Estimation method, estimation device, and estimation program

Abstract

The present invention estimates the cause of a vehicle queue. This estimation method for estimating the cause of a vehicle queue comprises: a step for acquiring sensor information obtained by a sensor mounted on a first vehicle that is a vehicle in a vehicle queue, and / or sensor information obtained by a sensor mounted on a second vehicle; a step for acquiring location information about the location where the first vehicle that obtained the sensor information is located; and a step for estimating the cause of the vehicle queue using the sensor information and the location information. The estimating step estimates using one of: information about a facility that is located in the vicinity of the first vehicle and is searched for from the location information; information about a land object; information indicating the state of the first vehicle as estimated from the sensor information; information that relates to an object located ahead of the first vehicle, and that is included in the sensor information; and information about a road that affects travel and is searched for from the location information.

Description

[Technical field]

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

[0002] There is known a situation recognition technology that detects the occurrence of a traffic jam or other such traffic convoy by analyzing images from surveillance cameras installed on general roads, expressways, etc. and recognizing road conditions (for example, Non-Patent Document 1 below). This technology makes it possible to detect the occurrence of a traffic convoy at low cost and in real time. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] "Development of traffic image analysis technology using image recognition by machine learning"[Retrieved March 16, 2020], Internet (URL: https: / / pr.fujitsu.com / jp / news / 2016 / 10 / 18-2.html) Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the case of a fixed surveillance camera, the shooting range is limited by the installation position and shooting direction, and it is only possible to detect the occurrence of a motorcade within the shooting range. Furthermore, the above-mentioned Non-Patent Document 1 does not mention any estimation of the cause of the motorcade.

[0005] In addition, even if one tries to estimate the cause of the motorcade using the technology described in Non-Patent Document 1 above, if the cause of the motorcade is outside the surveillance camera's range (for example, further beyond the range), it is naturally impossible to estimate the cause of the motorcade.

[0006] The present disclosure aims to estimate the cause of a convoy. [Means for solving the problem]

[0007] One aspect of the present disclosure teeth A method for estimating a cause of a traffic jam using a sensor mounted on a vehicle, comprising the steps of: a step of identifying, when the generation position of the motorcade is determined, a vehicle located at the front of the motorcade, vehicles belonging to the motorcade, vehicles traveling in a lane opposite to the lane in which the motorcade has occurred, and vehicles traveling in a lane adjacent to the lane in which the motorcade has occurred; The above-specified Sensor information acquired by sensors installed in the vehicle of obtaining the The sensor information is acquired Identified acquiring location information of a vehicle; and estimating a cause of the convoy using the sensor information and the position information; The estimating step includes: said location information and the sensor information The above is explored further. Identified Located near the vehicle Data on driving rules, Facility information, local information, or the above Location information and the sensor information The estimation is made using either information on roads that affect driving, or information on roads that are searched for more precisely. Effect of the Invention

[0008] According to the present disclosure, the cause of the motorcade can be inferred. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an example of a system configuration of an information providing system. [Diagram 2] FIG. 2 is a diagram showing an application example of the information providing system. [Diagram 3] FIG. 3 is a diagram illustrating an example of a hardware configuration of the vehicle queue cause estimating device. [Figure 4] FIG. 4 is a diagram illustrating an example of a functional configuration of the vehicle queue cause estimating device. [Diagram 5] FIG. 5 is a first diagram showing an example of the position information and the video information. [Figure 6]FIG. 6 is a second diagram showing an example of the position information and the video information. [Figure 7] FIG. 7 is a flowchart showing the flow of the process of estimating the cause of a traffic queue. [Figure 8] FIG. 8 is a diagram illustrating an example of a functional configuration of an in-vehicle system of a target vehicle. [Figure 9] FIG. 9 is a flowchart showing the flow of the information providing process. [Figure 10] FIG. 10 is a first diagram showing another application example to which the information provision system can be applied. [Figure 11] FIG. 11 is a second diagram showing another application example to which the information provision system can be applied. [Figure 12] FIG. 12 is a third diagram showing another application example to which the information provision system can be applied. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, each embodiment will be described with reference to the accompanying drawings. In this specification and the drawings, components having substantially the same functional configurations are denoted by the same reference numerals, and redundant description will be omitted.

[0011] [First embodiment] <System configuration of the information provision system> First, a system configuration of an entire information provision system having an information provision device according to a first embodiment will be described. FIG. 1 is a diagram showing an example of a system configuration of the information provision system. As shown in FIG. 1, the information provision system 100 has a vehicle procession cause estimation device 110, in-vehicle systems 120_1 to 120_n, an in-vehicle system 121_1, and an in-vehicle system 122_1. The vehicle procession cause estimation device 110 and the in-vehicle systems 120_1 to 122_1 are communicatively connected via a network 160.

[0012] The vehicle queue cause estimation device 110 detects the occurrence of a vehicle queue using a known method. A vehicle queue refers to a state in which two or more vehicles are lined up, and includes various causes such as a so-called traffic jam, a state in which vehicles are lined up waiting for a traffic light to turn right or left, a state in which vehicles are lined up after parking on the road, a state in which vehicles are lined up to enter a facility, and the like. In addition, each vehicle in the vehicle queue does not need to be stopped (0 km / h), but may be in a state in which it is traveling at a speed slower than a predetermined value compared to vehicles not in the vehicle queue.

[0013] Furthermore, when the vehicle motorcade cause estimation device 110 detects the occurrence of a vehicle motorcade, it determines the occurrence position of the vehicle motorcade and communicates with the in-vehicle systems mounted on each vehicle at the determined occurrence position (and its surroundings) to obtain position information and video information from each vehicle. Note that the occurrence position of the vehicle motorcade may be the occurrence area.

[0014] In addition, the vehicles from which the vehicle queue cause estimation device 110 acquires position information and video information when it detects the occurrence of a vehicle queue include, for example, The vehicle at the front of the convoy (leading vehicle of the convoy), - The second or third vehicle from the front of the convoy (vehicles near the front of the convoy), Other vehicles belonging to the motorcade (motorcade vehicles), - Vehicles traveling in the opposite lane to the lane in which the queue occurs (oncoming vehicles), - A vehicle (observation vehicle) traveling in a lane adjacent to the lane in which the convoy occurs; etc. The reason why the above vehicles include motorcade vehicles is, for example, as follows. That is, when there are multiple causes of a motorcade, the multiple causes can be estimated by using position information and video information acquired from the motorcade vehicles in addition to position information and video information acquired from the leading vehicle of the motorcade and vehicles surrounding the leading vehicle of the motorcade. Also, when a vehicle itself is the cause of the motorcade, it is possible to acquire and use video information captured by a vehicle that can capture an image of the vehicle causing the motorcade, such as the aforementioned motorcade vehicle or an oncoming vehicle.

[0015] In addition, the vehicle queue cause estimation device 110 estimates the cause of the vehicle queue in the traveling direction of the target vehicle based on the position information and image information acquired from each vehicle, and transmits the estimation result to the in-vehicle system 120_n of the target vehicle.

[0016] The on-vehicle systems 120_1 to 120_n-1, 121_1, and 122_1 are systems mounted on a vehicle at the head of the convoy, a vehicle nearby the head of the convoy, a vehicle in the convoy, an oncoming vehicle, and an observation vehicle, respectively. The on-vehicle systems 120_1 to 120_n-1, 121_1, and 122_1 each include a position information acquisition device 130_1 to 130_n-1, 131_1, and 132_1, and a video information recording device 140_1 to 140_n-1, 141_1, and 142_1, respectively.

[0017] Regardless of the vehicle attributes (vehicle at the head of the convoy, vehicle at the head of the convoy nearby, vehicle in the convoy, oncoming vehicle, observed vehicle), all in-vehicle systems have a position information acquisition device and a video information recording device because the vehicle attributes change over time. For example, a vehicle in a convoy changes over time to a vehicle at the head of the convoy nearby or to a vehicle at the head of the convoy, and a target vehicle changes to an observed vehicle.

[0018] The position information acquisition devices 130_1 to 130_n-1, 131_1, and 132_1 acquire current position information of each vehicle by, for example, a Global Positioning System (GPS). In addition, the position information acquisition devices 130_1 to 130_n-1, 131_1, and 132_1 transmit the acquired position information to the vehicle queue cause estimating device 110.

[0019] The video information recording devices 140_1 to 140_n-1, 141_1, and 142_1 are examples of sensor information recording devices, and are, for example, vehicle-mounted video recording devices attached to the windshield, dashboard, etc. of a vehicle. The video information recording devices 140_1 to 140_n-1, 141_1, and 142_1 record the current outside conditions of each vehicle as video, and transmit the recorded video information to the vehicle queue cause estimating device 110.

[0020] In this embodiment, a case where a video information recording device is used as a device for recording the state outside the vehicle will be described, but a sensor information recording device other than the video information recording device may be used instead of or in addition to the video information recording device. Examples of sensor information recording devices other than the video information recording device include a LiDAR (Laser Imaging Detection and Ranging) information recording device.

[0021] The in-vehicle system 120_n is a system installed in a target vehicle. The in-vehicle system 120_n includes an information providing device 150 in addition to a position information acquiring device 130_n and a video information recording device 140_n.

[0022] When a motorcade occurs, the information providing device 150 obtains the estimation result of the cause of the motorcade from the motorcade cause estimation device 110 and provides the estimation result (or instructions according to the estimation result) to the passengers of the target vehicle, etc. This enables the driver of the target vehicle to perform appropriate driving operations according to the estimation result of the cause of the motorcade.

[0023] An appropriate driving operation according to the estimation result of the cause of the traffic queue refers to, for example, performing a driving operation to travel on a detour route when it is determined from the estimation result of the cause of the traffic queue that the traffic queue will continue for a certain period of time or more, or performing a driving operation to continue following the traffic queue when it is determined from the estimation result of the cause of the traffic queue that the traffic queue will end within the certain period of time.

[0024] Alternatively, when it is determined from the estimation result of the cause of the procession that no procession has occurred in the adjacent lane ahead, the driving operation is performed to change lanes to the adjacent lane and continue driving. Also, when it is determined from the estimation result of the cause of the procession that a procession has occurred in the adjacent lane ahead, the driving operation is performed to continue driving following the procession.

[0025] For example, when the target vehicle is receiving route guidance from a navigation device, the information providing device 150 may provide the navigation device with the estimation result (or instructions according to the estimation result). This enables the navigation device to provide route guidance based on the estimation result (or instructions according to the estimation result), and the driver of the target vehicle can perform appropriate driving operations according to the estimation result of the cause of the vehicle queue.

[0026] Furthermore, for example, when the target vehicle has an automatic driving function and is in an automatic driving mode, the information providing device 150 may provide the estimation result (or an instruction according to the estimation result) to the automatic driving function. This allows the automatic driving function to perform an appropriate driving operation (automatic driving) according to the estimation result of the cause of the vehicle queue.

[0027] <Examples of information provision system applications> Next, an application example of the information providing system 100 will be described. FIG. 2 is a diagram showing an application example of the information providing system. The example of FIG. 2 is as follows: - Along a two-lane road, there is facility 210 ("Commercial Facility A"); The entrance to the parking lot of facility 210 faces (is adjacent to) a two-lane road on one side, There is a traffic light just before the entrance to the parking lot of facility 210. -Of the two-lane roads, the left lane is designated as a left-turn lane just before the traffic light. -Of the two-lane road, the left lane has a line of cars waiting to enter the parking lot of facility 210. It shows the situation.

[0028] In such a road condition, it is assumed that a target vehicle equipped with the in-vehicle system 120_n is at the end of a line of vehicles in order to turn left at a traffic light and head to a destination. In such a case, the vehicle line cause estimation device 110 in the information provision system 100 performs the following: - On-board system 120_1 in the leading vehicle of the train; - an on-board system 120_2 in a vehicle adjacent to the front of the train; - on-coming vehicle on-board system 121_1, - On-board system 122_1 of the observation vehicle, Based on the position information and image information acquired from the, the system infers that the cause of the queue of vehicles in the direction of travel of the target vehicle is waiting to enter the facility 210, and transmits the inference result to the in-vehicle system 120_n of the target vehicle.

[0029] As a result, for example, the driver of the target vehicle determines that there is no queue ahead in the adjacent lane, and changes lanes to the adjacent right lane. Also, after passing near the entrance to the parking lot of facility 210, the driver of the target vehicle changes lanes to the left lane and makes a left turn at an intersection with a traffic light.

[0030] In this way, the information provision system 100 can obtain a wider range of information by using the information (location information, video information) obtained by the in-vehicle system. Therefore, the information provision system 100 can estimate the cause of a motorcade, which cannot be estimated by a fixed surveillance camera, and provide the estimated result. As a result, when a motorcade occurs, it can be determined whether or not the motorcade will continue for a certain period of time or more, and whether or not a motorcade is occurring in an adjacent lane ahead, allowing appropriate driving operations to be performed.

[0031] <Hardware configuration of the vehicle queue cause estimation device> Next, a hardware configuration of the vehicle traffic cause estimation device 110 will be described. Fig. 3 is a diagram showing an example of the hardware configuration of the vehicle traffic cause estimation device. As shown in Fig. 3, the vehicle traffic cause estimation device 110 has a processor 301, a memory 302, an auxiliary storage device 303, an I / F (Interface) device 304, a communication device 305, and a drive device 306. The hardware components of the vehicle traffic cause estimation device 110 are connected to each other via a bus 307.

[0032] The processor 301 has various arithmetic devices such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), etc. The processor 301 reads various programs (for example, a vehicle queue cause estimation program described later) onto the memory 302 and executes them.

[0033] The memory 302 has a main storage device such as a read only memory (ROM) and a random access memory (RAM). The processor 301 and the memory 302 form a so-called computer, and the processor 301 executes various programs read onto the memory 302, causing the computer to realize various functions.

[0034] The auxiliary storage device 303 stores various programs and various data used when the various programs are executed by the processor 301. For example, a feature data storage unit 421 and a structure data storage unit 422, which will be described later, are realized in the auxiliary storage device 303.

[0035] The I / F device 304 is a connection device that connects an operation device 310, which is an example of an external device, a display device 311, and the vehicle traffic cause estimation device 110. The I / F device 304 accepts operations for the vehicle traffic cause estimation device 110 via the operation device 310. In addition, the I / F device 304 outputs results of processing by the vehicle traffic cause estimation device 110 and displays them on the display device 311.

[0036] The communication unit 305 is a communication device for communicating with the in-vehicle system via the network 160 .

[0037] The drive device 306 is a device for setting the recording medium 312. The recording medium 312 here includes media that record information optically, electrically, or magnetically, such as a CD-ROM, a flexible disk, a magneto-optical disk, etc. The recording medium 312 may also include semiconductor memories that record information electrically, such as ROM, flash memory, etc.

[0038] The various programs to be installed in the auxiliary storage device 303 are installed, for example, by setting the distributed recording medium 312 in the drive device 306 and reading out the various programs recorded in the recording medium 312 by the drive device 306. Alternatively, the various programs to be installed in the auxiliary storage device 303 may be installed by being downloaded from a network via the communication device 305.

[0039] In addition, while the hardware configuration of the vehicle queue cause estimation device 110 has been described in FIG. 3, each device of the in-vehicle system mounted on each vehicle (for example, the information providing device 150 of the in-vehicle system 120_n mounted on the target vehicle) is also assumed to have a similar hardware configuration.

[0040] <Functional configuration of the vehicle queue cause estimation device> Next, the functional configuration of the vehicle traffic cause estimation device 110 will be described. FIG. 4 is a diagram showing an example of the functional configuration of the vehicle traffic cause estimation device. As described above, a vehicle traffic cause estimation program is installed in the vehicle traffic cause estimation device 110, and by executing this program, the vehicle traffic cause estimation device 110: A vehicle train detection unit 410; ·Location information acquisition unit 411, A video information acquisition unit 412 (an example of a sensor information acquisition unit), · Vehicle Identification Unit 413, ·Feature search department 414, ·Structure search section 415, A vehicle queue cause estimation unit 416 (an example of an estimation unit), It functions as:

[0041] The vehicle train detection unit 410 detects the occurrence of a vehicle train near the target vehicle using a well-known method. When the vehicle train detection unit 410 detects the occurrence of a vehicle train, it determines the occurrence position of the vehicle train and notifies the position information acquisition unit 411 and the video information acquisition unit 412 of the occurrence position.

[0042] The location information acquisition unit 411 communicates with the in-vehicle systems installed in each vehicle at the occurrence location (and its surroundings) notified by the vehicle line detection unit 410, thereby acquiring location information from each vehicle and notifying the vehicle identification unit 413.

[0043] The video information acquisition unit 412 communicates with the in-vehicle systems installed in each vehicle at the occurrence location (and its surroundings) notified by the vehicle convoy detection unit 410, acquires video information from each vehicle, and notifies the feature search unit 414 and structure search unit 415.

[0044] In the above description, the vehicle that detects the occurrence of a motorcade and the vehicle that acquires position information and video information for estimating the cause of the motorcade are different vehicles, but they may be the same vehicle. In other words, the motorcade detection unit 410 may be configured to detect the occurrence of a motorcade from the position information and video information acquired from each vehicle.

[0045] When the vehicle identification unit 413 is notified of the location information of each vehicle by the location information acquisition unit 411, it determines the attributes of each vehicle (leading vehicle in the convoy, nearby vehicle at the front of the convoy, oncoming vehicle, observed vehicle) and notifies the feature search unit 414 and structure search unit 415 of this together with the location information.

[0046] The feature search unit 414 searches for corresponding feature data (feature data within a predetermined distance) in the feature data storage unit 421 based on the attributes and position information of each vehicle notified by the vehicle identification unit 413 and the image information notified by the image information acquisition unit 412. In addition, the feature search unit 414 notifies the vehicle train cause estimation unit 416 of the result of the search for feature data.

[0047] The feature data stored in the feature data storage unit 421 includes the following: (a) Data relating to the rules of travel on roads, such as intersections, traffic lights, road signs, etc.; or (b) Facility information, e.g. Data on the entrances (street entrances) of car parks at tourist sites or commercial establishments; Data on toll booths, Data about public transport stops such as bus stops, taxi stands or train stations, or (c) Information on features (information on features existing on the road), e.g. - Data on disasters (landslides), Data on temporary lane closures (construction, slow-moving vehicles (mobile sales vehicles, advertising vehicles, election vehicles, etc.)), The data on the driving rules may include rules defined by law and de facto rules that are common among users.

[0048] The structure searching unit 415 searches for corresponding structure data in the structure data storage unit 422 based on the attributes and position information of each vehicle notified by the vehicle identification unit 413 and the image information notified by the image information acquisition unit 412. In addition, the structure searching unit 415 notifies the vehicle train cause estimation unit 416 of the search result of the structure data.

[0049] The structure data stored in the structure data storage unit 422 includes the following: (d) Information about roads that affect travel, e.g. Data on changes in elevation and number of lanes on surrounding roads; Data on the connections between road links; - Data on sags and junctions, etc. are included.

[0050] The vehicle queue cause estimation unit 416 estimates the cause of the vehicle queue based on the search results of the feature data notified by the feature search unit 414 and the search results of the structure data notified by the structure search unit 415.

[0051] In addition, the vehicle queue cause estimation unit 416 directly estimates the cause of the vehicle queue based on the video information acquired by the video information acquisition unit 412.

[0052] For example, the motorcade cause estimation unit 416 calculates the speed of the leading vehicle in the motorcade based on video information acquired from the leading vehicle in the motorcade, and if the leading vehicle in the motorcade is traveling at a speed slower than a predetermined value compared to the target vehicle, it estimates that the leading vehicle in the motorcade is the cause of the motorcade.

[0053] In addition, the motorcade cause estimation unit 416 estimates that an object (an accident vehicle, a broken-down vehicle, a fallen object, or other obstacle) that is temporarily present (i.e., not present under normal circumstances) ahead on the road on which the leading vehicle of the motorcade is traveling, based on the video information acquired from the leading vehicle of the motorcade, is the cause of the motorcade.

[0054] The vehicle queue cause estimation unit 416 transmits the estimation result of the cause of the vehicle queue to the in-vehicle system 120_n of the target vehicle.

[0055] When multiple feature data search results and multiple structure data search results are notified, the vehicle traffic cause estimation unit 416 estimates the cause of the vehicle traffic by prioritizing the feature data, the structure data, or the feature data and the structure data.

[0056] Furthermore, if there are no search results for feature data or structure data, the vehicle convoy cause estimation unit 416 transmits an estimation result that the vehicle convoy has an unknown cause or has no particular cause to the in-vehicle system 120_n of the target vehicle.

[0057] A convoy without a particular cause refers to a convoy in which there is no feature or structure that may be the cause in the vicinity of the convoy, such as a convoy of vehicles (e.g., commercial vehicles such as transport vehicles and taxis) that have stopped for the driver to take a break, or a convoy of vehicles that have stopped to wait for entry into a facility in a distant location. Convoys without a particular cause may be estimated as "parked on the street" and transmitted to the in-vehicle system 120_n of the target vehicle. When estimating the cause of a convoy based on vehicles that have stopped for a break, time may also be taken into consideration. For example, during lunch time, a flag may be configured to be turned on to estimate that a vehicle that has stopped for a break is the cause of the convoy.

[0058] <Examples of location information and video information> Next, specific examples of the position information and the image information will be described. Figures 5 and 6 are first and second diagrams showing examples of the position information and the image information.

[0059] FIG. 5(a) shows image information 510 of a vehicle whose vehicle attributes have been determined to be the leading vehicle in a train based on location information (latitude=X1 degree, longitude=Y1 degree, altitude=Z1 degree). According to the image information 510, -There is a traffic light 511 ahead, There are no vehicles between the front vehicle of the train and signal 511. The first vehicle in the train is parked in front of the parking lot entrance 512. - An oncoming vehicle 513 is traveling. It is possible to grasp the following:

[0060] FIG. 5B shows image information 520 of a vehicle whose vehicle attributes have been determined to be a surrounding vehicle at the front of a train based on location information (latitude=X2 degrees, longitude=Y2 degrees, altitude=Z2 degrees). In addition to the information that can be ascertained from the image information 510, the image information 520 further includes: The head vehicle 522 of the train is stopped in front of the entrance 512 of the parking lot of "Commercial Facility A"; It is possible to grasp the following:

[0061] FIG. 6(a) shows image information 610 of a vehicle whose vehicle attributes have been determined to be an oncoming vehicle based on location information (latitude=X3 degrees, longitude=Y3 degrees, altitude=Z3 degrees). According to the image information 610, The vehicle 522 at the head of the train is parked at the front of the train just before the entrance 512 of the parking lot. - The front vehicle of the line, vehicle 611, is parked second in the line just before the entrance to the parking lot, vehicle 512. It is possible to grasp the following:

[0062] 6B shows image information 620 of a vehicle whose vehicle attributes have been determined to be an observed vehicle based on location information (latitude=X4 degrees, longitude=Y4 degrees, altitude=Z4 degrees). In addition to the information that can be understood from the image information 610, the image information 620 further includes: There is no traffic convoy ahead in the right lane adjacent to the left lane where the traffic convoy is occurring. It is possible to grasp the following:

[0063] <Flow of process to estimate cause of convoy> Next, there will be described the flow of the process of estimating the cause of a traffic jam by the vehicle traffic cause estimating device 110. Fig. 7 is a flowchart showing the flow of the process of estimating the cause of a traffic jam.

[0064] In step S701, the vehicle queue detection unit 410 of the vehicle queue cause estimation device 110 determines whether or not a vehicle queue has occurred near the target vehicle. If it is determined in step S701 that a vehicle queue has not occurred (NO in step S701), the process waits until it is determined that a vehicle queue has occurred.

[0065] On the other hand, if it is determined in step S701 that a motorcade has occurred (YES in step S701), the process proceeds to step S702. In step S702, the position information acquisition unit 411 and the video information acquisition unit 412 of the motorcade cause estimation device 110 acquire position information and video information from each vehicle at the position where the motorcade has occurred (and its surroundings).

[0066] In step S703, the vehicle identification unit 413 of the vehicle procession cause estimation device 110 identifies the position of each vehicle relative to the vehicle procession based on the position information of each vehicle, and determines the attributes of each vehicle.

[0067] In step S704, the feature search unit 414 and structure search unit 415 of the vehicle procession cause estimation device 110 search for feature data and structure data related to the vehicle procession based on the attributes and position information of each vehicle and the image information of each vehicle.

[0068] In step S705, the vehicle traffic cause estimation unit 416 of the vehicle traffic cause estimation device 110 estimates the cause of the vehicle traffic in the traveling direction of the target vehicle based on the search results of the feature data and structure data. Note that if the vehicle that detects the occurrence of the vehicle traffic and the vehicle that acquires the position information and image information for estimating the cause of the vehicle traffic are the same vehicle, the method of estimating the cause of the vehicle traffic is not limited to this. For example, the estimation may be performed by referring to information on the causes of vehicle traffic that have occurred in the past all over the country that is stored in advance, based on the position information and image information from the vehicle that detects the occurrence of the vehicle traffic (i.e., without searching for feature data and structure data).

[0069] In step S706, the vehicle queue cause estimation unit 416 of the vehicle queue cause estimation device 110 transmits the estimation result to the in-vehicle system of the target vehicle.

[0070] The vehicle queue cause estimation unit 416 of the vehicle queue cause estimation device 110 may transmit information grasped from the video information 510, 520, 610, 620 in addition to the estimation result to the in-vehicle system of the target vehicle.

[0071] <Functional configuration of the in-vehicle system of the target vehicle> Next, the functional configuration of the in-vehicle system 120_n of the target vehicle will be described. Fig. 8 is a diagram showing an example of the functional configuration of the in-vehicle system of the target vehicle. As described above, the in-vehicle system 120_n has a position information acquisition device 130_n, a video information recording device 140_n, and an information providing device 150. Of these, the information providing device 150 will be described in detail below.

[0072] An information provision program is installed in the information providing device 150, and by executing the program, the information providing device 150 functions as a vehicle queue cause acquisition unit 801, a judgment unit 802, a vehicle queue cause notification unit 803, a guidance unit 804, and a driving control unit 805.

[0073] The vehicle queue cause acquisition unit 801 acquires the result of estimation of the cause of the vehicle queue from the vehicle queue cause estimation device 110 when a vehicle queue occurs.

[0074] The determination unit 802 performs various determinations based on the acquired estimation result of the cause of the motorway, and notifies the determination result to the motorway cause notification unit 803. The various determination results here include, for example, a determination result of whether or not the motorway will continue for a certain period of time or more (whether or not it will end within a certain period of time) based on the estimation result of the cause of the motorway. Alternatively, the determination result of whether or not a motorway has occurred ahead of an adjacent lane may be included based on the estimation result of the cause of the motorway.

[0075] When making various determinations, the determination unit 802 may obtain information that can be understood from the video information 510, 520, 610, and 620 in addition to the estimated result of the cause of the procession.

[0076] The vehicle traffic cause notification unit 803 is an example of an instruction unit. When an estimation result of the cause of the vehicle traffic is acquired by the vehicle traffic cause acquisition unit 801, the vehicle traffic cause notification unit 803 provides the acquired estimation result of the cause of the vehicle traffic to the passengers of the target vehicle. In addition, when various determinations are made by the determination unit 802, the vehicle traffic cause notification unit 803 provides instructions according to the estimation result (for example, instructions on which lane to travel in). This allows the driver of the target vehicle to perform appropriate driving operations according to the estimation result of the vehicle traffic.

[0077] When the target vehicle is receiving route guidance from a navigation device, the guiding unit 804 provides the acquired estimation result of the cause of the motorcade (or instructions according to the estimation result) to the navigation device.

[0078] If the target vehicle has an autonomous driving function and is in autonomous driving mode, the driving control unit 805 provides the acquired inference result of the cause of the queue (or instructions according to the inference result) to the autonomous driving function.

[0079] <Information provision process flow> Next, a flow of the information provision process by the information provision device 150 of the in-vehicle system 120_n of the target vehicle will be described. Fig. 9 is a flowchart showing the flow of the information provision process.

[0080] In step S901, the vehicle queue cause acquisition unit 801 of the information providing device 150 determines whether or not an estimation result of the cause of the vehicle queue has been acquired from the vehicle queue cause estimation device 110. If it is determined in step S801 that an estimation result of the cause of the vehicle queue has not been acquired (NO in step S901), the process proceeds to step S907.

[0081] On the other hand, if it is determined in step S901 that an estimation result of the cause of the motorcade has been acquired (YES in step S901), the process proceeds to step S902.

[0082] In step S902, the driving control unit 805 of the information providing device 150 determines whether or not the vehicle is in the automatic driving mode, and if it is determined that the vehicle is in the automatic driving mode (YES in step S902), the process proceeds to step S903.

[0083] In step S903, the driving control unit 805 of the information providing device 150 provides the estimation result of the cause of the vehicle queue (or an instruction according to the estimation result) to the automatic driving function. This enables the automatic driving function to perform an appropriate driving operation (automatic driving) according to the estimation result of the cause of the vehicle queue.

[0084] On the other hand, if it is determined in step S902 that the vehicle is not in the automatic driving mode (if NO in step S902), the process proceeds to step S904.

[0085] In step S904, the guiding unit 804 of the information providing device 150 determines whether or not route guidance is being performed by the navigation device. If it is determined in step S904 that route guidance is being performed by the navigation device (YES in step S904), the process proceeds to step S905.

[0086] In step S905, the guiding unit 804 of the information providing device 150 provides the estimation result of the cause of the vehicle queue (or instructions according to the estimation result) to the navigation device. This enables the navigation device to provide route guidance based on the estimation result of the cause of the vehicle queue (or instructions according to the estimation result), and the driver of the target vehicle can perform appropriate driving operations according to the cause of the vehicle queue.

[0087] On the other hand, if it is determined in step S904 that the navigation device is not currently providing route guidance (NO in step S904), the process proceeds to step S906.

[0088] In step S906, the vehicle queue cause notification unit 803 of the information providing device 150 provides the passenger with the estimated result of the vehicle queue cause (or an instruction according to the estimated result). This allows the driver of the target vehicle to perform an appropriate driving operation according to the estimated result of the vehicle queue cause.

[0089] In step S907, the vehicle queue cause acquisition unit 801 of the information provision device 150 determines whether or not to end the information provision process. If it is determined in step S907 that the information provision process is to be continued (NO in step S907), the process returns to step S901.

[0090] On the other hand, if it is determined in step S907 that the information provision process is to be ended, the information provision process is ended.

[0091] <Summary> As is clear from the above description, the vehicle queue cause estimation device 110: When a convoy is detected near the target vehicle, the system communicates with the location of the convoy and each vehicle in the vicinity, and obtains location and video information from each vehicle. Based on the position information of each vehicle, the attributes of each vehicle determined based on the position information, and the image information of each vehicle, feature data and structure data related to the vehicle train are searched for. Based on the searched feature data and structure data, the cause of the traffic jam in the direction of travel of the target vehicle is estimated, and the estimation result is transmitted to the target vehicle.

[0092] This makes it possible to infer the cause of the queue.

[0093] In addition, the information providing device 150 of the target vehicle Obtain an estimate of the cause of the traffic jam in the direction of travel of the target vehicle, based on the position information and video information obtained from each vehicle other than the target vehicle. Depending on the inference of the cause of the traffic jam, the system instructs the target vehicle which lane to drive in.

[0094] This allows the target vehicle to perform appropriate driving operations when a convoy occurs.

[0095] [Second embodiment] In the above-described first embodiment, the case shown in Fig. 2 is exemplified as an application example of the information providing system 100. However, the application example of the information providing system 100 is not limited to this, and the information providing system 100 may be applied to other cases. Hereinafter, in the second embodiment, other cases to which the information providing system 100 can be applied will be exemplified.

[0096] <Other application example 1 of the information provision system> First, another application example 1 to which the information providing system 100 can be applied will be described. FIG. 10 is a first diagram showing another application example to which the information providing system can be applied. The example in FIG. 10 is as follows: - Along a two-lane road, there is facility 1010 ("Commercial Facility B"). The entrance to the parking lot of Facility 1010 faces the opposite side of a two-lane road. -There is a traffic light ahead of facility 1010. -Of the two-lane roads, the left lane is a continuation of the line of vehicles on the road after turning left. After the left turn, the road continues with the line of vehicles on the road after the left turn. After turning left again, you will come to the entrance of the parking lot of Facility 1010. - There is a line of cars waiting to enter the parking lot at the entrance of Facility 1010. It shows the situation.

[0097] In such a road condition, it is assumed that a target vehicle equipped with the in-vehicle system 120_n is at the end of a line of vehicles in order to turn left at a traffic light and head to a destination. In such a case, the vehicle line cause estimation device 110 in the information provision system 100 performs the following: - On-board system 120_1 in the leading vehicle of the train; - an on-board system 120_2 in a vehicle adjacent to the front of the train; - On-coming vehicle on-board systems 121_1, 121_2, - On-board system 122_1 of the observation vehicle, Based on the position information and image information acquired from the target vehicle, the system infers that the cause of the queue of vehicles in the direction of travel of the target vehicle is waiting to enter the facility 1010, and transmits the inference result to the in-vehicle system 120_n of the target vehicle.

[0098] As a result, for example, the driver of the target vehicle may determine that there is no traffic queue ahead in the adjacent lane and change lanes to the adjacent right lane, or may turn left at an intersection with traffic lights and then continue straight.

[0099] In this way, the information providing system 100 can obtain a wider range of information and estimate the cause of the motorcade, so that appropriate driving operations can be performed when a motorcade occurs.

[0100] <Other application examples of information provision systems 2> Next, another application example 2 to which the information providing system 100 can be applied will be described. FIG. 11 is a second diagram showing another application example to which the information providing system can be applied. The example in FIG. 11 is as follows: - Along a two-lane road, there is facility 210 ("Commercial Facility A"); The entrance to the parking lot of Facility 210 faces a two-lane road on one side, A first traffic light is installed ahead of the entrance to the parking lot of facility 210, -Of the two-lane roads, the left lane is designated as a left-turn lane just before the first traffic light. -Of the two-lane road, a line of cars waiting to enter the parking lot of Facility 210 was formed in the left lane. - In the middle of the queue of cars waiting to enter the parking lot, there is a T-junction, and there is another queue of cars on the side of the road that merges into a two-lane road, and there is also another queue of cars on the side of the two-lane road, On a two-lane road, there is a second traffic light just before the T-junction where the two lanes join. It shows the situation.

[0101] In such a road condition, it is assumed that a target vehicle equipped with the in-vehicle system 120_n is at the end of a line of vehicles in order to turn left at a first traffic light and head to a destination. In such a case, in the information provision system 100, the vehicle line cause estimation device 110 performs the following: In-vehicle systems 120_1, 120n-1, 120_4 in the leading vehicles of the train, In-vehicle systems 120_2, 120n, 120_5 in the leading vehicles of the train, - On-coming vehicle on-board systems 121_1, 121_2, - On-board systems for observation vehicles 122_1, 122_2 Based on the position information and image information acquired from the, it is estimated that the cause of the queue of vehicles in the direction of travel of the target vehicle is not the second traffic light, but waiting to enter the facility 210, and the estimation result is transmitted to the in-vehicle system 120_n of the target vehicle.

[0102] As a result, for example, the driver of the target vehicle determines that there is no queue ahead in the adjacent lane, and changes lanes to the adjacent right lane. Also, after passing the second traffic light and the entrance to the parking lot of facility 210, the driver of the target vehicle changes lanes to the left lane and makes a left turn at the intersection with the traffic light.

[0103] In this way, the information providing system 100 can obtain a wider range of information and estimate the cause of the motorcade, so that appropriate driving operations can be performed when a motorcade occurs.

[0104] <Other application examples of information provision systems 3> Next, another application example 3 to which the information providing system 100 can be applied will be described. FIG. 12 is a third diagram showing another application example to which the information providing system can be applied. The example in FIG. 12 is as follows: - On a two-lane road, the accident vehicle 1210 was stopped. There is a traffic light ahead of the accident vehicle 1210. -Of the two-lane roads, the left lane is designated as a left-turn lane just before the traffic light. A vehicle traveling in the left lane of a two-lane road and a vehicle traveling in the right lane of the two-lane road alternately pass the accident vehicle 1210 from the right lane. It shows the situation.

[0105] In such a road condition, it is assumed that a target vehicle equipped with the in-vehicle system 120_n is at the end of a line of vehicles in order to turn left at a traffic light and head to a destination. In such a case, the vehicle line cause estimation device 110 in the information provision system 100 performs the following: In-vehicle systems 120_1 and 120_1' in the front vehicles of the train In-vehicle systems 120_2, 120_2' in the leading vehicles of the train - on-coming vehicle on-board system 121_1, Based on the position information and image information acquired from the vehicle accident detection system 120, the vehicle accident detection system 120 estimates that the cause of the train of vehicles in the traveling direction of the target vehicle is the accident vehicle, and transmits the estimation result to the in-vehicle system 120_n of the target vehicle.

[0106] In this case, for example, the driver of the target vehicle determines that a queue is occurring ahead in the adjacent lane, and drives at the end of the queue without changing lanes. Also, the driver of the target vehicle changes lanes to the right lane just before the accident vehicle 1210 to avoid the accident vehicle 1210, then changes lanes again to the left lane and turns left at the intersection with a traffic light.

[0107] In this way, the information providing system 100 can obtain a wider range of information and estimate the cause of the motorcade, so that appropriate driving operations can be performed when a motorcade occurs.

[0108] <Summary> As is clear from the above description, the information providing device 150 of the target vehicle provides the estimation result of the cause of the vehicle convoy in various scenes where the vehicle convoy occurs. This allows the driver of the target vehicle to perform an appropriate driving operation according to the estimation result of the cause of the vehicle convoy.

[0109] In each of the above application examples, the case where the estimation result is provided has been described, but an instruction according to the estimation result may be provided as in the first embodiment. In addition, in each of the above application examples, the case where the estimation result is provided to a passenger of the target vehicle has been described, but the estimation result may be provided to a navigation device or an automatic driving function as in the first embodiment.

[0110] [Other embodiments] In the above first and second embodiments, the vehicle traffic cause estimation device 110 has been described as transmitting the estimation result of the vehicle traffic cause to the in-vehicle system 120_n of the target vehicle. However, the transmission destination of the estimation result of the vehicle traffic cause is not limited to the in-vehicle system 120_n of the target vehicle, and may be transmitted to, for example, a server device or server system of a service that provides vehicle traffic information or a service that provides map information. Alternatively, the vehicle traffic cause estimation device 110 may transmit position information and image information used in estimating the vehicle traffic cause to these server devices or server systems, instead of the estimation result of the vehicle traffic cause.

[0111] In the above first and second embodiments, the vehicle traffic cause estimation device 110 has been described as acquiring position information and image information of vehicles other than the target vehicle and estimating the cause of the vehicle traffic. However, the target vehicle may acquire position information and image information of vehicles other than the target vehicle and estimate the cause of the vehicle traffic. Alternatively, some of the functions realized by the vehicle traffic cause estimation device 110 (vehicle traffic detection unit 410, position information acquisition unit 411, image information acquisition unit 412, vehicle identification unit 413, feature search unit 414, structure search unit 415, and vehicle traffic cause estimation unit 416) may be realized by the target vehicle.

[0112] Furthermore, in the above first and second embodiments, a vehicle procession occurring near the target vehicle is detected. However, a vehicle procession occurring at a position away from the target vehicle may be detected.

[0113] In the above first and second embodiments, the cause of the vehicle procession is estimated using directly sensed sensor information such as a video information recording device, a sensor information recording device, etc. However, the method of estimating the cause of the vehicle procession is not limited to this, and the cause of the vehicle procession may be estimated using non-sensor information different from directly sensed sensor information.

[0114] As an example, a case will be described in which a chronic convoy of vehicles occurs due to a nearby facility (particularly a facility that is not captured by a vehicle-mounted video information recording device). In such a case, the cause of the convoy of vehicles cannot be inferred based on the video information.

[0115] In response to this, for example, in meshes obtained by dividing real space into predetermined ranges, information on the number of cars calculated in a predetermined time unit may be used to estimate that congestion is chronic. Alternatively, facilities that are the cause of a traffic jam may be registered in advance, and when a traffic jam occurs whose cause cannot be estimated, the registered facility that exists in the same mesh or in a nearby mesh may be estimated as the cause of the traffic jam.

[0116] In this way, by using non-sensor information, it is possible to estimate the cause of a motorcade when the cause is unknown.

[0117] The present invention is not limited to the configurations shown in the above embodiments, combinations with other elements, etc. These points can be changed without departing from the spirit of the present invention, and can be appropriately determined according to the application form. [Explanation of symbols]

[0118] 100: Information provision system 110: Vehicle convoy cause estimation device 120_1~120_n: In-vehicle systems 121_1, 122_1: In-vehicle systems 130_1~130_n: Location information acquisition device 131_1, 132_1: Location information acquisition device 140_1~140_n: Video information acquisition device 141_1, 142_1: Image information acquisition device 150: Information provision device 410: Vehicle line detection unit 411: Location information acquisition unit 412: Video information acquisition unit 413: Vehicle Identification Division 414: Feature Search Department 415:Structure Search Department 416: Traffic Accident Cause Estimation Department 801: Traffic Cause Acquisition Department 802: Judgment section 803: Traffic Cause Notification Department 804:Induction part 805: Operation control unit

Claims

1. An estimation method for estimating a cause of a traffic jam using a sensor mounted on a vehicle, comprising: a step of identifying, when the generation position of the motorcade is determined, a vehicle located at the front of the motorcade, vehicles belonging to the motorcade, vehicles traveling in a lane opposite to the lane in which the motorcade has occurred, and vehicles traveling in a lane adjacent to the lane in which the motorcade has occurred; acquiring sensor information acquired by a sensor mounted on the identified vehicle; acquiring location information of the identified vehicle that has acquired the sensor information; and estimating a cause of the convoy using the sensor information and the position information; The estimating step includes: An estimation method that uses any of data regarding driving rules present in the vicinity of the identified vehicle searched for using the location information and the sensor information, information regarding facilities, information regarding features, or information regarding roads that affect driving searched for using the location information and the sensor information.

2. The estimating step includes:

2. The estimation method according to claim 1, further comprising estimating a state of a vehicle at the front of the motorcade from the sensor information, and, if the state of the vehicle at the front of the motorcade is such that the vehicle is traveling at a speed slower than a predetermined value compared to a target vehicle that transmits an estimation result of the cause of the motorcade, estimating that the vehicle at the front of the motorcade is the cause of the motorcade.

3. The estimating step includes:

2. The estimation method according to claim 1, wherein, of the facilities located near the identified vehicle searched for using the position information and the sensor information, a facility within a predetermined distance from the identified vehicle and adjacent to a road on which the identified vehicle is traveling is estimated to be the cause of the motorcade.

4. The estimating step includes:

2. The method according to claim 1, wherein, of the features located near the identified vehicle searched for using the position information and the sensor information, a feature within a predetermined distance of the identified vehicle and a feature located on a road on which the identified vehicle is traveling are estimated to be the cause of the motorcade.

5. The estimating step includes:

2. The method according to claim 1, further comprising estimating, from among objects present in front of the vehicle at the front of the motorcade included in the sensor information, an object that is not normally present on a road on which the vehicle at the front of the motorcade is traveling, as the cause of the motorcade.

6. Further, the method includes a step of acquiring non-sensor information that is not directly sensed sensor information, The estimating step includes: The estimation method according to claim 2 , wherein, when a convoy of vehicles occurs, including on-street parking of a transport vehicle, the cause of the convoy cannot be estimated using the sensor information, the non-sensor information is used to estimate the cause of the convoy.

7. An estimation device that estimates a cause of a vehicle train using a sensor mounted on a vehicle, an identification unit that, when the occurrence position of the procession is determined, identifies a vehicle located at the front of the procession, vehicles belonging to the procession, vehicles traveling in a lane opposite to the lane in which the procession has occurred, and vehicles traveling in a lane adjacent to the lane in which the procession has occurred; a sensor information acquisition unit that acquires sensor information acquired by a sensor mounted on the specified vehicle; a location information acquisition unit that acquires location information of the identified vehicle that has acquired the sensor information; an estimation unit that estimates a cause of the vehicle train using the sensor information and the position information, The estimation unit is An estimation device that performs estimation using any of data regarding driving rules present in the vicinity of the identified vehicle searched for using the location information and the sensor information, information regarding facilities, information regarding features, or information regarding roads that affect driving searched for using the location information and the sensor information.

8. An estimation method for estimating a cause of a traffic jam using a sensor mounted on a vehicle, comprising: a step of identifying, when the generation position of the motorcade is determined, a vehicle located at the front of the motorcade, vehicles belonging to the motorcade, vehicles traveling in a lane opposite to the lane in which the motorcade has occurred, and vehicles traveling in a lane adjacent to the lane in which the motorcade has occurred; acquiring sensor information acquired by a sensor mounted on the identified vehicle; acquiring location information of the identified vehicle that has acquired the sensor information; and a step of estimating a cause of the vehicle train using the sensor information and the position information, The estimating step includes: An estimation program that makes an estimation using any of data regarding driving rules present in the vicinity of the identified vehicle searched for using the location information and the sensor information, information regarding facilities, information regarding features, or information regarding roads that affect driving searched for using the location information and the sensor information.

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