Map generation device and map generation system

Abstract

To appropriately generate a map necessary for safe vehicle control.SOLUTION: A map generation unit 174 of a map generation apparatus 60 has: a first generation unit configured to generate a map of a travel section based on recognition information recognized by a recognition unit 13, record, in a storage unit 12, map information corresponding to a section in which the success of completion is determined by a determination unit 175, and record, in the storage unit 12, section information indicating a section in which the failure of completion is determined by the determination unit 175, together with position information of an own vehicle; and a second generation unit configured to generate a map of the section in which the failure of completion is determined based on the recognition information of the section recognized by the recognition unit 13 when traveling next time, update the map by adding map information of the section to the map information recorded in the storage unit 12 by the first generation unit, and rewrite the section information recorded in the storage unit 12 by the first generation unit.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a map generating device and a map generating system that generate a map used to estimate the position of a vehicle. [Background technology]

[0002] Conventionally, as this type of device, a device configured to create a map using feature points extracted from a captured image acquired by a camera mounted on a traveling vehicle has been known (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-174910 Summary of the Invention [Problem to be solved by the invention]

[0004] With conventional technology, the accuracy of map information can be compromised in cases where, for example, other lanes are obscured by other vehicles, or when the road has so many lanes that it is not possible to create a map of the entire road at once. Generating maps necessary for vehicle control will enable smooth vehicle movement, improving traffic convenience and safety, and thereby contributing to the development of sustainable transportation systems. [Means for solving the problem]

[0005] A map generating device according to a first aspect of the present invention includes a recognition unit that recognizes the surrounding environment of a traveling vehicle, a map generating unit that generates a map based on recognition information from the recognition unit, a position estimation unit that estimates the position of the vehicle on the map generated by the map generating unit, a determination unit that determines whether the map generated by the map generating unit is complete, and a storage unit that stores map information indicating the map generated by the map generating unit. an input unit that inputs information indicating that degenerate control of the autonomous driving level has been performed or that a driver of the vehicle has intervened in a driving operation from a control unit that performs autonomous driving control that automatically controls at least the acceleration and deceleration of the vehicle using map information recorded in the storage unit;The map generation unit includes a first generation unit that generates a map of the travel section based on the recognition information recognized by the recognition unit, records map information corresponding to the section determined to be complete by the determination unit in the storage unit, and records section information indicating the section determined to be complete or not by the determination unit together with position information of the vehicle in the storage unit, and a second generation unit that generates a map for the section determined to be complete or not based on the recognition information of the section recognized by the recognition unit during the next travel, updates the map information recorded in the storage unit by the first generation unit by adding the map information of the section, and rewrites the section information recorded in the storage unit by the first generation unit. The determination unit determines whether the recognition information recognized by the recognition unit is complete or not when the information about the driving lane adjacent to the driving lane on which the vehicle is driving is insufficient or when the information about the features on the side of the road on which the vehicle is driving is insufficient. do. A map generation system according to a second aspect of the present invention includes a map generation device according to the first aspect and an external server configured to be able to communicate with a vehicle, and the external server stores recognition information acquired by the vehicle and other vehicles, and map information generated by the vehicle and other vehicles, and provides information to the vehicle and / or other vehicles using the stored recognition information and / or map information. [Effects of the Invention]

[0006] According to the present invention, it is possible to appropriately generate a map required for safe vehicle control. [Brief explanation of the drawings]

[0007] [Figure 1] 1 is a block diagram showing an overall configuration of a vehicle control system according to an embodiment of the present invention; [Figure 2] FIG. 1 is a block diagram showing a configuration of a main part of a map generating device according to an embodiment. [Figure 3A] FIG. 10 is a diagram showing an example of a camera image. [Figure 3B] FIG. 10 is a diagram illustrating extracted feature points. [Figure 3C] FIG. 10 is a diagram illustrating selected feature points. [Figure 4A] 6 is a flowchart illustrating an example of processing by a program executed by a controller. [Figure 4B] 6 is a flowchart illustrating an example of processing by a program executed by a controller. [Figure 4C] 6 is a flowchart illustrating an example of processing by a program executed by a controller. [Figure 5] FIG. 10 is a diagram illustrating the configuration of a map generation system according to a third modification. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. A map generating device according to an embodiment of the present invention can be applied to a vehicle having an automatic driving function, i.e., an automatic driving vehicle. The vehicle to which the map generating device according to the embodiment is applied may be referred to as the host vehicle to distinguish it from other vehicles. The host vehicle may be an engine vehicle having an internal combustion engine (engine) as a driving source, an electric vehicle having a traction motor as a driving source, or a hybrid vehicle having an engine and a traction motor as driving sources. The host vehicle can travel not only in an automatic driving mode in which no driving operation by the driver is required, but also in a manual driving mode in which the driver operates the vehicle.

[0009] First, a schematic configuration of a host vehicle related to autonomous driving will be described. Fig. 1 is a block diagram showing a schematic overall configuration of a vehicle control system 100 of the host vehicle having a map generation device according to an embodiment. As shown in Fig. 1, the vehicle control system 100 mainly includes a controller 10, an external sensor group 1 and an internal sensor group 2, each of which is communicatively connected to the controller 10, an input / output device 3, a positioning unit 4, a map database 5, a navigation device 6, a communication unit 7, and a driving actuator AC.

[0010] The external sensor group 1 is a collective term for a plurality of sensors (external sensors) that detect the external situation, which is information about the surroundings of the host vehicle. For example, the external sensor group 1 includes a lidar that measures the distance from the host vehicle to surrounding obstacles by measuring scattered light in response to light irradiated in all directions of the host vehicle, a radar that detects other vehicles and obstacles around the host vehicle by irradiating electromagnetic waves and detecting reflected waves, and a camera that is mounted on the host vehicle and has an imaging element (image sensor) such as a CCD or CMOS that captures images of the surroundings (front, rear, and sides) of the host vehicle.

[0011] The internal sensor group 2 is a collective term for multiple sensors (internal sensors) that detect the driving state of the host vehicle. For example, the internal sensor group 2 includes a vehicle speed sensor that detects the vehicle speed of the host vehicle, an acceleration sensor that detects the longitudinal acceleration and the lateral acceleration (lateral acceleration) of the host vehicle, a rotation speed sensor that detects the rotation speed of the driving source, a yaw rate sensor that detects the rotation angular velocity around the vertical axis of the center of gravity of the host vehicle, etc. The internal sensor group 2 also includes sensors that detect the driving operations of the driver in manual driving mode, such as operation of the accelerator pedal, operation of the brake pedal, operation of the steering wheel, etc.

[0012] The input / output device 3 is a general term for devices that input commands from the driver and output information to the driver. For example, the input / output device 3 includes various switches through which the driver inputs various commands by operating operating members, a microphone through which the driver inputs commands by voice, a display that provides information to the driver via displayed images, a speaker that provides information to the driver by voice, etc.

[0013] The positioning unit (GNSS unit) 4 has a positioning sensor that receives positioning signals transmitted from positioning satellites. The positioning satellites are artificial satellites such as GPS satellites and quasi-zenith satellites. The positioning unit 4 measures the current position (latitude, longitude, altitude) of the vehicle using the positioning information received by the positioning sensor.

[0014] The map database 5 is a device that stores general map information used in the navigation device 6, and is configured with, for example, a hard disk or semiconductor elements. The map information includes road position information, road shape information (curvature, etc.), and position information of intersections and branch points. Note that the map information stored in the map database 5 is different from the highly accurate map information stored in the memory unit 12 of the controller 10.

[0015] The navigation device 6 is a device that searches for a target route on roads to a destination input by the driver and provides guidance along the target route. The input of the destination and guidance along the target route are performed via the input / output device 3. The target route is calculated based on the current position of the vehicle measured by the positioning unit 4 and map information stored in the map database 5. The current position of the vehicle can also be measured using detection values ​​from the external sensor group 1, and the target route can be calculated based on this current position and high-precision map information stored in the memory unit 12.

[0016] The communication unit 7 communicates with various servers (not shown) via networks including wireless communication networks such as the Internet and mobile phone networks, and acquires map information, driving history information, traffic information, and the like from the servers periodically or at any timing. In addition to acquiring driving history information, the communication unit 7 may also transmit driving history information of the vehicle to the server. Networks include not only public wireless communication networks but also closed communication networks established for each predetermined management area, such as wireless LAN, Wi-Fi (registered trademark), Bluetooth (registered trademark), and the like. The acquired map information is output to the map database 5 and the storage unit 12, where the map information is updated.

[0017] Actuators AC are driving actuators for controlling the driving of the host vehicle. When the driving source is an engine, actuators AC include a throttle actuator that adjusts the opening of the engine's throttle valve (throttle opening). When the driving source is a driving motor, actuators AC include the driving motor. Actuators AC also include a brake actuator that operates the host vehicle's braking device and a steering actuator that drives the steering device.

[0018] The controller 10 is composed of an electronic control unit (ECU). More specifically, the controller 10 includes a computer having an arithmetic unit 11 such as a CPU (microprocessor), a storage unit 12 such as a ROM and RAM, and other peripheral circuits (not shown) such as an I / O interface. Note that although multiple ECUs with different functions, such as an engine control ECU, a traction motor control ECU, and a braking device ECU, can be provided separately, for convenience, the controller 10 is shown in FIG. 1 as a collection of these ECUs.

[0019] The storage unit 12 stores highly accurate, detailed map information (referred to as high-accuracy map information). The high-accuracy map information includes road position information, road shape (curvature, etc.), road gradient information, intersection and branch point position information, types of road dividing lines such as white lines and their positions, the number of lanes, lane width and position information for each lane (information on the center position of the lane and boundary lines of the lane positions), position information of landmarks (buildings, traffic lights, signs, etc.) as markers on the map, and road surface profile information such as road surface irregularities. In the embodiment, center lines, lane boundary lines, outer lane lines, etc. are collectively referred to as road dividing lines. The high-precision map information stored in the memory unit 12 includes map information obtained from outside the vehicle via the communication unit 7 (referred to as external map information), and a map created by the vehicle itself using detection values ​​from the external sensor group 1 or detection values ​​from the external sensor group 1 and the internal sensor group 2 (referred to as internal map information).

[0020] The external map information is, for example, information on a map (called a cloud map) acquired via a cloud server, and the internal map information is information on a map (called an environmental map) made up of three-dimensional point cloud data generated by mapping using a technology such as SLAM (Simultaneous Localization and Mapping). The external map information is shared between the vehicle and other vehicles, whereas the internal map information is map information unique to the vehicle (for example, map information that is solely possessed by the vehicle). For roads that the vehicle has not yet traveled on, newly constructed roads, etc., the vehicle itself creates an environmental map. The internal map information may be provided to a server device or other vehicles via the communication unit 7. In addition to the high-precision map information described above, the storage unit 12 also stores information such as the vehicle's travel trajectory information, various control programs, and threshold values ​​used in the programs.

[0021] The calculation unit 11 has, as functional components, a vehicle position recognition unit 13, an external environment recognition unit 14, a behavior plan generation unit 15, a driving control unit 16, and a map generation unit 17.

[0022] The vehicle position recognition unit 13 recognizes (may also be called estimates) the position of the vehicle on the map (vehicle position) based on the position information of the vehicle obtained by the positioning unit 4 and the map information of the map database 5. The vehicle position may be recognized (estimated) using high-precision map information stored in the memory unit 12 and information about the surroundings of the vehicle detected by the external sensor group 1, thereby enabling the vehicle position to be recognized with high precision. The vehicle's position can also be recognized by calculating the vehicle's movement information (movement direction, movement distance) based on the detection values ​​of the internal sensor group 2. When the vehicle's position can be measured by an external sensor installed on the road or beside the road, the vehicle's position can also be recognized by communicating with the sensor via the communication unit 7.

[0023] The external environment recognition unit 14 recognizes the external situation around the host vehicle based on signals from the external sensor group 1, such as a lidar, radar, and camera. For example, it recognizes the positions, speeds, and accelerations of surrounding vehicles (vehicles ahead and vehicles behind) traveling around the host vehicle, the positions of surrounding vehicles stopped or parked around the host vehicle, and the positions and states of other objects. Examples of other objects include signs, traffic lights, markings such as road dividing lines and stop lines, buildings, guardrails, utility poles, billboards, pedestrians, and bicycles. Examples of the states of other objects include the color of traffic lights (red, green, yellow), the movement speed and direction of pedestrians and bicycles, and the like. Some of the stationary objects among the other objects constitute landmarks that serve as indicators of locations on a map, and the external environment recognition unit 14 also recognizes the positions and types of the landmarks.

[0024] The behavior plan generation unit 15 generates a traveling trajectory (target trajectory) of the host vehicle from the current time to a predetermined time ahead based on, for example, a target route calculated by the navigation device 6, high-precision map information stored in the memory unit 12, the host vehicle position recognized by the host vehicle position recognition unit 13, and the external situation recognized by the external environment recognition unit 14. When there are multiple trajectories that are candidates for the target trajectory on the target route, the behavior plan generation unit 15 selects an optimal trajectory from among them that satisfies criteria such as compliance with laws and regulations and efficient and safe traveling, and sets the selected trajectory as the target trajectory. The behavior plan generation unit 15 then generates a behavior plan according to the generated target trajectory. The behavior plan generation unit 15 generates various behavior plans corresponding to overtaking driving to overtake a preceding vehicle, lane-changing driving to change the traveling lane, following driving to follow a preceding vehicle, lane-keeping driving to maintain the traveling lane without deviating from the traveling lane, decelerating driving, accelerating driving, etc. When generating the target trajectory, the behavior plan generation unit 15 first determines a driving mode and generates the target trajectory based on the driving mode.

[0025] In the autonomous driving mode, the driving control unit 16 controls the actuators AC so that the vehicle travels along the target trajectory generated by the behavior plan generation unit 15. More specifically, in the autonomous driving mode, the driving control unit 16 calculates a required driving force for achieving the target acceleration per unit time calculated by the behavior plan generation unit 15, taking into account the driving resistance determined by the road gradient, etc. Then, for example, the driving control unit 16 feedback-controls the actuators AC so that the actual acceleration detected by the internal sensor group 2 becomes the target acceleration. In other words, the driving control unit 16 controls the actuators AC so that the vehicle travels at the target vehicle speed and target acceleration. Note that in the manual driving mode, the driving control unit 16 controls the actuators AC in response to driving commands (such as steering operations) from the driver acquired by the internal sensor group 2.

[0026] While driving in manual driving mode, the map generation unit 17 uses detection values ​​detected by the external sensor group 1 to generate an environmental map of the area around the road on which the vehicle has traveled as internal map information. For example, edges that indicate the contours of objects are extracted from multiple frames of camera images acquired by a camera based on brightness and color information for each pixel, and feature points are extracted using the edge information. Feature points are, for example, intersections of edges, and correspond to corners of buildings or corners of road signs. The map generation unit 17 estimates the position and orientation of the camera according to the SLAM technology algorithm so that identical feature points converge to a single point across multiple frames of camera images, and calculates the three-dimensional position of the feature points. By performing this calculation process for each of the multiple feature points, an environmental map consisting of three-dimensional point cloud data is generated. It should be noted that instead of using a camera, data acquired by a radar or a lidar may be used to extract feature points of objects around the vehicle and generate an environmental map. In addition, when generating an environmental map, if the map generation unit 17 determines by object detection such as pattern matching processing that a geographically important feature (e.g., road dividing lines, traffic lights, signs, etc.) is included in the camera image, it adds the location information of points corresponding to the feature points of the feature based on the camera image to the environmental map and records it in the memory unit 12.

[0027] The vehicle position recognition unit 13 performs a process of recognizing the position of the vehicle in parallel with the map creation process by the map generation unit 17. That is, the vehicle position is estimated based on changes in the positions of feature points over time. The map creation process and the position recognition (estimation) process are performed simultaneously according to the algorithm of SLAM technology. The map generation unit 17 can generate an environmental map not only when driving in manual driving mode, but also when driving in automatic driving mode. If an environmental map has already been generated and stored in the memory unit 12, the map generation unit 17 may update the environmental map based on newly extracted feature points (which may also be called new feature points) from newly acquired camera images.

[0028] Incidentally, feature points used to generate an environmental map using SLAM technology must be unique feature points that are easily distinguishable from other feature points. In contrast, in actual vehicle control, it is necessary for information about features, such as road markings, to be included in the environmental map. In the embodiment, a map generation device is configured to perform the following processes (1) to (4), thereby appropriately generating an environmental map that includes information necessary for vehicle control.

[0029] (1) The feature points used to generate the environmental map are selected from among those extracted from camera images as unique feature points that are easy to distinguish from other feature points. If the feature points are not unique, it will be difficult to track the same feature points across multiple camera image frames. Therefore, while preferentially selecting unique feature points based on edge information such as building window frames, we avoid selecting feature points based on edge information of specific features such as road markings, signs, and traffic lights, which make it difficult to track the same feature points across multiple camera image frames.

[0030] (2) Information useful for recognizing (estimating) the vehicle's position is added to the environmental map. Because the environmental map does not contain information such as road markings that are necessary for recognizing the vehicle's position due to (1) above, the information such as road markings is added to the environmental map later (this can also be called embedding).

[0031] (3) When the environmental map is corrected, the information added in (2) above is re-added. Generally, in SLAM technology, errors accumulate because the vehicle recognizes its own position while moving. For example, when the vehicle travels around a road that is closed in a square shape, the accumulated errors cause the start and end points to not match. Therefore, when it is recognized that the vehicle's current position is on the previous travel trajectory, a loop closing process is performed in which the vehicle's position recognized using feature points (called new feature points) extracted from a camera image newly acquired at the same travel point as the previous one is set to the same coordinates as the vehicle's position previously recognized using feature points extracted from a camera image acquired during previous travel. In the embodiment, the loop closing process is called environmental map correction, and the 3D position information included in the environmental map is corrected. At this time, the information added in (2) above is deleted and added again to the corrected environmental map.

[0032] (4) The completion of the environmental map is determined. Specifically, it is checked whether the environmental map necessary for safe vehicle control has been generated. If it is determined that the map is not complete, the section information for the travel section is stored in the memory unit 12, and the next time the same section is traveled, a map is generated based on feature points extracted from newly acquired camera images. If it is determined that the map is complete, the environmental map can be used for vehicle control for automatic driving in that travel section. The following four examples (a) to (d) are examples of cases where the environmental map is judged to be incomplete. (a) When there is a defect (which may be called a deficiency or insufficiency) in the recognition information acquired while the vehicle is traveling. (b) When the vehicle is traveling in the autonomous driving mode to determine whether the environmental map is complete, the traveling control unit 16 degrades the autonomous driving level of the autonomous driving mode to a level lower than the current level. (c) When the vehicle is traveling using an environmental map in autonomous driving mode, a signal indicating that the driver has intervened in the driving operation is input from the internal sensor group 2. (d) When the difference between the position of a new feature point obtained based on the position of a lane marking or the like captured in a newly acquired camera image and the position of a point corresponding to the feature point of a lane marking or the like recorded in the environmental map generated during the previous driving exceeds a predetermined value. In the embodiment, if at least one of the above (a) to (d) is true, the environmental map is not determined to be complete, and a new map is generated based on feature points extracted from newly acquired camera images the next time the vehicle travels through the same section. In (a) above, cases where there is a gap in the recognition information acquired while the vehicle is traveling include, for example, when the lane next to the traveling lane is hidden due to the influence of another traveling vehicle, making it impossible to create a road map including lanes other than the traveling lane (even if it could be created, it would be incomplete as an environmental map), and when there are so many lanes on the traveling road that some lanes are outside the camera's field of view (the sides of the road are not visible), making it impossible to create a road map for lanes not visible in the camera image (even if it could be created, it would be incomplete as an environmental map).

[0033] The map generating device that performs the above processes (1) to (4) will now be described in more detail. Fig. 2 is a block diagram showing the configuration of a main part of a map generating device 60 according to an embodiment. The map generating device 60 is used to control the traveling operation of the host vehicle, and constitutes a part of the vehicle control system 100 shown in Fig. 1. As shown in Fig. 2, the map generating device 60 has a controller 10, a camera 1a, a radar 1b, and a lidar 1c.

[0034] The camera 1a constitutes part of the external sensor group 1 in Fig. 1. The camera 1a may be a monocular camera or a stereo camera, and captures images of the surroundings of the vehicle. The camera 1a is attached, for example, to a predetermined position in the front of the vehicle, continuously captures images of the space ahead of the vehicle at a predetermined frame rate, and sequentially outputs frame image data (simply referred to as camera images) as detection information to the controller 10. 3A is a diagram showing an example of a camera image of a certain frame captured by camera 1a. Camera image IM includes another vehicle V1 traveling ahead of the host vehicle, another vehicle V2 traveling in the right lane of the host vehicle, traffic lights SG around the host vehicle, pedestrians PE, traffic signs TS1 and TS2, buildings BL1, BL2, and BL3 around the host vehicle, outer roadway lines OL, and lane boundary lines SL.

[0035] The radar 1b in FIG. 2 is mounted on the host vehicle and detects other vehicles, obstacles, etc. around the host vehicle by emitting electromagnetic waves and detecting reflected waves. The radar 1b outputs detection values ​​(detection data) as detection information to the controller 10. The lidar 1c is mounted on the host vehicle and measures scattered light in response to irradiated light in all directions from the host vehicle to detect the distance from the host vehicle to surrounding obstacles. The lidar 1c outputs detection values ​​(detection data) as detection information to the controller 10.

[0036] The controller 10 includes a calculation unit 11 and a storage unit 12. The calculation unit 11 has, as functional components, an information acquisition unit 141, an extraction unit 171, a selection unit 172, a calculation unit 173, a generation unit 174, a determination unit 175, and a vehicle position recognition unit 13. The information acquisition unit 141 is included in, for example, the external environment recognition unit 14 in Fig. 1. The extraction unit 171, the selection unit 172, the calculation unit 173, the generation unit 174, and the determination unit 175 are included in, for example, the map generation unit 17 in Fig. 1. The storage unit 12 includes a map storage unit 121 and a trajectory storage unit 122 .

[0037] The information acquisition unit 141 acquires information used to control the traveling operation of the vehicle from the storage unit 12 (map storage unit 121). More specifically, the information acquisition unit 141 reads landmark information included in the environmental map from the map storage unit 121, and further acquires, from the landmark information, information indicating the positions of lane markings on the road on which the vehicle is traveling and the extension direction of those lane markings (hereinafter referred to as lane marking information). When the lane marking information does not include information indicating the direction in which the lane marks extend, the information acquisition unit 141 may calculate the direction in which the lane marks extend based on the positions of the lane marks. Alternatively, the information acquisition unit 141 may acquire information indicating the positions and directions in which the lane marks of the road on which the host vehicle is traveling from road map information or a white line map (information indicating the positions of white, yellow, and other lane markings) stored in the map storage unit 121.

[0038] The extraction unit 171 extracts edges that indicate the contour of an object from the camera image IM (illustrated in FIG. 3A) acquired by the camera 1a, and extracts feature points using the edge information. As described above, feature points are, for example, intersections of edges. FIG. 3B is a diagram illustrating feature points extracted by the extraction unit 171 based on the camera image IM of FIG. 3A. The black circles in the diagram represent feature points.

[0039] The selection unit 172 selects feature points for calculating three-dimensional positions from the feature points extracted by the extraction unit 171. In this embodiment, feature points included in features other than predetermined features (e.g., road dividing lines, traffic lights, traffic signs, etc.) are selected as unique feature points that are easily distinguishable from other feature points. FIG. 3C is a diagram illustrating feature points selected by the selection unit 172 based on FIG. 3B. Black circles in the diagram represent feature points. The illustrated predetermined features are merely examples, and at least one may be excluded.

[0040] The calculation unit 173 estimates the position and orientation of the camera 1a so that the same feature points converge to one point across multiple frames of camera images IM, and calculates the three-dimensional positions of the feature points. The calculation unit 173 calculates the three-dimensional positions of each of the multiple different feature points selected by the selection unit 172.

[0041] The generating unit 174 uses the three-dimensional positions of the different feature points calculated by the calculating unit 173 to generate an environmental map made up of three-dimensional point cloud data including information on each three-dimensional position.

[0042] The determination unit 175 determines whether the environmental map generated by the generation unit 174 is complete. As described above, the determination unit 175 determines that the map is not complete if at least one of the above (a) to (d) applies, and determines that the map is complete if none of the above (a) to (d) applies. Details of the determination process will be described later. In addition, the determination unit 175 also functions as a lane identification unit that identifies the driving lane in which the vehicle traveled as a specific lane based on the position of the vehicle estimated by the vehicle position recognition unit 13 described later while traveling in a driving section in which the environmental map has not been determined to be complete (in other words, it has been determined to be incomplete).

[0043] The vehicle position recognition unit 13 estimates the vehicle position on the environmental map based on the environmental map stored in the map storage unit 121. First, the vehicle position recognition unit 13 estimates the position of the host vehicle in the vehicle width direction. Specifically, the vehicle position recognition unit 13 uses machine learning (DNN (Deep Neural Network) or the like) technology to recognize road lane lines included in the camera image IM newly acquired by the camera 1a. The vehicle position recognition unit 13 recognizes the positions and extension directions of the lane lines included in the camera image IM on the environmental map based on lane line information acquired from landmark information included in the environmental map stored in the map storage unit 121. The vehicle position recognition unit 13 then estimates the relative positional relationship between the host vehicle and the lane lines in the vehicle width direction (positional relationship on the environmental map) based on the positions and extension directions of the lane lines on the environmental map. In this way, the position of the host vehicle in the vehicle width direction on the environmental map is estimated.

[0044] Next, the vehicle position recognition unit 13 estimates the position of the vehicle in the traveling direction. In detail, the vehicle position recognition unit 13 recognizes a landmark (e.g., building BL1) from a camera image IM (FIG. 3A) newly acquired by the camera 1a by processing such as pattern matching, and recognizes a feature point on the landmark from among the feature points extracted by the extraction unit 171. Furthermore, the vehicle position recognition unit 13 estimates the distance from the vehicle to the landmark in the traveling direction based on the position of the feature point of the landmark captured in the camera image IM. Note that the distance from the vehicle to the landmark may be calculated based on detection values ​​from the radar 1b and the lidar 1c.

[0045] The vehicle position recognition unit 13 searches for feature points corresponding to the landmarks in the environmental map stored in the map storage unit 121. In other words, feature points that match the feature points of the landmarks recognized from the newly acquired camera image IM are recognized from among the multiple feature points (point cloud data) that make up the environmental map. Next, the vehicle position recognition unit 13 estimates the position of the vehicle on the environmental map in the direction of travel based on the position of the feature point on the environmental map that corresponds to the feature point of the landmark and the distance in the direction of travel from the vehicle to the landmark. As described above, the vehicle position recognition unit 13 recognizes the position of the vehicle on the environmental map based on the estimated position of the vehicle on the environmental map in the vehicle width direction and the traveling direction.

[0046] The map storage unit 121 stores information about the environmental map generated by the generation unit 174. The trajectory storage unit 122 stores information indicating the travel trajectory of the host vehicle. The travel trajectory is represented as the host vehicle position on an environmental map, for example, recognized by the host vehicle position recognition unit 13 while the host vehicle is traveling.

[0047] <Explanation of the flowchart> An example of processing executed by the controller 10 of Fig. 2 according to a predetermined program will be described with reference to the flowcharts of Fig. 4A, Fig. 4B, and Fig. 4C. Fig. 4A shows processing before an environmental map is created, which is started, for example, in manual driving mode and repeated at a predetermined interval. Fig. 4B and Fig. 4C show processing performed in parallel with the map creation processing of Fig. 4A. Fig. 4B and Fig. 4C show processing after an environmental map is created, which is started, for example, in automatic driving mode and repeated at a predetermined interval.

[0048] In step S10 of FIG. 4A, the controller 10 acquires a camera image IM as detection information from the camera 1a, and the process proceeds to step S20.

[0049] In step S20, the controller 10 extracts feature points from the camera image IM using the extraction unit 171, and then the process proceeds to step S30.

[0050] In step S30, the controller 10 selects a feature point using the selection unit 172, and then proceeds to step S40. As described above, by selecting a feature point that is included in a feature other than road dividing lines, traffic lights, traffic signs, etc., it becomes possible to select a unique feature point that is easily distinguishable from other feature points.

[0051] In step S40, the controller 10 causes the calculation unit 173 to calculate the three-dimensional positions of the plurality of different feature points, and then proceeds to step S50.

[0052] In step S50, the controller 10 generates, by the generation unit 174, an environmental map made up of three-dimensional point cloud data including information on the three-dimensional positions of a plurality of different feature points, and then proceeds to step S60.

[0053] In step S60, the controller 10 acquires position information (distance from the vehicle to the feature) of a feature having a feature point that was not selected in step S30 among the feature points extracted in step S20, in other words, the predetermined feature (road dividing line, traffic light, traffic sign, etc.), and proceeds to step S70. This position information is obtained by estimating the distance from the vehicle to the feature based on the position of the feature point of the feature captured in the camera image IM. Note that the distance from the vehicle to the feature may also be acquired based on the detection value of the radar 1b or the lidar 1c.

[0054] In step S70, the controller 10 adds information about points corresponding to the feature points of the above-mentioned features to the point cloud data of the environmental map, and then proceeds to step S80. With this configuration, information about features such as lane lines is embedded in the environmental map. By adding information about lane lines, traffic lights, and traffic signs to the environmental map, it becomes possible to provide information about the positions of lane lines, traffic lights, and traffic signs that are visible from the host vehicle's position estimated based on the information about the environmental map to the host vehicle, based on the information about the environmental map.

[0055] In step S80, if the controller 10 recognizes that the position where the vehicle is traveling is on the past traveling trajectory, it corrects the three-dimensional position information contained in the environmental map by the loop closing process described above, and proceeds to step S90.

[0056] In step S90, the controller 10 determines whether or not occlusion exists. If there is a lane that is hidden by another vehicle V2 and does not appear in the camera image IM, such as the right lane in FIG. 3A, the controller 10 makes a positive determination in step S90 and proceeds to step S100. If there is a lane that is not visible in the camera image IM, it is not possible to create an environmental map of the road including that lane. Therefore, the controller 10 proceeds to step S100 to leave information indicating the existence of occlusion. On the other hand, if there is no lane that is hidden by another vehicle and does not appear in the camera image IM (in other words, if all lanes traveling in the same direction are visible in the camera image IM), the controller 10 makes a negative determination in step S90 and proceeds to step S110.

[0057] In step S100, the controller 10 records section information indicating a section where occlusion was detected while the host vehicle was traveling in the storage unit 12, and then proceeds to step S110. The section information includes position information indicating the position of the host vehicle estimated by the host vehicle position recognition unit 13.

[0058] In step S110, the controller 10 records the map information of the environmental map created during the processing of FIG. 4A in the map storage unit 121 of the storage unit 12, and ends the processing of FIG. 4A.

[0059] 4B, the controller 10 determines whether or not there is section information. If the above-mentioned section information is stored in the storage unit 12, the controller 10 makes an affirmative decision in step S201 and proceeds to step S202, and if no section information is stored, the controller 10 makes a negative decision in step S201 and proceeds to step S210.

[0060] In step S202, the controller 10 outputs information about the specific lane to the external device, and then the process proceeds to step S210. As described above, the specific lane is the driving lane in which the host vehicle traveled in the driving section in which the environmental map was determined to be incomplete.

[0061] In step S210, the controller 10 acquires a camera image IM as detection information from the camera 1a, and the process proceeds to step S220.

[0062] In step S220, the controller 10 extracts new feature points from the camera image IM using the extraction unit 171, and proceeds to step S230. Note that the feature points extracted in the processing of Fig. 4B are called new feature points even if they are points on the same object as the feature points extracted in the processing of Fig. 4A.

[0063] In step S230, the controller 10 selects new feature points using the selection unit 172, and proceeds to step S240. In step S230, new feature points based on edge information of predetermined features (road dividing lines, signs, traffic lights, etc.) and new feature points based on edge information of buildings and the like that are not predetermined features are selected.

[0064] In step S240, the controller 10 recognizes (estimates) the vehicle position based on the environmental map using the vehicle position recognition unit 13, and then the process proceeds to step S250.

[0065] In step S250, the controller 10 calculates the position difference and proceeds to step S260 in FIG. 4C. The position difference is the difference between the position of the new feature point of the predetermined feature selected in step S230 and the position of the point corresponding to the feature point of the predetermined feature that was added to the environmental map in step S70. The position information of the new feature point of the predetermined feature is obtained by estimating the distance from the vehicle to the lane marking, etc., based on the position of the lane marking, etc., captured in the camera image IM, for example. Note that the distance from the vehicle to the lane marking, etc., may also be obtained based on the detection value of the radar 1b or the lidar 1c.

[0066] In step S260 of Fig. 4C, the controller 10 determines whether the position difference is within a predetermined value. If the position difference is within the predetermined tolerance, the controller 10 makes an affirmative determination in step S260 and proceeds to step S280. The process proceeds to step S280 when the environmental map has reached a level required for vehicle control in autonomous driving with respect to the position difference in the area traveled during the processing of Fig. 4B. On the other hand, if the position difference exceeds the predetermined value, the controller 10 makes a negative determination in step S260 and proceeds to step S270. The process proceeds to step S270 when the environmental map does not reach the level required for vehicle control in autonomous driving with respect to the position difference in the area traveled during the processing of FIG. 4B.

[0067] In step S270, the controller 10 deletes the information added to the environmental map in step S70, and adds the position information of the new feature point of the predetermined feature selected in step S230 back to the environmental map, and then proceeds to step S340.

[0068] In step S280, the controller 10 determines whether or not there is occlusion. If the controller 10 makes a negative decision in step S90 during the processing of Fig. 4A (in other words, if section information is not recorded in the storage unit 12 during the processing of Fig. 4A), the controller 10 makes a positive decision in step S280 and proceeds to step S290. On the other hand, if the controller 10 makes a positive decision in step S90 (in other words, if section information is recorded in the storage unit 12 during the processing of Fig. 4A), the controller 10 makes a negative decision in step S280 and proceeds to step S340.

[0069] In step S290, the controller 10 determines whether or not there are any incomplete lanes. If all of the driving lanes of the road on which the host vehicle is traveling are captured in the camera image IM acquired during the processing of Figures 4A and 4B, the controller 10 makes a positive judgment in step S290 and proceeds to step S300. On the other hand, if there is a driving lane that is not captured in the camera image IM acquired during the processing of Figures 4A and 4B, the controller 10 makes a negative judgment in step S290 and proceeds to step S340.

[0070] In step S300, the controller 10 determines whether or not there has been a degeneration of the autonomous driving level. When the host vehicle is traveling in the autonomous driving mode to determine the completion of the environmental map, if the driving control unit 16 has not degraded the autonomous driving level of the autonomous driving mode to a level lower than the current level, the controller 10 makes a positive determination in step S300 and proceeds to step S310. On the other hand, if the driving control unit 16 has degraded the autonomous driving level of the autonomous driving mode to a level lower than the current level, the controller 10 makes a negative determination in step S300 and proceeds to step S340.

[0071] In step S310, the controller 10 determines whether or not there is any driver intervention. If a signal indicating that the driver has intervened in a driving operation is not input from the internal sensor group 2 while the vehicle is traveling in the autonomous driving mode using an environmental map, the controller 10 makes a positive determination in step S310 and proceeds to step S320. On the other hand, if a signal indicating that the driver has intervened in a driving operation is input from the internal sensor group 2 while the vehicle is traveling in the autonomous driving mode using an environmental map, the controller 10 makes a negative determination in step S310 and proceeds to step S340.

[0072] In step S320, the controller 10 rewrites the section information stored in the storage unit 12 during a previous trip with the latest information, and then proceeds to step S330. In this embodiment, if step S260 and steps S280 to S310 all return positive answers, it is determined that the environmental map is complete. The section information stored in the storage unit 12 is rewritten in order to delete old section information that indicates the reason why the environmental map was previously determined to be incomplete.

[0073] In step S330, the controller 10 records the information of the environmental map generated in the process of FIG. 4B in the map storage unit 121 of the storage unit 12, and ends the process of FIG. 4C.

[0074] 4B and 4C, the controller 10 records or rewrites in the storage unit 12 section information indicating sections where occlusion was detected, sections where the presence of an incomplete lane was detected, sections where the autonomous driving level was degraded, and sections where the driver intervened in a driving operation, and then proceeds to step S330. As described above, the section information includes position information indicating the position of the host vehicle estimated by the host vehicle position recognition unit 13. In the embodiment, if a positive determination cannot be made in step S260 and all of steps S280 to S310 (if a negative determination is made in any one of them), it is determined that the environmental map is incomplete (not complete). The reason for recording the section information in the storage unit 12 and / or rewriting the section information stored in the storage unit 12 is to re-record old section information that indicates the reason why the environmental map was previously determined to be incomplete with the latest information.

[0075] According to the embodiment described above, the following effects can be obtained. (1) The map generating device 60 includes a camera 1a as a recognition unit (external environment recognition unit 14) that recognizes the surrounding environment of the vehicle while it is traveling, a generation unit 174 that generates a map (environmental map) based on a camera image IM as recognition information of the camera 1a, a vehicle position recognition unit 13 that serves as a position estimation unit that estimates the position of the vehicle on the map generated by the generation unit 174, a determination unit 175 that determines whether the map generated by the generation unit 174 is complete, and a storage unit 12 that stores map information indicating the map generated by the generation unit 174. The generation unit 174 generates a map of the traveling section based on the camera image IM recognized by the camera 1a. and records in the memory unit 12 map information corresponding to the section determined to be complete by the determination unit 175, and records in the memory unit 12 section information indicating the section determined to be complete or not by the determination unit 175 together with position information of the vehicle; and a second generation unit 174B that generates a map for the section determined to be complete or not based on a camera image IM of the section recognized by the camera 1a during the next travel, updates the map information recorded in the memory unit 12 by the first generation unit 174A by adding the map information of the section, and rewrites the section information recorded in the memory unit 12 by the first generation unit 174A. With this configuration, if it is determined that the environmental map necessary for safe vehicle control has not been generated (incomplete), the section information for that travel section is stored in the storage unit 12, and the next time the same section is traveled, a newly generated map can be added to complete the map. This makes it possible to reduce the travel distance and number of travels and complete the environmental map more quickly than if an environmental map for a wide range of travel sections were generated anew and completed. In other words, it becomes possible to appropriately generate the environmental map necessary for safe vehicle control.

[0076] (2) The map generating device 60 of (1) above further includes a controller 10 as an input unit that inputs information indicating that a degraded control of the autonomous driving level has been performed or that the driver of the vehicle has intervened in the driving operation from the driving control unit 16 as a control unit that performs autonomous driving control that automatically controls at least the acceleration and deceleration of the vehicle using map information recorded in the memory unit 12, and the judgment unit 175 judges whether the autonomous driving control has been completed or not when information is input from the driving control unit 16 to the controller 10 while the autonomous driving control is being executed. With this configuration, it becomes possible to appropriately determine whether or not the environmental map necessary for safe vehicle control has been completed.

[0077] (3) In the map generating device 60 of (1) or (2) above, the judgment unit 175 judges whether the map is complete or not when the camera image IM recognized by the camera 1a lacks information about the driving lane adjacent to the driving lane in which the vehicle is driving, or when the information about the features on the side of the road in which the vehicle is driving is lacking. With this configuration, it is possible to determine whether the newly generated environmental map is complete or not when there is a high probability that using it for autonomous driving control will lead to degenerate control (for example, when occlusion occurs, or when some lanes of the road being driven are outside the field of view of camera 1a), making it possible to appropriately determine whether the environmental map necessary for safe vehicle control is complete or not.

[0078] (4) In the map generating device 60 described above in (1) to (3), the determination unit 175 includes a lane identification unit that identifies the driving lane in which the vehicle traveled as a specific lane based on the position of the vehicle estimated by the vehicle position recognition unit 13 in the section where completion or non-completion has been determined. With this configuration, for example, by identifying the driving lane in which the vehicle traveled when the environmental map could not be completed due to occlusion, it is possible to utilize information about the specific lane the next time the vehicle travels. For example, it is possible to prompt the driver of the vehicle to travel in a different driving lane than the specific lane the next time the vehicle travels, or to travel on a different day or time than the day or time in which the specific lane was traveled. As a result, if occlusion can be avoided during the next travel, the environmental map can be completed more quickly than if occlusion occurs in the same section during the next travel.

[0079] (5) In the map generating device 60 described in (4) above, the determination unit 175 as a lane identification unit further determines whether the driving lane during the next driving is the specified lane or a driving lane adjacent to the specified lane, based on the camera image IM recognized by the camera 1a during the next driving in the section determined as complete or not by the determination unit 175, and the second generation unit (generation unit 174) generates a map of only the specified lane according to the identification result by the determination unit 175 as a lane identification unit. With this configuration, by generating and supplementing a map of only the specific lane the next time the vehicle is driven, it is possible to complete the environmental map more quickly than if maps of other driving lanes other than the specific lane were generated and supplemented.

[0080] (6) The map generating device 60 of (4) above is provided with a controller 10 as an output unit that outputs information indicating the specific lane identified by the determination unit 175 as a lane identification unit in the section where the determination unit 175 has determined whether the section is complete or not to an external device (for example, a route guidance device of the vehicle and / or a camera 1a as the external environment recognition unit 14). With this configuration, for example, it is possible to notify the driver of the lane in which to drive via the input / output device 3 or the like, or to output an instruction to change the shooting direction to the camera 1a from the controller 10, so that the center of the angle of view of the camera 1a is on the side of a specific lane the next time the vehicle travels. This makes it possible to create a map creation environment in which occlusion is less likely to occur, and to complete an environmental map with fewer travels (in other words, fewer times the processes of Figs. 4B and 4C are executed).

[0081] The above embodiment can be modified in various ways, and modifications will be described below. (Variation 1) Road dividing lines, traffic signs, and traffic lights have been given as examples of specified features for which the selection unit 172 will not select feature points based on the camera images IM, but the configuration may also be such that feature points are not selected for other features as well, provided that the object is difficult to track across multiple frames of camera images IM.

[0082] (Variation 2) In the embodiment, for ease of explanation, the processing shown in Fig. 4A has been described as processing performed before the environmental map is created. However, even after the environmental map is created (after it is determined that the environmental map is complete), the processing shown in Fig. 4A may be performed in parallel with the vehicle position recognition processing shown in Fig. 4B and Fig. 4C. By performing the processing even after the environmental map is completed, for example, if there is a change in the road environment, it is possible to appropriately add that information to the environmental map.

[0083] (Variation 3) In the embodiment, an example has been described in which an environmental map is generated as internal map information used by the vehicle itself, but in Modification 3, the environmental map generated by the vehicle itself may be provided to other vehicles via, for example, a cloud server. That is, in Modification 3, the environmental map is shared among multiple vehicles.

[0084] Fig. 5 is a diagram illustrating the configuration of a map generation system 400 according to Modification 3. In Fig. 5, the map generation system 400 includes a server 200 connected to a communication network 300, and a vehicle control system 100a and a vehicle control system 100b configured to be communicatively connected to the communication network 300. The vehicle control system 100a is a vehicle control system 100 mounted on a host vehicle 101, and the vehicle control system 100b is a vehicle control system 100 mounted on another vehicle 102.

[0085] The server 200 is operated, for example, by a business entity that provides an information sharing service for environmental maps. The configurations of the vehicle control systems 100a and 100b are similar to the vehicle control system 100 in the above-described embodiment.

[0086] The vehicle control systems 100a and 100b are each connected via a communication unit 7 to a communication network 300 such as a wireless communication network, the Internet network, or a telephone network. Although two vehicles, the subject vehicle 101 and the other vehicle 102, are shown in FIG. 5, the number of vehicles that can be connected to the communication network 300 is not limited to two and may be many.

[0087] The vehicle control systems 100a and 100b of the vehicle 101 and the other vehicle 102 respectively transmit information on the environmental map of the vehicle stored in the storage unit 12 to the server 200 via the communication unit 7 at a predetermined transmission time. The transmission time may be set by the driver as appropriate, for example, once a week or every predetermined distance traveled.

[0088] When environmental map information is transmitted from the vehicle control systems 100a and 100b mounted on the host vehicle 101 and the other vehicle 102, the server 200 stores the environmental map information in a database (not shown).

[0089] In addition, when the server 200 receives a request for environmental map information from the vehicle control systems 100a and 100b installed in the own vehicle 101 and the other vehicle 102, it reads environmental map information for the area in which the requesting vehicle is traveling from the above database and transmits it to the requesting vehicle.

[0090] In Modification 3, for example, when a command from the driver requesting environmental map information from the server 200 is input via the input / output device 3, the controller 10 of the vehicle 101 or the like requests environmental map information for the area in which the vehicle 101 or the like is traveling from the server 200. At this time, the controller 10 notifies the server 200 of information indicating the position information and traveling direction of the vehicle 101 or the like. This enables the server 200 to transmit the corresponding environmental map information to the requesting vehicle. The vehicle 101 or the like may transmit the recognition information acquired by the vehicle 101 or the like to the server 200 together with the information on the environmental map or instead of the information on the environmental map. The server 200 also records the recognition information acquired by the vehicle 101, etc. in the database, and when it receives a request for environmental map information and / or recognition information from the vehicle 101, etc., it reads the environmental map information and / or recognition information of the area in which the requesting vehicle is traveling from the database and transmits it to the requesting vehicle. When the requesting vehicle acquires from the server 200 recognition information for a section for which the map is incomplete, the vehicle can generate an environmental map based on the acquired recognition information.

[0091] The map generation system 400 described in the above-described variant example 3 includes the above-mentioned map generation device 60 and a server 200 as an external server configured to be able to communicate with the host vehicle 101, etc. The server 200 stores recognition information acquired by the host vehicle 101 and other vehicles 102, and information on environmental maps generated by the host vehicle 101 and other vehicles 102, and provides information to the host vehicle 101 and / or other vehicles 102 using the stored recognition information and / or information on the environmental maps. With this configuration, the operational range of the environmental map generated by the vehicle 101 etc. is expanded compared to when it is used only by the vehicle, further improving convenience. The environmental map may be configured to be switchable between being shared with other vehicles and being used only by the vehicle itself.

[0092] The above description is merely an example, and the present invention is not limited to the above-described embodiment and modifications as long as the features of the present invention are not impaired. One or more of the above-described embodiment and modifications can be arbitrarily combined, and modifications can also be combined with each other. [Explanation of symbols]

[0093] 1a camera, 1b radar, 1c lidar, 10 controller, 11 calculation unit, 12 memory unit, 13 vehicle position recognition unit, 14 external environment recognition unit, 16 driving control unit, 17 map generation unit, 60 map generation device, 101 vehicle, 121 map memory unit, 122 trajectory memory unit, 171 extraction unit, 172 selection unit, 173 calculation unit, 174 generation unit, 175 determination unit, BL1 to BL3 buildings, IM camera image, OL roadway outer line, SG traffic light, SL lane boundary line, TS1, TS2 traffic sign, 102, V1, V2 other vehicles

Claims

1. a recognition unit that recognizes the surrounding environment of the vehicle; a map generation unit that generates a map based on the recognition information of the recognition unit; a position estimation unit that estimates a position of the vehicle on the map generated by the map generation unit; a determination unit that determines whether the map generated by the map generation unit is complete; a storage unit for storing map information indicating the map generated by the map generation unit; an input unit that inputs information indicating that degenerate control of the autonomous driving level has been performed or that a driver of the host vehicle has intervened in a driving operation from a control unit that performs autonomous driving control that automatically controls at least acceleration and deceleration of the host vehicle using the map information recorded in the storage unit, The map generation unit a first generation unit that generates a map of a travel section based on the recognition information recognized by the recognition unit, records the map information corresponding to the section determined to be complete by the determination unit in the storage unit, and records section information indicating the section determined to be complete or not by the determination unit in the storage unit together with position information of the vehicle; a second generation unit that generates a map for the section determined to be incomplete or not based on the recognition information of the section recognized by the recognition unit during the next travel, updates the map information recorded in the storage unit by the first generation unit by adding the map information of the section, and rewrites the section information recorded in the storage unit by the first generation unit, The determination unit determines whether the automatic driving control is complete when the information is input from the control unit to the input unit during the execution of the automatic driving control. A map generating device characterized by:

2. A recognition unit that recognizes the surrounding environment of a traveling vehicle; a map generation unit that generates a map based on the recognition information of the recognition unit; a position estimation unit that estimates a position of the vehicle on the map generated by the map generation unit; a determination unit that determines whether the map generated by the map generation unit is complete; a storage unit that stores map information indicating the map generated by the map generation unit, The map generation unit a first generation unit that generates a map of a travel section based on the recognition information recognized by the recognition unit, records the map information corresponding to the section determined to be complete by the determination unit in the storage unit, and records section information indicating the section determined to be complete or not by the determination unit in the storage unit together with position information of the vehicle; a second generation unit that generates a map for the section determined to be incomplete or not based on the recognition information of the section recognized by the recognition unit during the next travel, updates the map information recorded in the storage unit by the first generation unit by adding the map information of the section, and rewrites the section information recorded in the storage unit by the first generation unit, the determination unit determines whether the recognition information recognized by the recognition unit is complete or not when the recognition information recognized by the recognition unit lacks information about a driving lane adjacent to the driving lane on which the host vehicle is traveling, or when the recognition information lacks information about features on the side of the road on which the host vehicle is traveling. A map generating device characterized by:

3. 3. The map generating device according to claim 1, the determination unit includes a lane identification unit that identifies, as a specific lane, a driving lane in which the host vehicle has traveled, based on the position of the host vehicle estimated by the position estimation unit in the section for which completion or non-completion has been determined. A map generating device characterized by:

4. 4. The map generating device according to claim 3, The lane identification unit further identifies whether the driving lane at the time of the next driving corresponds to the specified lane or a driving lane adjacent to the specified lane, based on the recognition information recognized by the recognition unit at the time of the next driving in the section determined to be complete by the determination unit; the second generation unit generates a map of only the specified lane in accordance with the identification result by the lane identification unit. A map generating device characterized by:

5. 4. The map generating device according to claim 3, The specific lane identified by the lane identification unit in the section where the completion or non-completion is determined by the determination unit an output unit that outputs information indicating the mode to an external device; A map generating device characterized by:

6. A map generating device according to claim 1 or 2; an external server configured to be able to communicate with the vehicle; the external server stores the recognition information acquired by the host vehicle and the other vehicle, and map information generated by the host vehicle and the other vehicle; providing information to the host vehicle and / or the other vehicle using the stored recognition information and / or the stored map information; A map generation system characterized by:

Images