JP2022072963A - Information processing method, program, and information processing device - Google Patents

Abstract

To easily manage road conditions using appropriate location information when a managed object on a road is detected.SOLUTION: An information processing method that is executed by an information processing device including a processor causes the processor to: acquire information on a managed object on a road, which is detected using sensor information acquired by an in-vehicle sensor; identify, using map data having a predetermined level of accuracy that can be managed on a lane-by-lane basis, a first location at which the managed object is detected; and manage a condition of the road at the first location based on the information on the managed object.SELECTED DRAWING: Figure 9

Description

The present invention relates to an information processing method, a program, and an information processing apparatus.

Conventionally, there is a technique for managing abnormal parts of a road. For example, when a general user's vehicle is traveling on the road, it is configured to automatically detect and identify an abnormal location on the road and notify the user, and further, the notified user is specified. There is known a technique of transmitting an image of an abnormal place on a road taken by a camera to a management center together with the position information of the specified abnormal place on the road (see, for example, Patent Document 1).

Japanese Unexamined Patent Publication No. 2007-72667

However, in Patent Document 1, although the abnormal place of the road is detected and specified, the detailed abnormal place cannot be specified. Further, the user has to go to the vicinity of the abnormal place, identify the detailed abnormal place, and take a picture of the abnormal place with a digital camera or the like, which requires complicated processing.

On the other hand, in recent years, highly accurate map data has been generated, and the accuracy level of this map data enables accuracy at about 0.5 m, and it is possible to distinguish lanes.

Therefore, one of the objects of the present invention is to easily manage the road condition by using appropriate position information when the object to be managed on the road is detected.

The information processing method according to one aspect of the present invention is an information processing method executed by an information processing apparatus including a processor, and the processor is detected by using sensor information acquired by an in-vehicle sensor, and is managed on a road. To acquire information about the object, to identify the first position where the controlled object is detected by using map data having a predetermined accuracy level that can be managed for each lane, and to obtain information about the controlled object. Based on this, the state management of the road at the first position is performed.

According to the present invention, when a controlled object on a road is detected, it is possible to easily manage the road condition by using appropriate position information.

It is a figure which shows an example of the structure of the information processing system which concerns on one Embodiment of this invention. It is a figure which shows an example of the hierarchical structure of the map data which concerns on one Embodiment of this invention. It is a figure which shows an example of the structure of the vehicle which concerns on one Embodiment of this invention. It is a figure which shows an example of the structure of the CPU of the vehicle which concerns on one Embodiment of this invention. It is a figure which shows an example of the structure of the information processing apparatus which concerns on one Embodiment of this invention. It is a figure which shows an example of the database which concerns on one Embodiment of this invention. It is a figure which shows an example of the road management information which concerns on one Embodiment of this invention. It is a figure which shows the detection example of the controlled object which concerns on one Embodiment of this invention. It is a flowchart which shows an example of the processing on the vehicle side which concerns on one Embodiment of this invention. It is a flowchart which shows an example of the processing of the information processing apparatus which concerns on one Embodiment of this invention. It is a flowchart which shows an example of the state management process which concerns on one Embodiment of this invention.

[Embodiment]
Preferred embodiments of the present invention will be described with reference to the accompanying drawings. In each figure, those with the same reference numerals have the same or similar configurations.

<Overview of the system>
FIG. 1 is a diagram showing an example of a configuration of an information processing system 1 according to an embodiment of the present invention. The information processing system 1 shown in FIG. 1 includes a vehicle 10 equipped with a high-precision locator, an information processing device 20, and a positioning satellite 30 used in a GNSS (Global Navigation Satellite System), which are via network N. It is possible to send and receive data to and from each other. Further, the number of vehicles 10 and information processing devices 20 may be one or more.

The vehicle 10 is a vehicle equipped with a high-precision locator. Further, the vehicle 10 can receive a signal from the GNSS positioning satellite 30 and detect the position information of the own vehicle using a high-precision locator. Further, the vehicle 10 may be a vehicle equipped with an automatic driving system and capable of automatic driving (autonomous driving).

The high-precision locator is a locator capable of measuring the position in lane units based on a signal from the satellite positioning system, and a known locator may be used. The high-precision locator can acquire the position information of the vehicle 10 in lane units by receiving information from the quasi-zenith satellite and combining it with the high-precision three-dimensional map data described later. For example, by using a high-precision locator, the accuracy of the vehicle position can be improved to about 0.5 m or less. The position information includes, for example, three-dimensional position information of latitude, longitude and altitude, or two-dimensional position information of latitude and longitude.

The positioning satellite 30 is a satellite that transmits a signal necessary for measuring position information. For example, the positioning satellite 30 is a satellite used for GNSS, and may include a satellite capable of transmitting a signal related to highly accurate position information (for example, a quasi-zenith satellite).

The information processing device 20 is, for example, a server, and acquires the position information of the vehicle 10 acquired by the high-precision locator from the vehicle 10. Further, as will be described later, the information processing apparatus 20 acquires information on the managed object detected by the vehicle 10, and uses the managed object and the highly accurate position at the time of detection to determine the state of the road. to manage. The information processing device 20 may be composed of a plurality of information processing devices.

<Overview of map data>
Here, an outline of the map data used in the present embodiment will be described. The map data used in this embodiment is, for example, high-precision three-dimensional map data used for automatic driving and the like. As a specific example, this map data is map data called a dynamic map provided in real time to which more dynamic information such as information on surrounding vehicles and traffic information is added. The map data used in this embodiment is classified into, for example, four layers.

FIG. 2 is a diagram showing an example of a hierarchical structure of map data according to an embodiment of the present invention. In the example shown in FIG. 2, the map data is classified into static information SI1, quasi-static information SI2, quasi-dynamic information MI1, and dynamic information MI2.

The static information SI1 is three-dimensional high-precision basic map data (high-precision three-dimensional map data), and includes road surface information, lane information, three-dimensional structures, and three-dimensional position coordinates indicating a feature. And linear vector data. The quasi-static information SI2, the quasi-dynamic information MI1 and the dynamic information MI2 are dynamic data that change from moment to moment, and are data superimposed on static information based on position information.

The quasi-static information SI2 includes traffic regulation information, road construction information, wide area meteorological information, and the like. The quasi-dynamic information MI1 includes accident information, traffic jam information, narrow area weather information, and the like. The dynamic information MI2 includes ITS (Intelligent Transport System) information, and includes peripheral vehicles, pedestrians, signal information, and the like.

In order to realize a dynamic map, it is important to construct high-precision three-dimensional map data (hereinafter, also referred to as “HD (High Definition) map”) corresponding to static information SI1. The HD map has a predetermined accuracy level that can be managed in lane units (lane units). For example, if the map information level used to show the accuracy of the position and height in a digitized map is used as the accuracy level, the HD map has a map information level of about 500 (equivalent scale 1/500) and It is a map having a more precise level than the map information level 500.

Hereinafter, the vehicle 10 used for road management, the information processing device 20, and the like according to the present embodiment will be described.

<Vehicle configuration>
FIG. 3 is a diagram showing an example of the configuration of the vehicle 10 according to the embodiment of the present invention. In the example shown in FIG. 1, the vehicle 10 includes a high-precision locator 101, a processor 102, various sensors 103, and a communication device 104 as an on-board unit. Further, the vehicle 10 may be provided with an information processing device including an in-vehicle device.

The high-precision locator 101 is, for example, a locator that calculates the position of the own vehicle with high accuracy with an accuracy of 50 cm, and since the accuracy is about 50 cm or less, it is possible to measure the position in lane units as a result. Further, the high-precision locator 101 performs positioning using the positioning reinforcement signal from the positioning satellite 30 and the carrier phase, lane map matching using a camera, and accuracy evaluation using GNSS Raw data. You may.

The processor 102 is, for example, a CPU (Central Processing Unit), which controls the operation of the vehicle 10 or controls the transmission and reception of data with an external device. The various sensors 103 include an in-vehicle camera, a vehicle speed sensor, and an acceleration sensor. The communication device 104 transmits / receives data to / from an external device. For example, the communication device 104 transmits the position information of the vehicle 10 acquired by the high-precision locator 101 to the information processing device 20, or transmits information about the managed object detected by various sensors 103. Information about the controlled object includes, for example, an image captured by an in-vehicle camera.

<Vehicle processor configuration>
FIG. 4 is a diagram showing an example of the configuration of the CPU 102 of the vehicle 10 according to the embodiment of the present invention. The CPU 102 executes a program stored in a storage device (not shown) in the vehicle 10 to execute a travel control unit 112, a first acquisition unit 113, a first detection unit 114, a first management unit 115, and a first transmission / reception. It constitutes a part 116.

Further, the CPU 102 may be configured to control the processing of each part described later and execute the processing related to the traveling control or the road management of the vehicle 10.

The travel control unit 112 controls the travel of the vehicle 10 using various data. For example, the travel control unit 112 controls the automatic driving of the vehicle 10, and controls the high-precision locator 101, various sensors 103, and the communication device 104.

The first acquisition unit 113 acquires each sensor information sensed by various sensors 103. Each sensor information includes, for example, at least one of acceleration information sensed by an acceleration sensor, image information captured by an in-vehicle camera, and angular velocity information sensed by an angular velocity sensor.

Further, the first acquisition unit 113 may acquire the position information measured by the high-precision locator 101. The acquired high-precision position information is output to the first management unit 115.

The first detection unit 114 detects a predetermined managed object on the road by using the sensor information acquired by the in-vehicle sensors of various sensors 103. For example, the first detection unit 114 detects a predetermined managed object by recognizing an object using an image captured by an in-vehicle camera, or compares it with a past image to detect a portion different from the past image. It is detected as a controlled object. Further, the first detection unit 114 recognizes the vibration state of the road surface by using the acceleration sensor and the angular velocity sensor, and detects the controlled object based on this vibration state. When each sensor information is transmitted from the vehicle 10 to the information processing device 20, the first detection unit 114 may be provided in the information processing device 20.

Controlled objects alter, for example, objects related to road degradation, installations along the road, obstacles that impede driving on the road, people or vehicles on the road, and control of imaging devices contained in in-vehicle sensors. Contains at least one of the objects.

Objects related to road deterioration include, for example, road ruts, hazy lane markings (white lines, center lines, etc.), signs, signs, puddles, vehicle vibration points (potholes, pumps, steps, manholes, joints, etc.). And so on. By detecting these objects, it becomes possible to properly carry out road repairs or contact a predetermined management company as an example.

Roadside installations include, for example, planting, rubble, earth and sand. By detecting these objects, as an example, it is possible to grasp the timing of logging of plants, contact the management company of the objects, and contact the government office to request the removal of earth and sand, etc. become.

Obstacles that hinder driving on the road are, for example, objects that indicate lane restrictions (color cones (registered trademarks), triangular lights, regulation lines, etc.), places that are not accessible due to disasters (landslides, avalanche, flooding, etc.), puddles, and vehicles. Includes vibration points (potholes, pumps, steps, manholes, joints, etc.), low-positioned curved mirrors, falling objects such as cardboard. By detecting these objects, as an example, notifying nearby users (drivers) that they are out of service, contacting the object management company, and removing objects that interfere with driving. Will be possible.

People or vehicles on the road include, for example, sidewalks and road pedestrians or bicycles. By detecting these objects, it becomes possible to manage the number of people and vehicles, manage this number, and contact the company as an example.

Objects that change the control of the image pickup device included in the in-vehicle sensor include, for example, changes in camera control, and specific examples include front and rear tunnel entrances or exits, and glass-walled buildings (receives sunlight reflection). , Including places where there are few light sources other than the own vehicle light at night. By detecting these objects, it becomes possible to change the importance of the control parameter so as to give priority to LiDAR or the like rather than the camera as an example.

When at least one of the above-mentioned managed objects is detected, the first management unit 115 identifies the position information at the time of detection, and the position information and the information about the detected managed object are obtained. To manage the condition of the road using. Road condition management will be described later. When a part of the road management function of the first management unit 115 is provided in another device (for example, the information processing device 20), the first management unit 115 includes the specified position information and the information about the management object. May be controlled to be transmitted to a predetermined information processing device, for example, the information processing device 20.

Under the control of the first management unit 115, the first transmission / reception unit 116 transmits information about the management object and position information to the information processing device 20 via the communication device 104. Further, the first transmission / reception unit 116 may transmit the sensor information and the position information of various sensors acquired by the first acquisition unit 113 to the information processing apparatus 20. Further, the first transmission / reception unit 116 may transmit the identification information (ID) of the vehicle 10 to the information processing apparatus 20 together with the information about the management target and the position information.

As a result, if the management target is detected on the vehicle 10 side and the high-precision position information is measured by the high-precision locator 101, the position information (for example, the position information in lane units) and the management target can be obtained on the vehicle 10 side. Will be able to manage. Further, depending on the type and category of the detected managed object, the vehicle 10 can notify other vehicles connected to the vehicle 10 about the state of the managed object. For example, when the managed object belongs to the category of no lane (cannot drive in the lane), it is possible to notify the surrounding vehicles of which lane is not able to drive.

<Configuration of information processing device>
FIG. 5 is a diagram showing an example of the configuration of the information processing apparatus 20 according to the embodiment of the present invention. The information processing device 20 includes one or more processing units (CPUs) 210, one or more network communication interfaces 220, a storage device 230, a user interface 250, and one or more for interconnecting these components. Communication bus 270 is included. The user interface 250 is not always necessary.

The storage device 230 is a high-speed random access memory such as a DRAM, a SRAM, or another random access solid-state storage device. Further, the storage device 230 may be a non-volatile memory such as one or more magnetic disk storage devices, an optical disk storage device, a flash memory device, or another non-volatile solid-state storage device. Further, the storage device 230 may be a non-temporary recording medium that can be read by a computer.

Further, as another example of the storage device 230, one or a plurality of storage devices installed remotely from the CPU 210 may be used. In certain embodiments, the storage device 230 stores programs, modules and data structures executed by the CPU 210, or a subset thereof.

The storage device 230 stores the data used by the information processing system 1. For example, the storage device 230 stores data related to road management of the vehicle 10. As a specific example, a dynamic map, an HD map, reason management information, and the like are stored in the storage device 230.

FIG. 6 is a diagram showing an example of a database according to an embodiment of the present invention. In the example shown in FIG. 6, the storage device 230 stores the dynamic map data as a high-precision map database. As described above, the dynamic map data includes static information SI1, quasi-static information SI2, quasi-dynamic information MI1, and dynamic information MI2, and their respective information is associated with each other.

The static information SI1 included in the dynamic map data includes an HD map, and the HD map includes feature data. This feature data is basic information when an application uses a dynamic map, and includes data on features such as traffic lights, roadways, and lanes.

FIG. 7 is a diagram showing an example of road management information according to an embodiment of the present invention. In the example shown in FIG. 7, the road management information is stored in the storage device 230, and includes the type and position information of the management object, date and time information, image information, and the like in association with the vehicle ID.

The "vehicle ID" shown in FIG. 7 is information that can identify the vehicle. The information of the "managed object" is the managed object detected by each vehicle 10. The “position information” indicates the position where the management object is detected, and is the highly accurate position information that can be specified for each lane. "Date and time information" is information indicating the date and time when the managed object is detected. The image information is information on an image including a management object. In addition to the information shown in FIG. 7, the road management information may include categories of objects to be managed (disaster, lane interruption, falling objects, obstruction of travel, repair, grasping the number, etc.).

Returning to FIG. 5, the CPU 210 that executes the process related to the road management of the vehicle 10 according to the present embodiment will be described. The CPU 210 constitutes a road management unit 212, a second transmission / reception unit 213, a second acquisition unit 214, a second specific unit 215, and a second management unit 216 by executing a program stored in the storage device 230.

The CPU 210 is configured to control the processing of each part described later and execute the processing for managing the state of the road based on the management object detected by using the sensor information sensed by each vehicle 10.

The road management unit 212 controls the management of the road on which each vehicle 10 travels by using various data. For example, when the road management unit 212 acquires information on a management object and position information from each vehicle 10, the road management unit 212 links the two to control road management at a highly accurate position.

The second transmission / reception unit 213 transmits / receives data to / from the external device via the network communication interface 220. For example, the second transmission / reception unit 213 is configured as a reception unit that receives data, signals, etc. from the vehicle 10 and each positioning satellite 30, and is also configured as a transmission unit that transmits data, signals, etc. to the vehicle 10 and each positioning satellite 30. Will be done. As a specific example, the second transmission / reception unit 213 receives the position information acquired by the high-precision locator 101 from each vehicle 10, and transfers the road condition information including the road condition to each vehicle 10 located in a predetermined area. Send.

The second acquisition unit 214 acquires map data having a predetermined accuracy level that can be managed in lane units. For example, the second acquisition unit 214 acquires an HD map having a map information level of 500 or higher from the storage device 230.

Further, the second acquisition unit 214 sequentially acquires the position information of each vehicle 10 output by a locator (for example, a high-precision locator 101) capable of measuring the position in lane units based on the signal from the satellite positioning system. For example, the second acquisition unit 214 acquires the position information of the vehicle 10 received by the second transmission / reception unit 213 in order. The second acquisition unit 214 may directly acquire the position information of each vehicle 10 via the network communication interface 220.

In addition, the second acquisition unit 214 acquires information on the managed object on the road, which is detected by using the sensor information acquired by the in-vehicle sensor, from each vehicle 10. For example, the second acquisition unit 214 acquires information on a predetermined management object detected by using image recognition of an image captured by an in-vehicle camera, threshold value determination of acceleration information by an acceleration sensor, or the like from the second transmission / reception unit 213. do. Further, the second acquisition unit 214 may acquire sensor information from each vehicle 10.

The second specifying unit 215 identifies the first position where the controlled object is detected by using the map data having a predetermined accuracy level that can be managed for each lane. For example, the second specifying unit 215 identifies the first position where the management object is detected on the map data by using the highly accurate position information acquired by the second acquisition unit 214.

The second management unit 216 manages the state of the road at the specified first position based on the information regarding the detected managed object. For example, as shown in the example shown in FIG. 7, the second management unit 216 has the detected position information associated with the vehicle ID, the type of the management object included in the information about the management object, the image information, and the date and time information. And manage. Further, the second management unit 216 may associate information indicating the type of the management target with the first position in the map data.

As a result, when a management object on the road is detected, it becomes possible to easily manage the road condition using appropriate position information. For example, managed objects such as non-travelable lanes, falling objects, and interruptions in the event of a disaster are associated with highly accurate positions (for example, in lane units), so roads can be managed with high accuracy and appropriately. become able to.

Further, the second management unit 216 may include updating the state of the road at the first position in the map data. For example, the second management unit 216 updates the state of the road at this first position in the road management information in relation to the first position of the HD map based on the information about the management object. The HD map and the reason management information are associated with each other by using, for example, location information.

This makes it possible to update the road condition in relation to the first position on the map data, and when the map data is referenced by other devices, etc., provide the updated road condition. Will be possible.

Further, when the map data includes the first information including static data and the second information including dynamic data, the second management unit 216 states the road state included in the second information based on the management object. May include updating. For example, the second management unit 216 manages dynamically changeable lane restrictions, lane interruption states at the time of a disaster, etc. as dynamic data of map data, associates them with location information or feature data, and manages them. Update road conditions based on objects. The dynamic data is, for example, any of the above-mentioned quasi-static information SI2, quasi-dynamic information MI1, and dynamic information MI2.

As a result, it is possible to distribute the updated road condition by managing the road condition based on the management object that can change dynamically as the road condition included in the dynamic data of the map data. become. As a result, it becomes possible to notify the devices around the managed object of the current state.

Further, the second management unit 216 may include transmitting information about the management target to another information processing device specified according to the type of the management target. For example, if the managed object corresponds to the following types, the second management unit 216 transmits the position information and the information (image, etc.) about the managed object to the information processing device of the road management company.
・ Things that cover roads and signs (planting, rubble, garbage, etc.)
・ Features such as roads, signs, lane markings, etc. that need repair ・ Parking on the street (including queues in parking lots, etc.)
・ Falling objects (cardboard, puncture factors (screws, nails, etc.))
・ Vehicle vibration locations, locations that affect ride quality, locations that are out of service due to disasters, etc. (landslides, flooding, bridge drop locations, etc.)

In addition, if the managed object corresponds to the following types, the second management unit 216 will provide the vehicle or the like within a predetermined distance from the position of the managed object with the position information and information (images, etc.) regarding the managed object. And send.
・ Lane restrictions such as construction and accidents ・ Non-communication due to disasters (landslides, etc.)
・ Traffic volume (congestion of people)
・ Temporary installation on the road (color cone (registered trademark), triangular light, etc.)
-Changes in camera control Note that the above example is an example, and information indicating the state of the controlled object may be transmitted to an appropriate device.

Further, the second management unit 216 may include managing the state of the road when the object to be managed is detected more than a predetermined number of times within a predetermined range. For example, when the same controlled object is detected more than a predetermined number of times in the same predetermined area, the second management unit 216 is not a erroneously detected controlled object or a moving object, but the same controlled object. It is determined that the object is a managed object that exists at the position. The second management unit 216 manages the condition of the road based on this management object.

As a result, the managed object existing at a predetermined position can be managed, and the managed object that moves can be excluded. As a result, the reliability of the road management state can be improved.

Further, the second management unit 216 may include managing the state of the road when the object to be managed is detected more than a predetermined number of times within a predetermined time. For example, if the same controlled object is detected more than a predetermined number of times within a predetermined time (for example, 10 minutes), the second management unit 216 may use a falsely detected controlled object or a temporary controlled object. It is determined that the object is a controlled object that exists constantly. The second management unit 216 manages the condition of the road based on this management object.

As a result, it is possible to manage the controlled object that exists constantly, and it is possible to eliminate the controlled object that exists instantaneously or temporarily. As a result, the reliability of the road management state can be improved. The second management unit 216 may manage the state of the road based on the management object detected within a predetermined range and a predetermined number of times or more within a predetermined time.

Further, the information processing apparatus 20 may cooperate with a server that manages meteorological information, acquire meteorological data, and associate the map data with the meteorological data. In this case, the second specifying unit 215 of the information processing apparatus 20 specifies the position on the map data of the predetermined vehicle 10 and specifies the meteorological data of the specified position. In addition, the second specifying unit 215 specifies the weather forecast in the traveling direction of the vehicle 10 or after a predetermined time in the destination area or at the estimated time of arrival.

Next, in the second management unit 216, for example, the traveling direction or destination of the vehicle 10 is a heavy rain forecast, and there is a road or lane in the traveling direction or destination area that may be flooded or inundated by heavy rain. In that case, the road or lane may be notified to the vehicle 10 in advance. The second management unit 216 can specify whether or not a road that may be flooded or inundated due to heavy rain has been managed as a management target in the past. Further, if there is an application capable of presenting the inundation area at the time of a disaster, the information processing apparatus 20 may cooperate with the application to acquire the data of the inundation area.

Further, the information processing apparatus 20 may add virtual information on the map data to notify the vehicle 10 of the danger. For example, it is possible to estimate the depth of inundation according to the height of inundation on the road during heavy rain. Therefore, the second management unit 216 of the information processing apparatus 20 sets a virtual line in advance for a feature (for example, a utility pole, a traffic light, etc.) extending in the height direction. For example, the first line is flooded 1 m, the second line is flooded 2 m, and the like.

For example, there is a recessed road that is flooded during heavy rain, and no vehicle is detected as a flooded road as a management target unless it is traveling on this flooded recessed road. Even in this case, on the road before arriving at this recessed road, the vehicle 10 has a virtual line such as a traffic light set on the map data and an actual flood line detected by an in-vehicle sensor or the like. By comparing, it is possible to predict how many meters are currently flooded, and it is possible to grasp the flooded road ahead in the direction of travel.

As a result, by comparing the virtual information with the current state in advance, it is possible to detect in advance the danger that may approach the vehicle 10.

<Example of detection of controlled object>
FIG. 8 is a diagram showing an example of detecting a controlled object according to an embodiment of the present invention. In the example shown in FIG. 8, the first detection unit 114 of the vehicle 10 or the information processing device 20 detects the object A1 on the road. For example, the first detection unit 114 performs object recognition using the captured image captured by the vehicle-mounted camera, and detects the object A1. For example, the first detection unit 114 may detect an object A1 having a predetermined size or larger on the road and classify it into a category of obstacles that hinder traveling.

In addition, the first detection unit 114 detects cracks A2 on the road. For example, the first detection unit 114 recognizes an object using an image captured by an in-vehicle camera and detects a crack A2. Regarding object recognition, the first detection unit 114 may learn the controlled object to be detected in advance and detect the controlled object by using this learned model. The trained algorithm includes an inference algorithm that inputs an image and outputs a recognized controlled object.

In addition, the first detection unit 114 detects the planting A3 that covers the lane marking along the road. For example, the first detection unit 114 detects an object covering the lane marking using the captured image captured by the vehicle-mounted camera. The first detection unit 114 may detect any object that blocks the lane marking. Further, the first detection unit 114 may detect an object covering the lane marking by comparing with a past image.

When the first detection unit 114 is provided in the vehicle 10, the first transmission / reception unit 116 captures an image at the time of detection (for example, an image as shown in FIG. 8) when the controlled object is detected by the first detection unit 114. Information related to the management object including the above and the position information at the time of detection are transmitted to the information processing apparatus 20.

<Operation processing>
Next, the processing on the vehicle 10 side of the information processing system 1 and the processing on the information processing device 20 side will be described. FIG. 9 is a flowchart showing an example of processing on the vehicle side according to the embodiment of the present invention. The process shown in FIG. 9 is a process executed by each vehicle 10 while traveling.

In step S102, the first acquisition unit 113 of the vehicle 10 acquires various sensor information from the vehicle-mounted sensor. The various sensor information may include image information, acceleration information, and the like.

In step S104, the first acquisition unit 113 of the vehicle 10 acquires the position information of the vehicle 10 from the high-precision locator 101. The order of steps S102 and S104 does not matter.

In step S106, the first detection unit 114 determines whether or not the controlled object has been detected based on the acquired image information and acceleration information. If the controlled object is detected (step S106-YES), the process proceeds to step S108, and if the controlled object is not detected (step S106-NO), the process returns to step S102.

In step S108, the first transmission / reception unit 116 transmits information related to the managed object and position information to the information processing apparatus 20.

According to the above processing, when the vehicle 10 is equipped with the high-precision locator 101, it is possible to acquire the position information of the vehicle 10 whose position can be measured in lane units. Further, the vehicle 10 detects a managed object on the road using various sensor information, and transmits information related to the managed object and highly accurate position information to the information processing apparatus 20.

FIG. 10 is a flowchart showing an example of processing of the information processing apparatus 20 according to the embodiment of the present invention.
In step S202, the second acquisition unit 214 determines whether or not the position information transmitted from the vehicle 10 and the information related to the management object have been acquired. If both information are acquired (step S202-YES), the process proceeds to step S204, and if both information are not acquired (step S202-NO), the process returns to step S202.

In step S204, the second specifying unit 215 identifies the first position where the managed object is detected by using the map data having a predetermined accuracy level that can be managed for each lane and the acquired position information. ..

In step S206, the second management unit 216 executes a process of managing the state of the road at the first position on the map data based on the information about the management object.

FIG. 11 is a flowchart showing an example of the state management process according to the embodiment of the present invention.
In step S302, the second management unit 216 updates the state of the first position on the map data based on the detected managed object and the position information. For example, the second management unit 216 updates the state of the road at the first position where the controlled object is detected by using the information related to the detected controlled object. Specifically, the second management unit 216 associates information such as lane regulation, flooding, and falling objects with the first position.

In step S304, the second management unit 216 determines whether or not the notification process is unnecessary according to the type or category of the managed object. If the notification process is unnecessary (step S304-YES), the process ends, and if the notification process is required (step S304-NO), the process proceeds to step S306.

In step S306, the second management unit 216 specifies the notification destination based on the type of the managed object. As the notification destination, for example, there are a road management company, a vehicle 10 in the vicinity of a predetermined position, and the like. Regarding the identification of the notification destination, the second management unit 216 may refer to, for example, the contact information of the notification destination associated with the type of the managed object. The contact information is stored, for example, in the storage device 230.

In step S308, the second management unit 216 notifies the specified notification destination of the content according to the management target. For example, information such as lane restrictions, flood caution, and repair roads is notified.

According to the above processing, by acquiring the information about the management object detected by each vehicle 10 and the highly accurate position information, the management object can be easily managed by using the highly accurate position. It will be like.

Although one embodiment of the present invention has been described in detail above, the present invention is not limited to the above embodiment, and various modifications and changes can be made within the scope of the claims. For example, in the present invention, with respect to the processing executed by the vehicle 10 or the information processing apparatus 20, a part of the processing may be transferred to another information processing apparatus, or a plurality of information processing apparatus may be integrated as appropriate.

<Modification example>

Further, in the above-described embodiments and modifications, the traveling of the vehicle 10 has been described, but the technique of the present disclosure can also be applied to an air vehicle traveling in a traveling lane. The flying object includes, for example, an unmanned or manned flying object, a drone, and the like.

1 ... Information processing system, 10 ... Vehicle, 20 ... Information processing device, 30 ... Positioning satellite, 101 ... High-precision locator, 102 ... Processor, 103 ... Various sensors, 104 ... Communication device, 112 ... Travel control unit, 113 ... No. 1 acquisition unit, 114 ... first detection unit, 115 ... first management unit, 116 ... first transmission / reception unit, 210 ... CPU, 212 ... road management unit, 213 ... second transmission / reception unit, 214 ... second acquisition unit, 215 ... 2nd specific unit, 216 ... 2nd management unit, 220 ... network communication interface, 230 ... storage device, 250 ... user interface

Claims (10)

An information processing method executed by an information processing device including a processor.
The processor
Acquiring information about managed objects on the road, which is detected using sensor information acquired by in-vehicle sensors,
Identifying the first position where the controlled object is detected using map data having a predetermined accuracy level that can be managed on a lane-by-lane basis.
An information processing method for performing state management of the road at the first position based on information about the managed object. Performing the above state management is
The information processing method according to claim 1, wherein the map data includes updating the state of the road at the first position. Performing the above state management is
When the map data includes the first information including static data and the second information including dynamic data, updating the state of the road included in the second information based on the managed object. The information processing method according to claim 2, which includes. Performing the above state management is
The information processing method according to any one of claims 1 to 3, which comprises transmitting information about the controlled object to another information processing device specified according to the type of the controlled object. Performing the above state management is
The information processing method according to any one of claims 1 to 4, which comprises managing the state of the road when the controlled object is detected more than a predetermined number of times within a predetermined range. Performing the above state management is
The information processing method according to any one of claims 1 to 4, which comprises managing the state of the road when the controlled object is detected a predetermined number of times or more within a predetermined time. The information processing device includes an in-vehicle device.
Performing the above state management is
The information processing method according to any one of claims 1 to 6, wherein the vehicle-mounted device transmits the position information regarding the first position and the information regarding the managed object to a predetermined information processing apparatus. .. The controlled object is an object related to deterioration of the road, an object installed along the road, an obstacle obstructing traveling on the road, a person or a vehicle on the road, and control of an image pickup device included in the in-vehicle sensor. The information processing method according to any one of claims 1 to 6, which comprises at least one object that changes the information processing. For the processor included in the information processing device
Acquiring information about managed objects on the road, which is detected using sensor information acquired by in-vehicle sensors,
Identifying the first position where the controlled object is detected using map data having a predetermined accuracy level that can be managed on a lane-by-lane basis.
A program for executing the state management of the road at the first position based on the information about the managed object. An information processing device that includes a processor
The processor
Acquiring information about managed objects on the road, which is detected using sensor information acquired by in-vehicle sensors,
Identifying the first position where the controlled object is detected using map data having a predetermined accuracy level that can be managed on a lane-by-lane basis.
An information processing device that manages the state of the road at the first position based on the information about the managed object.

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