Patent Document 1 recognizes obstacles by obtaining point cloud data using a LIDAR. However, LIDAR is not installed in many vehicles. Vehicles that are not equipped with a LIDAR cannot recognize obstacles. For this reason, it is desirable to estimate the presence of an obstacle by utilizing devices installed in as many vehicles as possible.

[0006] The present disclosure provides an information processing device, an information processing method, and an information processing program capable of estimating the presence of an obstacle. [Means for solving the problem]

[0007] An information processing device of one embodiment includes a first acquisition unit that acquires vehicle information including vehicle driving information related to the driving of the vehicle, a second acquisition unit that acquires at least one of the following driving conditions of the vehicle based on the vehicle driving information acquired by the first acquisition unit: a change in the steering angle toward the center of the road when the vehicle is driving, a change in the direction of the turn signal toward the center of the road when the vehicle is driving, a change in the vehicle's driving speed slowing down, and a change in the distance between the vehicle and a vehicle driving in front or behind narrowing; and a first estimation unit that estimates the presence of an obstacle based on the driving conditions of the vehicle acquired by the second acquisition unit. Effect of the Invention

[0008] According to one aspect, it is possible to estimate whether an obstacle is present in the traveling direction of a vehicle. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an information processing system according to an embodiment. [Diagram 2] FIG. 1 is a block diagram illustrating an information processing device according to an embodiment. [Diagram 3] FIG. 1 is a diagram for explaining an example of a road with one lane on each side. [Figure 4] FIG. 1 is a diagram for explaining an example of a road with three lanes on each side. [Diagram 5] 1 is a flowchart illustrating an information processing method according to an embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] An embodiment will be described below.

[0011] [Outline 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.

[0012] The information processing system 1 includes, for example, a vehicle 10, a server 20, and an information processing device 30. The information processing device 30 may be configured, for example, as an obstacle estimation device that estimates whether an obstacle exists in the traveling direction of the vehicle 10. The information processing device 30 may also be configured, for example, as a traffic flow estimation device that estimates whether a traffic flow disturbance will occur in the traveling direction of the vehicle 10. The information processing device 30 may also be configured, for example, as a map registration device that registers the above-mentioned estimation result in a road map. The information processing device 30 may be, for example, a server, a desktop, a laptop, a tablet, a smartphone, or the like.

[0013] The information processing device 30 acquires vehicle information generated by the vehicle 10. As an example of this case, the information processing device 30 may acquire the vehicle information from at least one selected from the server 20 and the group of the vehicle 10. Note that here, when the vehicle 10 generates the vehicle information, the vehicle information may be transmitted to the server 20 or the information processing device 30, for example. The vehicle information may include, for example, vehicle driving information related to the driving of the vehicle 10. The vehicle driving information may be, for example, probe information, CAN information, and the like. The vehicle information may also include image information generated by capturing an image in the traveling direction by an imaging unit (vehicle-mounted camera) mounted on the vehicle 10, for example. The vehicle information may also include information regarding the results of recognition of objects around the vehicle by a sensor (on-board sensor) mounted on the vehicle 10. In this case, as an example, the object may be a feature on the ground, and the information may be feature recognition information. As another example, the on-board sensor may recognize the object (feature on the ground) by using laser light. Furthermore, the vehicle information may include, for example, position information regarding the traveling position of the vehicle 10. As an example of this case, the vehicle 10 may acquire the position information using the GNSS or the like. The vehicle information may also include, for example, time information relating to the time.

[0014] The information processing device 30 acquires the driving state of the vehicle 10 based on, for example, the vehicle driving information. In this case, the information processing device 30 may acquire, for example, at least one driving state selected from the following groups (1) to (4) as the driving state of the vehicle 10. (1) When the vehicle 10 is traveling, the steering angle changes toward the center of the road. (2) When the vehicle 10 is traveling and the turn signal is operated toward the center of the road, (3) When the travel speed of vehicle 10 decreases (4) When the distance between the vehicle 10 traveling in front or behind the vehicle 10 decreases For example, the information processing device 30 may estimate that an obstacle is present when at least one traveling condition selected from the above-mentioned groups (1) to (4) is acquired.

[0015] [Details of information processing device 30] Next, the information processing device 30 according to an embodiment will be described in detail. FIG. 2 is a block diagram for explaining an information processing device 30 according to an embodiment.

[0016] The information processing device 30 includes, for example, a communication unit 331, a storage unit 332, a display unit 333, and a control unit 311. The communication unit 331, the storage unit 332, and the display unit 333 may be an embodiment of an output unit. The control unit 311 includes, for example, a first acquisition unit 312, a second acquisition unit 313, a third acquisition unit 314, a first estimation unit 315, a second estimation unit 316, a third estimation unit 317, a registration unit 318, a route guidance unit 319, and an output control unit 320. The control unit 311 may be configured by, for example, an arithmetic processing device of the information processing device 30. The control unit 311 (e.g., a calculation processing unit, etc.) may realize the functions of each unit (e.g., the first acquisition unit 312, the second acquisition unit 313, the third acquisition unit 314, the first estimation unit 315, the second estimation unit 316, the third estimation unit 317, the registration unit 318, the route guidance unit 319, and the output control unit 320, etc.) by, for example, appropriately reading and executing various programs, etc. stored in the memory unit 332, etc.

[0017] The communication unit 331 is capable of transmitting and receiving various information to and from, for example, a device (external device) outside the information processing device 30. The external device may be, for example, the server 20, the vehicle 10, and the like.

[0018] The storage unit 322 may store, for example, various information and programs. Examples of the storage unit 322 may be a memory, a solid state drive, a hard disk drive, etc. The storage unit 322 may be, for example, a storage area on a cloud, a server, etc. The storage unit 322 stores map information related to a road map. The map information may include, for example, location information such as longitude and latitude.

[0019] The display unit 333 is capable of displaying, for example, various characters, symbols, images, and the like.

[0020] The first acquisition unit 312 acquires vehicle information including vehicle driving information related to the driving of the vehicle 10. The vehicle driving information may be, for example, information related to the driving operation of the vehicle 10, or information acquired by various sensors and devices mounted on the vehicle 10.

[0021] The first acquisition unit 312 may acquire vehicle information including position information related to a traveling position of the vehicle 10. The position information may be information related to a position acquired by the vehicle 10 using, for example, GNSS or the like.

[0022] The first acquisition unit 312 may acquire vehicle information including feature recognition information related to features recognized based on the measurement results of the on-board sensor. The on-board sensor may, for example, recognize features by emitting laser light and receiving the laser light (reflected light) reflected by the features. An example of the on-board sensor may be a sensor that generates point cloud data.

[0023] The first acquisition unit 312 may acquire vehicle information including image information related to an image generated by an on-board camera. The image information is, for example, information generated by a camera (on-board camera) mounted on the vehicle 10. In this case, the on-board camera may capture, for example, an image of the traveling direction of the vehicle 10.

[0024] The second acquisition unit 313 may acquire, based on the vehicle driving information acquired by the first acquisition unit 312, at least one of the following driving conditions of the vehicle 10 in the cases (1) to (4). (1) When the vehicle 10 is traveling, the steering angle changes toward the center of the road. (2) When the vehicle 10 is traveling, the turn signal is operated toward the center of the road. (3) When the travel speed of vehicle 10 decreases (4) When the distance between the vehicle 10 traveling in front or behind the vehicle 10 decreases

[0025] Regarding (1) above The change in steering angle toward the center of the road when the vehicle 10 travels may be, for example, a change in steering angle toward the center of the road with respect to the traveling direction of the vehicle 10. That is, for example, on a road on which the vehicle 10 is required to keep to the left (for example, a road in Japan, etc.), the change in steering angle may be toward the right. In this case, for example, the steering angle of the vehicle 10 differs when the vehicle 10 changes lanes to the right and when the vehicle 10 turns right. That is, for example, the steering angle when the vehicle 10 changes lanes to the right is smaller than the steering angle when the vehicle 10 turns right. Also, for example, the steering angle when the vehicle 10 changes lanes falls within a predetermined angle range. For this reason, for example, it is possible to predefine the range of the steering angle when the vehicle 10 changes lanes.

[0026] Regarding (2) above The operation of the turn signal toward the center of the road can be obtained, for example, based on the operation direction of the turn signal (for example, operation of the turn signal toward the right).

[0027] Regarding (3) above The change in the vehicle 10's traveling speed to slow down can be obtained, for example, from the rotational speed of the tire axle or drive shaft, the speed indicated by a speedometer installed in the vehicle 10, and whether or not the driver operates the brakes.

[0028] Regarding (4) above The change in the distance to the vehicle 10 traveling ahead or behind the vehicle 10 becoming narrower can be obtained, for example, by continuously or intermittently monitoring the distance to the preceding vehicle or the following vehicle over time using an on-board sensor (such as an obstacle sensor, for example) that monitors the front and rear of the vehicle 10. Here, the on-board sensor may be mounted on the vehicle itself to obtain the distance to the preceding vehicle or the following vehicle, may be mounted on the preceding vehicle to obtain the distance to the following vehicle, or may be mounted on the following vehicle to obtain the distance to the preceding vehicle. The above-mentioned first acquisition unit 312 may acquire vehicle travel information (vehicle information) including the vehicle distance acquired by the vehicle itself, the preceding vehicle, or the following vehicle from each vehicle 10. Alternatively, the first acquisition unit 312 may acquire vehicle travel information (vehicle information) including the vehicle distance acquired by the preceding vehicle or the following vehicle via the vehicle itself.

[0029] The third acquisition unit 314 acquires facility information related to the location and business hours of a facility. The facility may be, for example, a variety of facilities including restaurants and stores that sell products or provide services. The location of the facility may be, for example, a location based on the longitude and latitude of the location of the facility. The facility information may be, for example, registered in map information or accumulated in the server 20 or the like. The third acquisition unit 314 may also acquire, for example, the location and business hours of a facility published on a communication network as facility information.

[0030] The first estimation unit 315 estimates the presence of an obstacle based on the traveling state of the vehicle 10 acquired by the second acquisition unit 313. That is, the first estimation unit 315 may estimate that an obstacle is present when the second acquisition unit 313 acquires at least one traveling state of the vehicle 10 selected from the above groups (1) to (4). Here, the first estimation unit 315 may specify a position where the presence of the obstacle is estimated based on, for example, position information included in the vehicle information.

[0031] The first estimation unit 315 may estimate the presence of an obstacle when it is estimated that a facility in operation is present within a predetermined distance from the traveling position of the vehicle 10 based on, for example, the position information acquired by the first acquisition unit 312 and the facility information acquired by the third acquisition unit 314. The first estimation unit 315 may acquire, for example, weather information related to the weather when the vehicle 10 generating the vehicle information was traveling from the server 20 or the like. The first estimation unit 315 may specify the time when the obstacle is present based on, for example, time information (vehicle information). In this case, the first estimation unit 315 may, for example, collect the estimation results for each predetermined period, and specify an area where the presence of multiple obstacles is estimated (an area including positions where the presence of a predetermined number or more obstacles is estimated) based on the day of the week, the time period, the weather, and the business status of nearby facilities. The first estimation unit 315 may specify the estimated area (position) for each link unit of the road network, or for each section unit obtained by dividing the road into units of 100 m or the like. The first estimation unit 315 may specify a position where the presence of an obstacle is estimated based on, for example, vehicle information acquired in real time and vehicle information acquired in the past.

[0032] In a section of a road where there are traffic regulations such as parking bans according to the day of the week and the time of day, the vehicle 10 may be parked outside the traffic regulation period. In this case, when estimating the presence of an obstacle according to the above-mentioned day of the week and the time of day, the first estimation unit 315 may also estimate the presence or absence of traffic regulations such as parking bans according to the day of the week and the time of day.

[0033] Furthermore, the first estimation unit 315 does not need to estimate the presence of an obstacle within an intersection based on the position information (vehicle information) and map information.

[0034] The first estimation unit 315 may estimate the presence of an obstacle when it is estimated that a facility in business is present within a predetermined distance from the traveling position of the vehicle 10 based on the position information acquired by the first acquisition unit 312 and the facility information acquired by the third acquisition unit 314. The first estimation unit 315 may specify a position where at least one selected from the above groups (1) to (4) is acquired by the first acquisition unit 312 based on the position information (vehicle information). Furthermore, the first estimation unit 315 may specify whether a facility is located within a predetermined distance from the specified position based on, for example, the specified position and facility information (position of the facility). Furthermore, the first estimation unit 315 may estimate whether a facility corresponding to the specified location is in business based on, for example, time information (facility information) and facility information (business hours of the facility). The first estimation unit 315 may estimate the presence of an obstacle when it is estimated that a facility corresponding to the specified location is in business.

[0035] The first estimation unit 315 may acquire weather information on the weather when the vehicle 10 that generated the vehicle information traveled from the server 20 or the like. The first estimation unit 315 may specify the time when the obstacle exists based on time information (vehicle information), for example. In this case, the first estimation unit 315 may, for example, collect the estimation results for each predetermined period and specify the area where the obstacle exists (the area including the position where the traffic flow is estimated to be disturbed by a predetermined number or more) based on the day of the week, the time period, the weather, and the business status of the nearby facilities. The first estimation unit 315 may specify the position where the obstacle exists for each link unit of the road network, or for each section unit obtained by dividing the road into units of 100 m or the like. The first estimation unit 315 may specify the position where the obstacle exists based on the vehicle information acquired in real time and the vehicle information acquired in the past, for example.

[0036] In addition, when the first estimation unit 315 estimates the presence of an obstacle according to the day of the week and the time period described above, for example, it is also possible to estimate the presence or absence of traffic regulations such as parking bans according to the day of the week and the time period. Furthermore, the first estimation unit 315 does not need to estimate the presence of an obstacle within an intersection based on the position information (vehicle information) and map information.

[0037] The first estimation unit 315 may estimate the presence of an obstacle based on feature recognition information acquired by the first acquisition unit 312. That is, when a feature is recognized based on a detection result of an in-vehicle sensor, for example, the first estimation unit 315 may estimate whether an obstacle exists based on the recognition result (feature recognition information).

[0038] The first estimation unit 315 may estimate the presence of an obstacle based on the image information acquired by the first acquisition unit 312. The first estimation unit 315 may estimate whether an obstacle is recorded in the image information based on, for example, a learned model that has learned the shape of the vehicle 10 and patterns of various obstacles such as poles and trees and other features, and the image information. Alternatively, the first estimation unit 315 may estimate whether an obstacle is recorded in the image information by using pattern matching based on the shape of a lane and patterns of features. In this case, for example, when the image information is information in which a moving image is recorded and information in which still images are recorded continuously at a predetermined time interval, the first estimation unit 315 can estimate whether an object recorded in the image information is stationary or moving by using frames and still images that are different in time. The first estimation unit 315 can estimate a stationary object as an obstacle by using a learned model and pattern matching.

[0039] The first estimation unit 315 may estimate whether an obstacle exists within a predetermined distance in the road width direction from the lane estimated by the third estimation unit 317 described later. In this case, the first estimation unit 315 may estimate the presence of an obstacle within a predetermined distance in the road width direction from the lane boundary line or the center line of the road. That is, the first estimation unit 315 may estimate whether an obstacle exists within a predetermined distance in the road width direction from the center line or the lane boundary line of the road (leftward on Japanese roads) of the lane estimated by the third estimation unit 317.

[0040] FIG. 3 is a diagram for explaining an example of a road with one lane on each side. FIG. 4 is a diagram for explaining an example of a road with three lanes on each side.

[0041] For example, when the lane estimated by the third estimation unit 317 is the center line 401 of a road with one lane in each direction (see FIG. 3) or the lane boundary 402a of the first lane 411 of a road with two or more lanes in each direction (see FIG. 4), the first estimation unit 315 may estimate whether an obstacle 421 is present within a predetermined distance L1, L2 from the center line 401 or the lane boundary 402a in the direction of the outer lane 403. As a specific example in this case, the predetermined distances L1, L2 may be 3.5 m or may be various other distances. Here, 3.5 m is an example, and may be appropriately set in consideration of a width that makes it easy for a vehicle to travel.

[0042] In addition, for example, when the lane estimated by the third estimation unit 317 is a lane of a road with two or more lanes on each side, the first estimation unit 315 may set the total distance obtained by adding a distance that includes the second lane 412 and the lane width of one or more lanes on the side of the center line 401 of the roadway from the second lane 412 to the above-mentioned specified distance as the specified distance L3, L4, and estimate whether there is an obstacle 421 between the lane on the side of the center line 401 of the roadway from the second lane 412 (lane boundary line 402b and center line 401 of the roadway) and the specified distance (see Figure 4). As a specific example, when the road estimated by the third estimation unit 317 is a two-lane road on each side, the first estimation unit 315 may set the total distance from the center line 401 of the roadway to the lane width of the second lane 412 plus the above-mentioned example of 3.5 m as the specified distance, and estimate whether an obstacle 421 is present between the center line 401 of the roadway and the specified distance. As another specific example, when the road estimated by the third estimation unit 317 is a road with three lanes on each side, the first estimation unit 315 may set the total distance from the lane boundary line 402b between the second lane 412 and the third lane 413 to the lane width of the second lane 412 plus the above-mentioned example of 3.5 m as a predetermined distance L3, and estimate whether an obstacle 421 is present between the lane boundary line 402b and the predetermined distance L3 (see Figure 4). As another specific example, when the road estimated by the third estimation unit 317 is a road with three lanes on each side, the first estimation unit 315 may determine the total distance from the center line 401 of the roadway to the lane widths of the second lane 412 and the third lane 413 plus the above-mentioned example of 3.5 m as a predetermined distance L4, and estimate whether an obstacle 421 is present between the center line 401 of the roadway and the predetermined distance L4 (see Figure 4).

[0043] The obstacle may be, for example, a parked vehicle, a feature, or the like that may impede the vehicle 10 when traveling along a road. The obstacle to the travel of the vehicle 10 may be, for example, a steering operation such as changing lanes, a driving operation such as slowing down, or other operations that require an operation to avoid the obstacle.

[0044] The first estimation unit 315 may estimate that an obstacle exists when the outer lane line cannot be recognized. That is, for example, when the outer lane line is estimated by the third estimation unit 317, the first estimation unit 315 may estimate that an obstacle exists when the outer lane line cannot be recognized in the image information. In this case, the first estimation unit 315 may estimate that an obstacle exists when, for example, frames and still images (images) at different times are used, and the outer lane line can be recognized in an image at a certain time t, but the outer lane line cannot be recognized in an image within a predetermined time after the time t. Furthermore, the first estimation unit 315 may estimate that an obstacle exists when, for example, the outer lane line was recognized by the third estimation unit 317 based on multiple vehicle information at the same position (approximately the same position), but the outer lane line became unrecognizable within a predetermined time from the time when the outer lane line was last recognized, and the outer lane line became recognizable within the subsequent predetermined time, that is, when the outer lane line cannot be recognized temporarily by the third estimation unit 317.

[0045] Alternatively, the first estimation unit 315 may estimate that an obstacle exists when the outer lane line cannot be recognized in the same position (same area) during a specific time period based on a plurality of image information, for example. In addition, the first estimation unit 315 may estimate that the outer roadway line has become unrecognizable due to wear or removal, for example, when the outer roadway line cannot be recognized at the same position (same area) for a relatively long period of time based on multiple image information.

[0046] The second estimation unit 316 may estimate a traffic disturbance based on the traveling state of the vehicle 10 acquired by the second acquisition unit 313. That is, the second estimation unit 316 may estimate that there is a traffic disturbance when the second acquisition unit 313 acquires the traveling state of at least one vehicle 10 selected from the above groups (1) to (4). For example, the second estimation unit 316 may estimate that there is a traffic disturbance when the first estimation unit 315 estimates the presence of an obstacle. Here, the traffic flow may be, for example, an overall flow of a plurality of vehicles, etc., which is an accumulation of the movements of a plurality of vehicles, etc. on a road. The traffic disturbance may be, unlike a case where a plurality of vehicles, etc. travel smoothly on a road, when at least one of the following occurs: a relatively large traffic volume, a relatively high traffic density, and a relatively slow traveling speed.

[0047] The second estimation unit 316 may estimate that there is a disturbance in the traffic flow when the driving state of the vehicle 10 acquired by the second acquisition unit 313 includes a driving state that is equal to or exceeds a threshold value of change or operation. For example, when the second acquisition unit 313 acquires (1) the running state of the vehicle 10 in which the steering angle changes toward the center of the road while the vehicle 10 is running (change in steering angle when the vehicle 10 changes lanes), the second estimation unit 316 may estimate that there is a disturbance in the traffic flow if there is a change in steering angle that is larger than the steering angle of the steering wheel when the vehicle 10 runs along the road (runs along the road). Here, for example, the steering angle when the vehicle 10 changes lanes is considered to be larger than the steering angle when the vehicle 10 runs along the road. For this reason, the upper limit of the change in steering angle when the vehicle 10 runs along the road may be set as the threshold A. Also, for example, the steering angle of the vehicle 10 when the vehicle 10 turns right (or left) is considered to be larger than the steering angle when the vehicle 10 changes lanes. For this reason, an upper limit threshold B (threshold A<threshold B) may also be set for the steering angle when the vehicle 10 changes lanes, and the range between the two thresholds A and B may be the change in steering angle when the vehicle 10 changes lanes. Here, the thresholds A and B may be set in advance.

[0048] In addition, when the second acquisition unit 313 acquires (2) the driving state of the vehicle 10 such as operation of the turn indicator toward the center of the road while the vehicle 10 is traveling (operation of the turn indicator when the vehicle 10 changes lanes), the second estimation unit 316 may estimate that there is a disruption in traffic flow based on the operation of the turn indicator (turn indicator on).

[0049] Furthermore, for example, when the second acquisition unit 313 acquires (3) the traveling state of the vehicle 10, which is a change in which the traveling speed of the vehicle 10 slows down, the second estimation unit 316 may estimate that there is a disturbance in the traffic flow when the traveling speed slows down to a threshold value or less based on the traveling speed just before the deceleration. Here, the threshold value may be set in advance.

[0050] Furthermore, for example, when the second acquisition unit 313 acquires (4) a traveling state of the vehicle 10 in which the distance between the vehicle 10 traveling ahead or behind the vehicle 10 is narrowing, the second estimation unit 316 may estimate that there is a disturbance in the traffic flow when the distance between the vehicle 10 becomes shorter than or equal to a threshold based on the distance between the vehicle 10 before the change in the distance between the vehicle 10 that narrowed. Here, the threshold may be set in advance.

[0051] The second estimation unit 316 may estimate that there is a traffic disturbance based on at least one of the driving conditions (1) to (4) as described above. In this case, the second estimation unit 316 may estimate that there is a traffic disturbance when, for example, one of the following (A) to (C) is met. (A) When one of the driving conditions (1) to (4) above is acquired (B) When two (or three) of the above (1) to (4) driving conditions are acquired (C) When all of the driving conditions (1) to (4) above are acquired

[0052] The third estimation unit 317 may estimate lanes on a road based on image information acquired by the first acquisition unit 312. The third estimation unit 317 may estimate lanes on a road recorded in image information based on, for example, a trained model that has learned the shape, color, and the like of lanes and the like, and the image information. Alternatively, the third estimation unit 317 may estimate lanes on a road recorded in image information by using, for example, pattern matching based on a pattern of the shape, etc. of the lanes.

[0053] The third estimation unit 317 may be capable of estimating at least one of a lane boundary line and a roadway centerline as the lane. For example, the lane may be the roadway centerline 401 when the road has one lane on each side (see FIG. 3), and may be the roadway centerline 401 or the lane boundary line 402 when the road has two or more lanes on each side (see FIG. 4). Here, for example, the lane boundary line 402 when the road has two or more lanes on each side may be the lane boundary line 402a of the first lane 411. Furthermore, the third estimation unit 317 may estimate the outer roadway line 403 (FIGS. 3 and 4) as the lane. That is, the third estimation unit 317 may estimate at least one of the lane boundary line 402 and the roadway center line 401, and the outer roadway line 403 as the lane.

[0054] The registration unit 318 may register a position based on the estimation in the map information in at least one of the cases where the first estimation unit 315 estimates the presence of an obstacle and the second estimation unit 316 estimates that there is a traffic flow disruption. That is, the registration unit 318 may register, for example, a position where the presence of an obstacle is estimated in a road map (map information). Also, the registration unit 318 may register, for example, a position where there is an estimated traffic flow disruption in a road map (map information).

[0055] The registration unit 318 may rank the ease of driving the vehicle 10 based on the number of cases where the presence of an obstacle is estimated and the number of cases where the traffic flow is estimated to be disrupted, and may register the ranking in the road map (map information) in association with the estimated position. For example, when the number of cases is relatively large, the registration unit 318 may rank the vehicle 10 as being more difficult to drive. Also, when the number of cases is relatively small, the registration unit 318 may rank the vehicle 10 as being more easy to drive.

[0056] In this case, the registration unit 318 may rank the ease of travel for the vehicle 10 according to the number of lanes (the number of lanes on one side) of the road at the position where the presence of the obstacle is estimated and the position where the traffic flow is estimated to be disturbed, and may register the ranking in the road map (map information) in association with the estimated position. For example, when the number of lanes described above is relatively small, the registration unit 318 may rank the vehicle 10 as being more difficult to travel on. Also, for example, when the number of lanes described above is relatively large, the registration unit 318 may rank the vehicle 10 as being more easy to travel on.

[0057] Furthermore, the registration unit 318 may rank the ease of travel for the vehicle 10 according to the width of the road (e.g., the width of the first lane) at the position where the presence of an obstacle is estimated and at the position where the traffic flow is estimated to be disturbed, and may register the ranking in the road map (map information) in association with the estimated position. For example, when the road width described above is relatively narrow, the registration unit 318 may rank the road as being more difficult for the vehicle 10 to travel on. For example, when the road width described above is relatively wide, the registration unit 318 may rank the road as being more easy for the vehicle 10 to travel on.

[0058] The registration unit 318 may also register the estimation results (presence of obstacles and traffic disturbances) according to the day of the week, time period, weather, and business status of the facility in the road map (map information). This allows the registration unit 318 to provide information on whether it is constantly difficult to drive the vehicle 10 or whether it is temporarily difficult to drive the vehicle 10 to a user (e.g., a driver, etc.) who uses the road map (map information).

[0059] The route guidance unit 319 may provide route guidance from a departure point to a destination point using a road map in which at least one of a position where an obstacle is estimated to exist and a position where traffic flow is disrupted is registered. The route guidance unit 319 may be, for example, a navigation function. For example, when receiving a request for route guidance from a departure point to a destination (route guidance request), the route guidance unit 319 may search for a detour route that avoids the position where an obstacle is estimated to exist and the position where traffic flow is disrupted, and provide route guidance using the detour route. In addition, when receiving a route guidance request, the route guidance unit 319 may provide route guidance such as traveling in a lane (for example, other lanes except the first lane in the case of a road with two or more lanes in each direction) that avoids the position where an obstacle is estimated to exist and the position where traffic flow is disrupted. Furthermore, for example, when the registration unit 318 registers a ranking of the ease of driving of the vehicle 10 in a road map (map information), the route guidance unit 319 may provide route guidance such that the vehicle 10 travels along a road (or a lane) on which a ranking for ease of driving is registered. Here, the route guidance unit 319 may receive a route guidance request from a user terminal (not shown) via the communication unit 331. The user terminal may be, for example, a terminal used by a user of the information processing device 30. In this case, the user terminal may be, for example, a portable terminal (for example, a laptop, a tablet, a smartphone, etc.). The route guidance unit 319 may output information related to route guidance to the user terminal via the communication unit 331, for example.

[0060] For example, when vehicle information is acquired in real time, the route guidance unit 319 may acquire information on the ease of driving or the difficulty of driving the vehicle 10, estimated using the vehicle information, in almost real time, and perform route guidance. In this case, the control unit 311 (for example, the first to third estimation units 315 to 317, etc.) may perform estimation processing using information obtained from the current situation information, without performing statistical estimation processing using the vehicle driving information. As an example, the route guidance unit 319 may acquire a guide route based on the use of statistical estimation processing in a route search when the vehicle 10 departs, and perform route guidance after the vehicle 10 departs that takes into account the above-mentioned estimation processing in almost real time. That is, for example, the route guidance unit 319 may guide the vehicle to a lane that is easy to drive on based on estimation in the route guidance after departure. Furthermore, for example, the route guidance unit 319 may acquire a detection result of a sensor (vehicle-mounted sensor) mounted on the vehicle, and guide the vehicle to a lane that is easy to drive on according to the estimation result in almost real time based on the result.

[0061] For example, when vehicle information is acquired in real time, the route guidance unit 319 may provide route guidance using the estimation results registered in the road map in almost real time by the registration unit 318. In this case, the registration unit 318 may register the degree of ease of driving for the vehicle 10 in the road map (map information) in relation to the link cost of the route search. For example, the route guidance unit 319 may present a guide route candidate that prioritizes the degree of ease of driving for the vehicle 10.

[0062] In addition, the route guidance unit 319 can provide route guidance for both a manned vehicle and an unmanned vehicle, for example. In this case, for example, when the vehicle 10 is set to an automatic driving mode, a driving assistance mode, or the like, the route guidance unit 319 may change the guidance route according to the degree of ease of driving ranked in the road map (map information) by the registration unit 318. In addition, for example, when the vehicle 10 is set to an automatic driving mode, a driving assistance mode, or the like, the route guidance unit 319 may select each control mode such as the automatic driving mode and the driving assistance mode, or may switch between those control modes, according to the degree of ease of driving ranked in the road map (map information) by the registration unit 318.

[0063] In addition, the route guidance unit 319 may provide guidance for traveling on a road, for example, by using a road map in which at least one of a position where an obstacle is estimated to exist and a position where traffic flow is disrupted is registered. For example, when the vehicle 10 travels along a road, the route guidance unit 319 may estimate whether an obstacle exists on the route (road) to be traveled, by using a road map of the route (road) to be traveled. That is, the route guidance unit 319 may estimate whether traffic flow is disrupted on the route to be traveled, by using a road map, for example. For example, when it is estimated that an obstacle exists (traffic flow is disrupted) on the route (road) to be traveled, the route guidance unit 319 may present a lane that is easy to travel on. That is, the route guidance unit 319 may provide guidance to take a workaround such as changing lanes in advance before reaching a position where an obstacle exists (a position where traffic flow is disrupted). For example, the route guidance unit 319 may provide the above-mentioned guidance whether the vehicle 10 is a manned vehicle or an unmanned vehicle. As an example, the route guidance unit 319 may control the traveling of the vehicle so that avoidance measures such as lane changing are taken in advance, or may perform driving assistance for the traveling of the vehicle.

[0064] The route guidance unit 319 may provide route guidance using, for example, characters, symbols, images, and sounds.

[0065] The output control unit 320 may control the output unit to output information indicating that the first estimating unit 315 has estimated the presence of an obstacle and its estimated position. The output control unit 320 may control the output unit to output the information that the second estimating unit 316 has estimated that there is a traffic disturbance and its estimated location. The output control unit 320 may control the output unit to output a road map whose position is registered by the registration unit 318 . Here, the output unit may be a communication unit 331, a storage unit 332, a display unit 333, and the like.

[0066] That is, the output control unit 320 may control the communication unit 331 to transmit, for example, the above-mentioned estimation result and position, and at least one selected from the group of road maps to an external device. Here, the external device may be, for example, the server 20, the vehicle 10, a user terminal (not shown), etc. In this case, the user terminal may be, for example, a desktop, a laptop, a tablet, a smartphone, etc. Furthermore, the output control unit 320 may control the storage unit 332 to store at least one selected from the group of the above-mentioned estimation result and position, and a road map, for example. Furthermore, the output control unit 320 may control the display unit 333 to display at least one selected from the group of the above-mentioned estimation result and position, and a road map, for example.

[0067] [Information processing method] Next, an information processing method according to an embodiment will be described. FIG. 5 is a flowchart illustrating an information processing method according to an embodiment.

[0068] In step ST101, the first acquisition unit 312 acquires vehicle information. The vehicle information may include at least one piece of information selected from the group of image information, feature recognition information, vehicle driving information, and position information, for example.

[0069] In step ST102, the third estimation unit 317 estimates lanes on the road based on the image information acquired in step ST101. In this case, the third estimation unit 317 may be capable of estimating at least one of a lane boundary line and a roadway centerline as the lane. The third estimation unit 317 may also estimate at least one of a lane boundary line and a roadway centerline, and an outer roadway line as the lane.

[0070] In step ST103, the first estimation unit 315 may estimate the presence of an obstacle based on the traveling state of the vehicle 10 acquired by the second acquisition unit 313. Here, the second acquisition unit 313 may acquire at least one of the following traveling conditions of the vehicle 10 in the cases (1) to (4) based on the vehicle traveling information acquired in step ST101. (1) When the vehicle 10 is traveling, the steering angle changes toward the center of the road. (2) When the vehicle 10 is traveling, the turn signal is operated toward the center of the road. (3) When the travel speed of vehicle 10 decreases (4) When the distance between the vehicle 10 traveling in front or behind the vehicle 10 decreases

[0071] The first estimation unit 315 may also estimate whether an obstacle exists within a predetermined distance in the road width direction from the lane (e.g., lane boundary line or roadway center line, etc.) estimated in step ST102. The first estimation unit 315 may also estimate whether an obstacle exists based on the image information acquired in step ST101. The first estimation unit 315 may also estimate whether an obstacle exists based on the feature recognition information in step ST101. The first estimation unit 315 may estimate that an obstacle exists when the outer roadway line cannot be recognized.

[0072] Here, the third acquisition unit 314 may acquire facility information. In this case, the first estimation unit 315 may estimate that there is a disruption in traffic flow if it is estimated that there is a facility that is open within a specified distance from the traveling position of the vehicle 10 based on the location information acquired in step ST101 and the facility information acquired by the third acquisition unit 314.

[0073] In step ST104, the second estimation unit 316 may estimate a disturbance in traffic flow based on the traveling state of the vehicle 10 acquired by the second acquisition unit 313. The second estimation unit 316 may estimate that there is a disturbance in traffic flow when the traveling state of the vehicle 10 acquired by the second acquisition unit 313 includes a traveling state that is equal to or exceeds a threshold amount of change or operation.

[0074] Here, the third acquisition unit 314 may acquire facility information. In this case, the second estimation unit 316 may estimate that there is a disruption in traffic flow if it is estimated that there is a facility that is open within a specified distance from the traveling position of the vehicle 10 based on the location information acquired in step ST101 and the facility information acquired by the third acquisition unit 314. For example, when a facility is open, it is expected that vehicles will park in a relatively close area from the facility. In such a case, traffic flow may be disrupted in order to avoid the parked vehicles. Therefore, the second estimation unit 316 can estimate whether there is a disruption in traffic flow depending on the business status of the facility.

[0075] In step ST105, when at least one of the cases where the presence of an obstacle is estimated in step ST103 and the case where the traffic flow is estimated to be disrupted in step ST104, the registration unit 318 registers the position based on the estimation in the map information.

[0076] In step ST106, the route guidance unit 319 performs route guidance from the departure point to the arrival point by using the road map in which at least one of the estimation results (e.g., positions, etc.) in step ST103 and step ST104 is registered in step ST105. Note that, depending on the embodiment, the process in step ST106 may not be performed.

[0077] Each unit of the information processing device 30 described above may be realized as a function of an arithmetic processing device of a computer, etc. That is, the first acquisition unit 312, the second acquisition unit 313, the third acquisition unit 314, the first estimation unit 315, the second estimation unit 316, the third estimation unit 317, the registration unit 318, the route guidance unit 319, and the output control unit 320 (control unit 311) of the information processing device 30 may be realized as a first acquisition function, a second acquisition function, a third acquisition function, a first estimation function, a second estimation function, a third estimation function, a registration function, a route guidance function, and an output control function (control function), respectively, by an arithmetic processing device 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 30 may be realized by an arithmetic processing device of a computer or the like. The arithmetic processing device or the like is configured by, for example, an integrated circuit or the like. Therefore, each unit of the information processing device 30 may be realized as a circuit constituting the arithmetic processing device or the like. That is, the first acquisition unit 312, the second acquisition unit 313, the third acquisition unit 314, the first estimation unit 315, the second estimation unit 316, the third estimation unit 317, the registration unit 318, the route guidance unit 319, and the output control unit 320 (control unit 311) of the information processing device 30 may be realized as a first acquisition circuit, a second acquisition circuit, a third acquisition circuit, a first estimation circuit, a second estimation circuit, a third estimation circuit, a registration circuit, a route guidance circuit, and an output control circuit (control circuit) constituting the arithmetic processing device of a computer or the like. The communication unit 331, the storage unit 332, and the display unit 333 (output unit) of the information processing device 30 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 331, the storage unit 332, and the display unit 333 (output unit) of the information processing device 30 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 331, the storage unit 332, and the display unit 333 (output unit) of the information processing device 30 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.

[0078] The information processing device 30 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."

[0079] [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. Also, each aspect may, for example, achieve at least one of the effects described below.

[0080] (Aspect 1) An information processing device of one embodiment includes a first acquisition unit that acquires vehicle information including vehicle driving information related to the driving of the vehicle, a second acquisition unit that acquires at least one of the following driving conditions of the vehicle based on the vehicle driving information acquired by the first acquisition unit: a change in the steering angle toward the center of the road when the vehicle is driving, a change in the direction of the turn signal toward the center of the road when the vehicle is driving, a change in the vehicle's driving speed slowing down, and a change in the distance between the vehicle and a vehicle driving in front or behind narrowing; and a first estimation unit that estimates the presence of an obstacle based on the driving conditions of the vehicle acquired by the second acquisition unit. When an obstacle is present, the driver of the vehicle is expected to perform an operation to avoid the obstacle. Therefore, when the information processing device acquires the above-mentioned driving state (predetermined driving information), the information processing device estimates that an obstacle is present, and can perform more accurate estimation. In addition, when the information processing device estimates the presence of an obstacle using the vehicle driving information, the information processing device can reduce the dependency on image analysis processing using only image information, and can reduce the processing load. In addition, since the vehicle travel information is acquired from a relatively large number of vehicles, the information processing device can estimate the presence of an obstacle based on the vehicle travel information acquired using devices mounted on a large number of vehicles. The information processing device can provide driving assistance for both manned and unmanned vehicles by estimating the presence of an obstacle.

[0081] (Aspect 2) The information processing device of one aspect may further include a second estimation unit that estimates a traffic disturbance based on the vehicle traveling state acquired by the second acquisition unit. When an obstacle is present on the road, it is considered that the traffic flow of vehicles will be disrupted in order to avoid the obstacle. At that time, it is considered that the vehicles will be in the above-mentioned predetermined running state. Therefore, the information processing device can estimate the traffic flow disruption based on the running state of the vehicles. The information processing device can provide driving assistance to both manned and unmanned vehicles by estimating traffic flow disruptions.

[0082] (Aspect 3) In one embodiment of the information processing device, the second estimation unit may estimate that there is a disruption in traffic flow when the vehicle driving condition acquired by the second acquisition unit includes a driving condition that is greater than or equal to a threshold change amount or operation. It is considered that the driving operation to avoid an obstacle requires a larger amount of driving operation and a larger amount of change in the driving state compared to when the vehicle is traveling along the road (following the road). Therefore, the information processing device can estimate that there is a traffic disturbance when the driving state has a threshold amount of change or operation or more for the above-mentioned predetermined driving state.

[0083] (Aspect 4) An information processing device of one embodiment may include a third acquisition unit that acquires facility information regarding the location and business hours of the facility, the first acquisition unit acquires vehicle information including location information regarding the vehicle's traveling location, and the first estimation unit may estimate the presence of an obstacle when it is estimated that there is a facility that is open within a predetermined distance from the vehicle's traveling location based on the location information acquired by the first acquisition unit and the facility information acquired by the third acquisition unit. For example, when a facility is open, it is expected that vehicles will be parked in a relatively close area from the facility. Therefore, the information processing device can estimate whether there is a disruption in traffic flow depending on the business status of the facility.

[0084] (Aspect 5) In one embodiment of the information processing device, the first acquisition unit acquires vehicle information including feature recognition information regarding features recognized based on measurement results of an on-board sensor, and the first estimation unit may estimate the presence of an obstacle based on the feature recognition information acquired by the first acquisition unit. In this way, the information processing device can estimate the presence of an obstacle more accurately by further utilizing the feature recognition results by the vehicle-mounted sensor. Also, when the information processing device estimates the presence of an obstacle by further utilizing the feature recognition information, it can reduce the dependency on image analysis processing using image information, thereby reducing the processing load.

[0085] (Aspect 6) In one embodiment of the information processing device, a first acquisition unit acquires vehicle information including image information regarding an image generated by an on-board camera, and the information processing device further includes a third estimation unit that estimates lanes on a road based on the image information acquired by the first acquisition unit, and the first estimation unit may estimate whether an obstacle exists within a predetermined distance in the road width direction from the lane estimated by the third estimation unit. The information processing device may estimate the presence of an obstacle by using image information generated by an on-board camera. In recent years, on-board cameras have been used for driving recorders and Vlog (Video Blog) shooting, and are being installed in more and more vehicles. Therefore, the information processing device acquires image information by using, for example, an on-board camera, which is a more general-purpose device, and is therefore able to acquire more image information, and can estimate the presence of an obstacle not only on roads with relatively high traffic volume, but also on roads with relatively low traffic volume.

[0086] (Aspect 7) In the information processing device of the aspect, the first estimation unit may estimate the presence of an obstacle based on the image information acquired by the first acquisition unit. This allows the information processing device to estimate the presence of an obstacle by utilizing image information generated by the vehicle-mounted camera.

[0087] (Aspect 8) In one embodiment of the information processing device, the third estimation unit may be capable of estimating at least one of a lane boundary line and a road center line as the lane, and the first estimation unit may be configured to estimate the presence of an obstacle within a predetermined distance in the road width direction from the lane boundary line or the road center line. This enables the information processing device to estimate the presence of an obstacle based on the lane boundary lines and the center line of the road.

[0088] (Aspect 9) In the information processing device of one aspect, the third estimation unit may estimate an outer lane as the lane, and the first estimation unit may estimate that an obstacle is present when the outer lane cannot be recognized. If the outer lane line cannot be recognized, it is presumed that a vehicle (including a motorcycle) is parked on the outer lane line, or if the outer lane line cannot be recognized, it is presumed that an obstacle exists, thereby enabling more accurate estimation.

[0089] (Aspect 10) An information processing device of one embodiment may include a memory unit that stores map information regarding a road map, and a registration unit that registers a position based on the estimation in the map information when at least one of a first estimation unit estimates the presence of an obstacle and a second estimation unit estimates that there is a disruption in traffic flow. The information processing device can register locations where it is difficult for a vehicle to travel in a road map (map information). The information processing device can improve user convenience by providing the road map (map information) to a user (e.g., a driver, etc.).

[0090] (Aspect 11) An information processing device according to one embodiment may include a route guidance unit that provides route guidance from a departure point to a destination using a road map in which at least one of locations where the presence of an obstacle is estimated and locations where traffic flow is disrupted is registered. The information processing device can provide route guidance using roads that are easier for a vehicle to travel on. This can reduce the burden on the driver in relation to driving, and can prevent accidents and the like from occurring.

[0091] (Aspect 12) An information processing device according to one embodiment may include a route guidance unit that provides guidance when traveling on roads using a road map in which at least one of locations where the presence of obstacles is estimated and locations where traffic flow is disrupted is registered. As a result, even when the vehicle is driving autonomously and following a road, the information processing device can use a road map of the planned route to estimate whether there is an obstacle on the planned route, i.e., whether there is a location on the route where traffic flow will be disrupted, and if there is an obstacle (where traffic flow is disrupted), can take avoidance measures such as changing lanes in advance.

[0092] (Aspect 13) In one aspect of the information processing method, a computer executes a first acquisition step of acquiring vehicle information including vehicle driving information related to the driving of the vehicle, a second acquisition step of acquiring at least one of the following driving conditions of the vehicle based on the vehicle driving information acquired by the first acquisition step: a change in the steering angle toward the center of the road when the vehicle is driving, a change in the turn signal toward the center of the road when the vehicle is driving, a change in the vehicle's driving speed slowing down, and a change in the distance between the vehicle and a vehicle driving in front or behind narrowing; and a first estimation step of estimating the presence of an obstacle based on the driving conditions of the vehicle acquired by the second acquisition step. As a result, the information processing method can achieve the same effects as the information processing device according to the above-described aspect.

[0093] (Aspect 14) An information processing program of one embodiment causes a computer to realize a first acquisition function that acquires vehicle information including vehicle driving information regarding the driving of the vehicle, a second acquisition function that acquires at least one of the following driving conditions of the vehicle based on the vehicle driving information acquired by the first acquisition function: a change in the steering angle toward the center of the road when the vehicle is driving, a change in the turn signal toward the center of the road when the vehicle is driving, a change in the vehicle's driving speed slowing down, and a change in the distance between the vehicle and a vehicle driving in front or behind narrowing; and a first estimation function that estimates the presence of an obstacle based on the driving condition of the vehicle acquired by the second acquisition function. As a result, the information processing program can achieve the same effects as the information processing device according to the above-described aspect. [Explanation of symbols]

[0094] 1. Information Processing Systems 10 Vehicles 20 Servers 30 Information processing device 311 Control Unit 312 First acquisition part 313 Second Acquisition Department 314 Third Acquisition Department 315 1st estimation part 316 Second Estimation Department 317 Third Estimation Department 318 Registration Department 319 Route Guidance Department 320 Output control section 331 Communications Department 332 Storage section 333 Display section

Claims

1. A first acquisition unit that acquires vehicle information including vehicle driving information related to the driving of the vehicle and position information related to a driving position of the vehicle; a second acquisition unit that acquires at least one of the following vehicle driving conditions based on the vehicle driving information acquired by the first acquisition unit: a change in steering angle toward the center of the road while the vehicle is driving, a change in a vehicle speed that slows down, and a change in a vehicle distance that narrows between the vehicle and a vehicle driving ahead or behind the vehicle; a third acquisition unit that acquires facility information related to a location and business hours of the facility; a first estimation unit which estimates the presence of an obstacle based on the vehicle traveling state acquired by the second acquisition unit, and which estimates the presence of an obstacle when it is estimated that a facility in operation is present within a predetermined distance from the vehicle traveling position based on the position information acquired by the first acquisition unit and facility information acquired by the third acquisition unit; a second estimation unit that estimates a traffic disturbance based on the vehicle traveling state acquired by the second acquisition unit; An information processing device comprising:

2. The second estimation unit estimates that a traffic flow is disturbed when a vehicle driving state acquired by the second acquisition unit includes a driving state having a change amount or operation equal to or greater than a threshold value. The information processing device according to claim 1 .

3. The first acquisition unit acquires vehicle information including feature recognition information regarding features recognized based on a measurement result of an on-board sensor, The first estimation unit estimates the presence of an obstacle based on the feature recognition information acquired by the first acquisition unit.

3. The information processing device according to claim 1 or 2.

4. The first acquisition unit acquires vehicle information including image information relating to an image generated by an in-vehicle camera, The information processing device further includes a third estimation unit that estimates lanes on a road based on the image information acquired by the first acquisition unit, The first estimation unit estimates whether an obstacle is present within a predetermined distance in a road width direction from the lane estimated by the third estimation unit.

4. The information processing device according to claim 1.

5. The first estimation unit estimates the presence of an obstacle based on the image information acquired by the first acquisition unit. The information processing device according to claim 4.

6. the third estimation unit is capable of estimating, as a lane, at least one of a lane boundary line between adjacent lanes of a road having a plurality of lanes on one side and a roadway centerline closest to an oncoming lane of a road having one or a plurality of lanes on one side; The first estimation unit estimates the presence of an obstacle within a predetermined distance in a road width direction from a lane boundary line or a center line of a road.

6. The information processing device according to claim 4 or 5.

7. The third estimation unit estimates, as a lane, an outer side line of a roadway closest to a shoulder of a road having one or more lanes on one side, The first estimation unit estimates that an obstacle is present when an outer roadway line cannot be recognized.

7. The information processing device according to claim 4.

8. A storage unit for storing map information relating to a road map; a registration unit that registers a position based on the estimation in map information when at least one of the first estimation unit estimates the presence of an obstacle and the second estimation unit estimates the presence of a disturbance in traffic flow; The information processing device according to any one of claims 1 to 7, comprising:

9. A route guidance unit provides route guidance from a departure point to a destination using the map information on a road map in which at least one of positions where an obstacle is estimated to exist and positions where traffic flow is disrupted is registered. The information processing device according to claim 8.

10. A route guidance unit is provided that uses the map information on a road map in which at least one of positions where the presence of an obstacle is estimated and positions where traffic flow is disrupted is registered, to provide guidance when traveling on the road. The information processing device according to claim 8.

11. The computer A first acquisition step of acquiring vehicle information including vehicle driving information related to the driving of the vehicle and position information related to a driving position of the vehicle; a second acquisition step of acquiring at least one of the following vehicle driving conditions based on the vehicle driving information acquired by the first acquisition step: a change in steering angle toward the center of the road while the vehicle is driving, a change in a vehicle speed that slows down, and a change in a vehicle distance that narrows between the vehicle and a vehicle driving ahead or behind the vehicle; a third acquisition step of acquiring facility information related to the location and business hours of the facility; a first estimation step of estimating the presence of an obstacle based on the vehicle's traveling state acquired in the second acquisition step, and estimating the presence of an obstacle when it is estimated that a facility in operation is present within a predetermined distance from the vehicle's traveling position based on the position information acquired in the first acquisition step and the facility information acquired in the third acquisition step; a second estimation step of estimating a traffic flow disturbance based on the vehicle traveling state acquired in the second acquisition step; An information processing method for performing the above.

12. On the computer, A first acquisition function that acquires vehicle information including vehicle driving information related to the driving of the vehicle and position information related to the driving position of the vehicle; a second acquisition function for acquiring at least one of the following vehicle driving conditions based on the vehicle driving information acquired by the first acquisition function: when the steering angle changes toward the center of the road while the vehicle is driving, when a turn signal is operated toward the center of the road while the vehicle is driving, when the vehicle's driving speed changes to slow down, and when the distance between the vehicle and a vehicle driving ahead or behind the vehicle changes to narrow; A third acquisition function for acquiring facility information related to the location and business hours of the facility; a first estimation function for estimating the presence of an obstacle based on the vehicle's traveling state acquired by the second acquisition function, and estimating the presence of an obstacle when it is estimated that a facility in operation is present within a predetermined distance from the vehicle's traveling position based on the location information acquired by the first acquisition function and facility information acquired by the third acquisition function; A second estimation function that estimates a traffic flow disturbance based on the vehicle running state acquired by the second acquisition function; An information processing program that realizes this.

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