JP2022129175A - Vehicle evaluation method and vehicle evaluation device - Google Patents

Abstract

To save labor in realizing a test environment in which an evaluation is performed when a vehicle is actually driven and evaluated by a drive support function that detects a surrounding environment by a sensor and supports the vehicle driving.SOLUTION: A vehicle evaluation method constructs a virtual environment in which a virtual position on a road map corresponding to a position of an own vehicle in a real environment is determined by associating coordinate information on a predetermined road map with coordinates in the real environment (S2). A virtual object is arranged in the virtual environment (S3). Detection information is acquired by detecting a relative position of an object existing around the own vehicle to the own vehicle by the sensor (S4). A self-position of the own vehicle is calculated (S5). Based on the self-position, the detection information acquired by the sensor and information of the virtual environment are integrated into integrated information (S6). Travel of the own vehicle is controlled based on the integrated information (S7-S10).SELECTED DRAWING: Figure 5

Description

The present invention relates to a vehicle evaluation method and a vehicle evaluation device.

Various driving support technologies and automatic driving technologies have been proposed for blind spots and shielding around vehicles. For example, in Patent Document 1, it is determined from sensor information whether or not the vehicle is traveling at an intersection with poor visibility. , and then repeats forward and stop to pass through the intersection.

JP 2019-067295 A

When evaluating driving support functions that detect the surrounding environment with sensors and support driving of the vehicle by actually driving the vehicle, a large amount of labor and costs are incurred to create a test environment according to the evaluation items. was
The present invention saves the work of realizing a test environment for performing evaluation in a real environment when evaluating a driving support function that detects the surrounding environment with a sensor and supports the driving of the vehicle by actually running the vehicle. The purpose is to

According to one aspect of the present invention, there is provided a vehicle evaluation method for an autonomous vehicle that automatically drives an own vehicle based on the ambient environment surrounding the own vehicle. In this vehicle evaluation method, by associating coordinate information on a predetermined road map with coordinates in the real environment, a virtual environment is constructed in which a virtual position on the road map corresponding to the position of the own vehicle in the real environment is determined. , a virtual object is placed in a virtual environment, the sensor detects the relative positions of objects existing around the own vehicle with respect to the own vehicle and acquires detection information, calculates the own position of the own vehicle, , the detection information acquired by the sensor and the information of the virtual environment are integrated into integrated information, and the running of the own vehicle is controlled based on the integrated information.

According to the present invention, when a driving support function that detects the surrounding environment by a sensor and supports the driving of the vehicle is evaluated by actually driving the vehicle, the test environment for performing the evaluation is realized in the real environment. can save labor.

1 is a schematic configuration diagram of an example of a travel control device according to an embodiment; FIG. It is a block diagram of an example of functional composition of a cruise control device of an embodiment. 1 is an explanatory diagram (part 1) of an example of a vehicle evaluation method according to an embodiment; FIG. FIG. 2 is an explanatory diagram (part 2) of an example of a vehicle evaluation method according to an embodiment; FIG. 3 is an explanatory diagram (part 3) of an example of a vehicle evaluation method according to an embodiment; FIG. 4 is an explanatory diagram (part 4) of an example of the vehicle evaluation method of the embodiment; FIG. 10 is an explanatory diagram (part 1) of an example of correction of the shape of a virtual object according to the shape of a road surface in a real environment; FIG. 11 is an explanatory diagram (part 2) of an example of correction of the shape of a virtual object according to the road surface shape in the real environment; FIG. 13 is an explanatory diagram (part 3) of an example of correction of the shape of the virtual object according to the road surface shape in the real environment; It is a flow chart of an example of a vehicle evaluation method of an embodiment.

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, embodiments of the present invention will be described with reference to the drawings. Note that each drawing is schematic and may differ from the actual one. Further, the embodiments of the present invention shown below are examples of apparatuses and methods for embodying the technical idea of the present invention. are not specific to the following: Various modifications can be made to the technical idea of the present invention within the technical scope defined by the claims.

(Constitution)
FIG. 1 is a schematic configuration diagram of an example of a travel control device according to an embodiment. The own vehicle 1 is an automatically driven vehicle provided with a cruise control device 10 that performs driving support control of the own vehicle 1 based on the surrounding environment of the own vehicle 1 . The driving support control by the driving control device 10 includes automatic driving control for automatically driving the own vehicle 1 without involving the driver, automatic steering, automatic braking, constant speed driving control, lane keeping control, merging support control, and the like. , driving control, braking control, or steering control.

In the vehicle evaluation method of the embodiment, the own vehicle 1 is caused to travel under the driving support control by the driving control device 10, and the function/performance of the driving support control is evaluated and verified (hereinafter, sometimes simply referred to as "evaluation verification"). to implement.
At that time, a virtual environment for evaluating driving support control by the cruise control device 10 is constructed, and the host vehicle 1 is caused to travel within the virtual environment as the host vehicle 1 actually travels in the real world.
Driving support control is performed based on information obtained by detecting the actual surrounding environment with a sensor mounted on the own vehicle 1 and information on the surrounding environment of the own vehicle 1 in the virtual environment, and actual vehicle behavior. Evaluate and verify the function/performance of driving support control by generating
Hereinafter, the place in the real world where the vehicle is actually run and the evaluation verification is performed may be referred to as "real environment". Also, a virtual environment in which evaluation verification is performed may be referred to as an “evaluation environment”. The evaluation environment is an example of the "virtual environment" described in the claims.

The traveling control device 10 includes a sensor 11, a positioning device 12, a map database (map DB) 13, an object database (object DB) 14, a controller 15, an actuator 16, and a user interface (user I/F) 17. and
The sensors 11 include a plurality of different types of object detection sensors that detect objects around the vehicle 1 and vehicle sensors that detect various information (vehicle signals) obtained from the vehicle 1 .
The object detection sensor may be, for example, a laser radar, millimeter wave radar, LIDAR (Light Detection and Ranging, Laser Imaging Detection and Ranging) mounted on the vehicle 1, or a camera.

The vehicle sensors include, for example, a vehicle speed sensor that detects the running speed (vehicle speed) of the vehicle 1, a wheel speed sensor that detects the rotational speed of each tire of the vehicle 1, and acceleration (deceleration) of the vehicle 1 in three axial directions. A 3-axis acceleration sensor (G sensor) that detects steering angle (including steering angle), a steering angle sensor that detects steering angle (including steering angle), a gyro sensor that detects angular velocity generated in own vehicle 1, and a yaw rate sensor that detects yaw rate. , an accelerator sensor for detecting the accelerator opening of the own vehicle, and a brake sensor for detecting the amount of brake operation by the driver.

The positioning device 12 has a global positioning system (GNSS) receiver, receives radio waves from a plurality of navigation satellites, and measures the current position of the vehicle 1 . A GNSS receiver may be, for example, a global positioning system (GPS) receiver or the like. The positioning device 12 may be, for example, an inertial navigation device.
The map database 13 stores road map information 13a, which is predetermined road map information.
The road map information 13a is road map information set in a virtual evaluation environment. Here, the evaluation verification has items to be evaluated for the driving support control of the cruise control device 10 (hereinafter referred to as "evaluation items"). For example, the road map information 13a may be information on roads having road structures and attributes on which the functions or performances of vehicles to be evaluated for given evaluation items are exhibited.

The road map information 13a may include, for example, coordinate information of roads, lane boundaries, lane markings, and road surface shape information. The road map information 13a may also include coordinate information of features on or near roads (eg, guardrails, buildings, utility poles, curbs, pedestrian crossings, stop lines, traffic lights, railroad crossings, etc.).
The road map information 13a is sensor information obtained by running a vehicle equipped with a sensor such as the object detection sensor described above on an actual road and detecting roads, lane boundaries, road surface shapes, and features with the sensors. good. The sensor information may be, for example, point cloud data output from a distance measuring device or coordinate information of an object recognized from an image captured by a camera. Further, the road map information 13a may be map information virtually created by simulating such sensor information.
For example, the road map information 13a may be high-definition (HD) map data suitable as a map for automatic driving.

The map database 13 also includes road surface information 13b. The road surface information 13b is information about the shape and gradient of the road surface in the real environment where the own vehicle 1 is actually run and the evaluation verification is performed. The road surface information 13b may include, for example, road surface height information (for example, altitude information) at each point.
The object database 14 stores information on virtual objects to be arranged in the evaluation environment and their coordinate information according to evaluation items of evaluation verification.
The virtual object information may be sensor information obtained by detecting a realistic object with a sensor such as the object detection sensor described above, or may be information virtually created by simulating such sensor information. Alternatively, it may be three-dimensional object information in another format (for example, polyhedral information using polygons).

The controller 15 is an electronic control unit (ECU) that performs a process of virtually simulating the running of the vehicle 1 in the evaluation environment while performing driving support control of the vehicle 1 .
Controller 15 includes a processor 20 and peripheral components such as storage device 21 . The processor 20 may be, for example, a CPU (Central Processing Unit) or an MPU (Micro-Processing Unit).
The storage device 21 may include a semiconductor storage device, a magnetic storage device, an optical storage device, or the like. The storage device 21 may include memories such as a register, a cache memory, a ROM (Read Only Memory) used as a main memory, and a RAM (Random Access Memory).

The functions of the controller 15 to be described below are implemented by the processor 20 executing a computer program stored in the storage device 21, for example.
Note that the controller 15 may be formed of dedicated hardware for executing each information processing described below.
For example, controller 15 may comprise functional logic circuitry implemented in a general-purpose semiconductor integrated circuit. For example, controller 15 may include a programmable logic device (PLD), such as a field-programmable gate array (FPGA), or the like.

The actuator 16 operates the steering wheel, the accelerator opening, and the braking device of the own vehicle according to the control signal from the controller 15 to generate the vehicle behavior of the own vehicle. Actuator 16 includes a steering actuator, an accelerator opening actuator, and a brake control actuator. The steering actuator controls the steering direction and amount of steering of the host vehicle.
The accelerator opening actuator controls the accelerator opening of the host vehicle. The brake control actuator controls the braking operation of the brake system of the host vehicle 1 .

The user interface 17 is a human machine interface (HMI) for exchanging information between the cruise control device 10 and the passenger. The user interface 17 may be an information terminal (for example, a smart phone or a tablet device) separate from the driving support device 10 . In addition to the driver, the occupant includes an occupant and a fellow passenger who have operation instruction authority related to the autonomous travel control of the own vehicle 1 .
User interface 17 may include, for example, a speaker and microphone for transmitting and receiving audio information. The user interface 17 may also include a display device (eg, head-up display, etc.) that provides display information. The user interface 17 may include a keyboard, buttons, dials, sliders, mice, touch panels, levers, joysticks, touch pads, etc. that are physically operated by the occupant.

Next, an example of the functional configuration of the travel control device 10 implemented by the controller 15 will be described with reference to FIG. 2 .
The controller 15 includes a sensor information acquisition unit 30, a self-position calculation unit 31, an evaluation environment construction unit 32, an environment information integration unit 33, a surrounding environment recognition unit 34, an action determination unit 35, and a trajectory generation unit 36. , a vehicle control unit 37 and an information presentation unit 38 .
The sensor information acquisition unit 30 acquires sensor information, which is information obtained by detecting the relative position of an actual object existing around the own vehicle 1 with respect to the own vehicle 1 by the object detection sensor of the sensor 11 .

For example, the sensor information acquisition unit 30 may acquire point cloud data output from a distance measuring device as sensor information. For example, these point cloud data may be clustered and recognized as an object, and information on the relative position, shape, and size of the object with respect to the own vehicle 1 may be acquired as sensor information. Further, for example, an object existing around the own vehicle 1 may be recognized from an image captured by a camera, and information on the relative position, shape, and size of the object with respect to the own vehicle 1 may be acquired as sensor information.
The self-position calculator 31 calculates the self-position, which is the position of the vehicle 1 on the map. For example, the self-position calculator 31 may calculate the self-position based on vehicle information detected by the vehicle sensor of the sensor 11 . For example, the self-position calculator 31 may calculate the self-position by odometry based on vehicle information. Also, the self-position calculator 31 may acquire the self-position from the positioning device 12 .

The evaluation environment constructing unit 32 constructs an evaluation environment, which is a virtual environment in which evaluation verification is performed. At that time, the evaluation environment constructing unit 32 associates the coordinates on the map in the real environment with the coordinate information of the road map information 13a.
By associating the coordinates in the real environment with the coordinate information of the road map information 13a, it is possible to set the virtual position of the vehicle 1 in the road map information 13a corresponding to the self position calculated by the self-position calculator 31. That is, the relative positional relationship between the vehicle 1 and the roads, lane boundaries, lane markings, features, etc. included in the road map information 13a can be set. As a result, it is possible to create a simulated situation in which the own vehicle 1 travels on the road in the evaluation environment in which the roads, lane boundaries, lane markings, features, etc. included in the road map information 13a are arranged. .

For example, by translating the coordinates of the road map information 13a to the coordinates of the real environment (that is, converting the coordinates of the road map information 13a into the coordinates of the location in the real world where the vehicle 1 actually travels), The coordinates in the environment may be associated with the coordinate information of the road map information 13a.
At this time, the real environment and the coordinates of the road map information 13a are corresponded so that the coordinates of the road on the road map information 13a that can verify the evaluation item of the evaluation verification are included in the actual evaluation verification implementation place (real environment). You can put it on.
Note that the coordinates on the map in the real environment may be translated to the coordinates of the road map information 13a. That is, either the coordinate values of the real environment or the coordinate values of the road map information 13a may be used as the coordinate values of the evaluation environment. Alternatively, as the coordinate values of the evaluation environment, dedicated coordinate values that are neither the coordinate values of the real environment nor the coordinate values of the road map information 13a are set, and the coordinate values of the real environment and the coordinate values of the road map information 13a are set as dedicated coordinate values. You can move parallel to .

FIG. 3A shows an example of the environment around the own vehicle 1 in the real environment. The real environment in which the evaluation verification by the vehicle evaluation method according to the embodiment is performed includes features forming lanes (for example, lane boundary lines) so as not to conflict with virtual roads and virtual objects provided in the virtual evaluation environment. , lane markings, curbs, etc.) and nearby features.
Further, in order to evaluate the recognition function of the surrounding environment by the sensor 11, real objects may be placed in the real environment according to the evaluation items. In the example of FIG. 3A , real other vehicles 2 are arranged around the own vehicle 1 . A real object placed in the real environment is sometimes referred to as a “substantial object”.

FIG. 3B shows an example of an evaluation environment constructed by associating the coordinates on the map in the real environment with the coordinate information of the road map information 13a. In the constructed evaluation environment, the road 3 included in the road map information 13a exists around the own vehicle 1 (the white lines 3a to 3c are lane boundary lines of the road 3).
Note that when the road surface shape in the real environment and the road surface shape of the road 3 in the road map information 13a are different (that is, when the road surface heights of the two differ from each other), the height information of the road 3 in the road map information 13a (For example, altitude information) may be corrected in accordance with the road surface shape in the actual environment.

Furthermore, the evaluation environment constructing unit 32 arranges the virtual object corresponding to the evaluation item in the evaluation environment based on the information of the virtual object and its coordinate information stored in the object database 14 .
FIG. 3C shows an example of an evaluation environment in which virtual objects are arranged. In the evaluation environment of FIG. 3C, a wall 4 and a virtual other vehicle 5 are arranged as examples of virtual objects. Wall 4 is an example of a stationary virtual object. The other vehicle 5 may be a stationary virtual object such as a parked vehicle, a moving virtual object such as a running vehicle, or a movable stationary virtual object such as a temporarily stopped vehicle. It can be an object.

When arranging the virtual object in the evaluation environment, the evaluation environment construction unit 32 may match the arrangement position of the virtual object in the height direction with the shape of the road surface in the real environment.
In this case, the shape of the road surface assumed as the placement location of the virtual object stored in the object database 14 may differ from the shape of the road surface in the real environment where the virtual object is placed. An example is shown in FIG. 4A.
The wall 4 shown in FIG. 4A is a virtual object arranged on an inclined surface like the road surface 6e. The slope of the road surface 6r in the real environment on which 6e is virtually placed differs from the road surface 6e (for example, the road surface 6r may be horizontal).

In this case, if the height of any position of the road surface 6e on which the wall 4 is arranged is adjusted to the height of any position of the road surface 6r in the real environment, the wall 4 will float as shown in FIG. 4A. Alternatively, as shown in FIG. 4B, a portion of the wall 4 is sunk under the road surface 6e.
Therefore, as shown in FIG. 4C, the evaluation environment construction unit 32 causes the height direction position of the bottom surface 4b of the wall (virtual object) 4 to match the height direction position of the road surface 6r in the real environment over the bottom surface 4b. , the position of the top surface 4t may be corrected so that the height of the top surface 4t with respect to the bottom surface 4b of the wall (virtual object) 4 is maintained.

When arranging a moving virtual object, the evaluation environment construction unit 32 may move the virtual object along the shape of the road surface in the real environment.
At that time, the virtual object may be moved according to a predetermined scenario so that the virtual object moves as determined in advance. Also, the virtual object is moved based on a predetermined program or algorithm that determines at least one of the moving direction, moving speed, and moving amount of the virtual object based on predetermined conditions so that the virtual object moves according to the situation. may

In this way, the evaluation environment includes the roads, lane boundaries, lane markings, and features placed in the evaluation environment from the road map information 13a, in addition to the real entities placed in the real environment, and the object database. 14 using virtual objects placed in the evaluation environment.
Roads, lane boundaries, lane markings, and features placed in the evaluation environment from the road map information 13a, virtual objects placed in the evaluation environment based on the object database 14, and entities placed in the real environment are described below. It is sometimes described as a "virtual construction" to distinguish it from an object.

Please refer to FIG. The evaluation environment construction unit 32 outputs information on the virtual building placed in the evaluation environment (hereinafter sometimes referred to as “evaluation environment information”) to the environment information integration unit 33 .
For example, the evaluation environment information may include coordinate information representing the position and shape of the virtual structure placed in the evaluation environment.
The environment information integration unit 33 combines the sensor information acquired by the sensor information acquisition unit 30 (that is, the detection result of the real object) with the virtual evaluation environment information generated by the evaluation environment construction unit 32 into the self-position calculation unit 31. based on the calculated self-position. In other words, the virtual evaluation environment information is treated as information equivalent to the sensor information obtained by detecting the surrounding environment of the vehicle 1 with a sensor, and added to the sensor information acquired by the sensor information acquisition unit 30 .
Hereinafter, information obtained by integrating sensor information and evaluation environment information may be referred to as "integrated information".

For example, the environment information integration unit 33 calculates the relative position of the virtual structure included in the evaluation environment information with respect to the own vehicle 1 based on the self-position calculated by the self-position calculation unit 31 . Based on the calculated relative position, the environment information integration unit 33 extracts the virtual structure existing in the detectable area by the sensor 11, and the sensor information acquisition unit 30 acquires the evaluation environment information of the extracted virtual structure. The evaluation environment information may be integrated into the integrated information by adding it to the sensor information.
At this time, the environment information integration unit 33 determines whether the object in the sensor information acquired by the sensor information acquisition unit 30 (that is, the physical object detected by the sensor 11) is shielded by the virtual structure when viewed from the host vehicle 1. Then, the sensor information of the physical object that cannot be acquired by the sensor 11 when it is shielded by the virtual building may be deleted from the integrated information.

For example, the environmental information integration unit 33 determines whether or not the physical object detected by the sensor 11 is shielded by the virtual construction when viewed from the own vehicle 1, based on the positional relationship between the physical object and the virtual construction. good. For example, the environment information integration unit 33 detects the sensor 11 based on the actual relative distance between the own vehicle 1 and the physical object and the virtual relative distance between the own vehicle 1 and the virtual structure in the evaluation environment. It may be determined whether or not the detected physical object is blocked by the virtual structure when viewed from the own vehicle 1 .

For example, the environment information integration unit 33 calculates an area (that is, a blind spot area) that is blocked by the virtual structure when viewed from the host vehicle 1, and the real object that exists in the area that is blocked by the virtual structure is blocked by the virtual structure. can be determined.
Further, for example, the environment information integration unit 33 determines whether or not a physical object existing in the same direction as the virtual construction is farther from the own vehicle 1 than the virtual construction. It may be determined that the vehicle 1 is shielded by the virtual construction.
Similarly, it is determined whether or not the virtual structure is shielded from the host vehicle 1 by the physical object detected by the sensor 11 or another virtual structure, and the shielded evaluation environment information is deleted from the integrated information. You may
See FIG. 3D. The part 4a of the wall 4, which is a virtual object, shields the other vehicle 2, which is a real object, and the other part 4b of the wall 4. Integrated information from which the evaluation environment information of the part 4b of 4 is deleted is generated.

Note that a specific identifier may be attached to a physical object that exists in the real environment where evaluation verification is performed, and the sensor information of the physical object to which the identifier is attached may be deleted from the integrated information. As a result, sensor information unnecessary for evaluation and verification can be removed from the sensor information of the physical objects that actually exist in the real environment. For example, identifiers may be attached to various measuring instruments installed in the real environment for use in evaluation verification.
The identifier may be, for example, a visual identifier such as a mark or sign, and the identifier may be detected by the object detection sensor (eg camera) of the sensor 11 to determine whether the identifier is attached to the physical object. The identifier may also be an emitter that emits a specific signal (eg a beacon).

Further, the evaluation environment construction unit 32 constructs an evaluation environment (hereinafter sometimes referred to as “evaluation environment construction processing”), and the environment information integration unit 33 integrates sensor information and evaluation environment information into integrated information. Processing (hereinafter referred to as “environmental information integration processing”) requires a certain amount of computing time. As a result, the evaluation environment construction process and the environment information integration process may not be completed in time for the driving support control.
Therefore, the environment information integration unit 33 may estimate and output the integrated information at the time advanced by the calculation time required for the evaluation environment construction process and the environment information integration process.

For example, the environment information integration unit 33 may estimate the future self-position and the future position of the moving object at a time advanced by the above calculation time. For example, the future self-position may be estimated based on the current moving direction and moving speed of the own vehicle 1 . Further, the future position of the moving physical object may be estimated based on the moving direction and moving speed of the physical object. The future position of the moving virtual object may be calculated based on the scenario or program that defines the position of the virtual object.
Based on these estimated future positions, the environmental information integration unit 33 may estimate integrated information at a time advanced by the computation time.

Please refer to FIG. The surrounding environment recognition unit 34 recognizes the surrounding environment of the own vehicle 1 based on the integrated information output from the environment information integration unit 33 . For example, the surrounding environment recognizing unit 34 verifies (associates) the identity of objects included in each piece of integrated information given at different times, and based on the association, the behavior such as velocity and posture of the object is determined. to predict. The surrounding environment recognition unit 34 determines attributes of objects included in the integrated information based on the speed, behavior, size, and shape of the objects. For example, as an attribute of an object, it is determined whether it is a stationary object or a moving object. As attributes of objects, the types of objects such as vehicles, pedestrians, bicycles, and structures (for example, features on or near roads) are determined.

The behavior determination unit 35 determines a rough driving behavior of the own vehicle 1 to be executed by the cruise control device 10 based on the recognition result of the surrounding environment recognition unit 34 . The driving behavior determined by the behavior determining unit 35 includes, for example, stop, pause, running speed, deceleration, acceleration, course change, right turn, left turn, go straight, lane change in a merging section or multiple lanes, lane maintenance, Actions such as overtaking and dealing with obstacles are included.
For example, the action determining unit 35 determines the surroundings of the own vehicle 1 based on the self-position of the own vehicle 1, the positions and orientations of objects around the own vehicle 1 recognized by the surrounding environment recognition unit 34, and the high-precision map. It generates a route space map that expresses the route and the presence or absence of objects, and a risk map that quantifies the degree of risk of the driving area. The action determination unit 35 generates a driving action plan for the own vehicle 1 based on the route space map and the risk map.

The trajectory generation unit 36 generates a travel trajectory and a speed profile candidate for the vehicle 1 to travel based on the driving action plan determined by the behavior determination unit 35, the motion characteristics of the vehicle 1, and the route space map.
The trajectory generator 36 evaluates the future risk of each candidate based on the risk map, selects the optimum travel trajectory and speed profile, and sets them as the target travel trajectory and target speed profile for the vehicle 1 to travel.
The vehicle control unit 37 drives the actuator 16 so that the vehicle 1 travels along the target travel trajectory at a speed according to the target speed profile generated by the trajectory generation unit 36 .

The information presentation unit 38 visualizes the information of the surrounding environment of the own vehicle 1 recognized by the surrounding environment recognition unit 34 , outputs it from the user interface 17 , and presents it to the occupant of the own vehicle 1 . Alternatively, the information may be provided to an observer outside the own vehicle 1 via a user interface 17 provided as a device separate from the driving support device 10 .
For example, the information presentation unit 38 visualizes only the virtual structure among the information recognized by the surrounding environment recognition unit 34, and displays it on the head-up display in front of the occupant, or projects it on the front windshield for display. It may be displayed on a display device. Also, an image in which the physical object recognized by the surrounding environment recognition unit 34 and the virtual structure are superimposed may be displayed on the display device.
As described above, by deleting the sensor information of the real object that is blocked by the virtual structure and cannot be acquired by the sensor 11 from the integrated information, an image in which the blocked portion is not displayed can be provided.

(motion)
Next, with reference to FIG. 5, an example of the vehicle evaluation method of the embodiment will be referred to.
In step S<b>1 , the evaluation environment construction unit 32 acquires the road map information 13 a from the map database 13 and the road surface information 13 b including shape information such as the slope of the road surface in the real environment. Further, from the object database 14, information on the virtual object to be placed in the evaluation environment and its coordinate information are acquired as information on the evaluation environment corresponding to the verification item of the evaluation verification.
In step S2, the evaluation environment building section 32 builds an evaluation environment by associating the coordinates on the map in the real environment with the coordinate information of the road map information 13a.
In step S3, the evaluation environment construction unit 32 arranges virtual objects in the constructed evaluation environment.

In step S<b>4 , the sensor information acquisition unit 30 acquires sensor information that the object detection sensor of the sensor 11 detects an actual object existing around the own vehicle 1 .
In step S5, the self-position calculator 31 calculates the self-position, which is the position of the vehicle 1 on the map.
In step S6, the environment information integration unit 33 integrates the sensor information acquired by the sensor information acquisition unit 30 and the evaluation environment information constructed by the evaluation environment construction unit 32 into integrated information.
In step S7, the surrounding environment recognition unit 34 recognizes the surrounding environment of the own vehicle 1 based on the integrated information.

In step S<b>8 , the action determination unit 35 determines a driving action plan for the own vehicle 1 to be executed by the cruise control device 10 based on the recognition result of the surrounding environment recognition unit 34 .
In step S<b>9 , the trajectory generation unit 36 generates a target travel trajectory and a target speed profile for the vehicle 1 to travel based on the driving action plan determined by the action determination unit 35 .
In step S<b>10 , the vehicle control unit 37 drives the actuator 16 so that the vehicle 1 travels along the target travel trajectory at a speed according to the target speed profile generated by the trajectory generation unit 36 . Processing then ends.

(Effect of Embodiment)
(1) The travel control device 10 can implement a vehicle evaluation method for an automatically driven vehicle that automatically drives the own vehicle 1 based on the surrounding environment of the own vehicle 1 . The evaluation environment constructing unit 32 of the travel control device 10 associates the coordinate information on the predetermined road map with the coordinates of the real environment, thereby obtaining a virtual position on the road map corresponding to the position of the own vehicle 1 in the real environment. is established, and virtual objects are arranged in the evaluation environment. The sensor information acquisition unit 30 acquires detection information obtained by detecting the relative position of an object existing around the own vehicle 1 with respect to the own vehicle 1 by the sensor 11 . The self-position calculator 31 calculates the self-position of the own vehicle 1 . The environment information integration unit 33 integrates the detection information acquired by the sensor 11 and the evaluation environment information into integrated information based on the self-location. The surrounding environment recognition unit 34, the action determination unit 35, the trajectory generation unit 36, and the vehicle control unit 37 control traveling of the own vehicle 1 based on the integrated information.
This makes it possible to virtually create a test environment for evaluating automated driving vehicles. As a result, it is possible to save labor in the work of realizing the test environment.

(2) The environmental information integration unit 33 integrates the detection information of the detected object that is shielded by the virtual object as seen from the vehicle 1 based on the positional relationship between the detected object, which is the object detected by the sensor, and the virtual object. May be excluded from information.
As a result, it is possible to realize an environment in which the physical object detected by the sensor 11 is shielded by the virtual object when viewed from the own vehicle 1 .
(3) The environment information integration unit 33 calculates the following from the own vehicle 1 based on the relative distance between the own vehicle 1 and the detected object and the relative distance between the own vehicle 1 and the virtual object in the evaluation environment. It may be determined whether or not the object to be detected is blocked by the virtual object.
Thereby, it is possible to determine whether or not the physical object detected by the sensor 11 is shielded by the virtual object when viewed from the own vehicle 1 .

(4) When constructing the evaluation environment, the evaluation environment construction unit 32 may correct the road surface shape of the road included in the road map to match the road surface shape of the actual environment.
As a result, an evaluation environment can be constructed according to the shape of the road surface in the actual environment.
(5) When arranging the virtual object, the evaluation environment constructing unit 32 may correct the upper surface 4t of the virtual object to match the shape of the road surface in the real environment at the coordinates at which the virtual object is arranged. As a result, the positional information of the top surface 4t in the height direction can be corrected so as to maintain the height of the virtual object according to the shape of the road surface in the real environment.

(6) The evaluation environment construction unit 32 may arrange, as the virtual object, a moving object that moves according to the shape of the road surface in the real environment at the coordinates at which the virtual object is located.
This makes it possible to simulate a virtual object that moves along the shape of the road surface in the real environment.
(7) The evaluation environment construction unit 32 may move the virtual object according to a predetermined scenario or a predetermined program.
Thereby, a virtual object can be moved according to arbitrary evaluation items.
(8) The environmental information integration unit 33 may estimate future integrated information at a time advanced by the calculation time for constructing the evaluation environment and integration into the integrated information. The surrounding environment recognition unit 34, the action determination unit 35, the trajectory generation unit 36, and the vehicle control unit 37 may control the traveling of the own vehicle 1 based on future integrated information. As a result, it is possible to prevent the process of constructing the evaluation environment and the process of integrating into the integrated information from falling behind the running control of the own vehicle 1 .

Reference Signs List 1 self-vehicle 10 traveling control device 11 sensor 12 positioning device 13 map database (map DB) 13a road map information 13b road surface information 14 object database (object DB) 15 ... controller 16 ... actuator 17 ... user interface (user I/F) 20 ... processor 21 ... storage device 30 ... sensor information acquisition unit 31 ... self-position calculation unit 32 ... evaluation environment construction unit 33 ... Environmental information integration unit 34 Surrounding environment recognition unit 35 Action determination unit 36 Trajectory generation unit 37 Vehicle control unit 38 Information presentation unit

Claims (9)

A vehicle evaluation method for an automatically driven vehicle that automatically drives the own vehicle based on the surrounding environment of the own vehicle,
constructing a virtual environment in which a virtual position on the road map corresponding to the position of the own vehicle in the real environment is determined by associating coordinate information on the predetermined road map with the coordinates of the real environment;
placing a virtual object in the virtual environment;
Acquiring detection information obtained by detecting a relative position of an object existing around the own vehicle with respect to the own vehicle by a sensor,
calculating the self-position of the own vehicle;
integrating the detection information acquired by the sensor and the information of the virtual environment into integrated information based on the self-location;
controlling travel of the own vehicle based on the integrated information;
A vehicle evaluation method characterized by: Based on the positional relationship between the detected object, which is the object detected by the sensor, and the virtual object, the detection information of the detected object that is shielded by the virtual object as viewed from the own vehicle is excluded from the integrated information. The vehicle evaluation method according to claim 1, characterized in that: Based on the relative distance between the own vehicle and the detected object, and the relative distance between the own vehicle and the virtual object in the virtual environment, the object to be detected is determined as viewed from the own vehicle. 3. The vehicle evaluation method according to claim 2, further comprising determining whether or not the vehicle is blocked by the virtual object. 4. The vehicle evaluation according to any one of claims 1 to 3, wherein when the virtual environment is constructed, the road surface shape of the road included in the road map is corrected to match the road surface shape of the real environment. Method. arranging a static object as the virtual object;
The vehicle evaluation method according to any one of claims 1 to 4, wherein the upper surface of the stationary object is corrected in accordance with the shape of the road surface in the real environment of the coordinates at which the stationary object is arranged. The vehicle evaluation method according to any one of claims 1 to 5, wherein the virtual object is a moving object that moves in accordance with the shape of the road surface in the real environment of the coordinates at which the virtual object is positioned. The vehicle evaluation method according to any one of claims 1 to 5, wherein a moving object that moves according to a predetermined scenario or a predetermined program is arranged as the virtual object. estimating the integrated information in the future at a time advanced by the computation time for building the virtual environment and integrating the integrated information;
controlling travel of the own vehicle based on the future integrated information;
The vehicle evaluation method according to any one of claims 1 to 7, characterized in that: A vehicle evaluation device for an automatically driven vehicle that automatically drives the own vehicle based on the surrounding environment of the own vehicle,
a map database that stores predetermined road map information;
a sensor that detects objects existing around the own vehicle;
an actuator for generating a vehicle behavior in the subject vehicle;
constructing a virtual environment in which a virtual position on the road map corresponding to the position of the own vehicle in the real environment is determined by associating the coordinate information on the road map with the coordinates of the real environment; A virtual object is arranged in the virtual object, a sensor detects the relative position of an object existing around the own vehicle with respect to the own vehicle, and the detection information is obtained, the self-position of the self-vehicle is calculated, and a controller that integrates the detection information acquired by the sensor and the information of the virtual environment into integrated information and controls the actuator based on the integrated information;
A vehicle evaluation device comprising:

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