Vehicle identification system and identification method

Abstract

The present invention provides a vehicle identification system and identification method that can prevent the control function of a vehicle from being excessively inhibited by the attachment of dirt to LIDAR. The vehicle identification system includes: a vehicle-mounted laser radar device that uses light or electromagnetic waves close to light to detect an object and includes a dirt detection unit, which calculates a dirt value indicating the degree of dirt of the device for each of the segments obtained by dividing the detection range of the object into a plurality of segments based on the detection result of the object; and a dirt determination device, including a dirt determination unit, which determines that dirt to be removed is attached to the vehicle-mounted laser radar device when a first condition and a second condition are met, the first condition being that a specified time has passed since the dirt value exceeded a specified threshold, and the second condition being that the difference between the maximum value and the minimum value of the dirt value within the specified time is within a specified range.

Description

Technical Field

[0001] The invention relates to a vehicle identification system and an identification method. Background Art

[0002] In recent years, research on automatic control of vehicles is being promoted. In the automatic control of vehicles, a laser radar (Light Detection and Ranging, LIDAR) installed on the vehicle is used to detect the distance from the vehicle to the surrounding objects of the vehicle. LIDAR is a device that irradiates light (or electromagnetic waves with a wavelength close to light) and measures its scattered light, and measures the distance to the object based on the time from light emission to light reception. Therefore, if dirt adheres to the irradiation part of the light or the light receiving part of the scattered light, the measurement performance may be reduced. Patent document 1 describes the following method: In order to reduce the influence of the light used for distance measurement on the measurement result when it is reflected by a wiper such as a dirty wiper that wipes the measuring device, the distance information obtained other than the nth time is used to correct the distance information obtained at the nth time.

[0003] [Prior art literature]

[0004] [Patent Document]

[0005] [Patent Document 1] Japanese Patent Application Publication No. 2018-87703 Summary of the invention

[0006] [Problems to be solved by the invention]

[0007] However, in the prior art, even if the acquired distance information can be corrected, it may not be possible to identify the extent to which dirt adheres to the LIDAR. Therefore, the control function of the vehicle may be excessively inhibited due to the adhesion of dirt to the LIDAR.

[0008] The present invention has been completed in consideration of such a situation, and one of its purposes is to provide a vehicle recognition system and recognition method that can prevent the control function of the vehicle from being excessively inhibited due to the adhesion of dirt to the LIDAR.

[0009] [Technical means to solve the problem]

[0010] The vehicle recognition system and recognition method of the present invention adopt the following configurations.

[0011] (1): A vehicle identification system according to an embodiment of the present invention comprises: a vehicle-mounted laser radar device, which detects objects using light or electromagnetic waves close to light and comprises a dirt detection unit, wherein the dirt detection unit calculates a dirt value indicating the degree of dirtiness of the device for each of a plurality of segments obtained by dividing a detection range of the object into a plurality of segments based on a detection result of the object; and a dirt determination device, comprising a dirt determination unit, wherein the dirt determination unit determines whether dirt to be removed is attached to the vehicle-mounted laser radar device when a first condition and a second condition are satisfied, the first condition being that a specified time has passed since the dirt value exceeded a specified threshold value, and the second condition being that a difference between a maximum value and a minimum value of the dirt value within the specified time is within a specified range.

[0012] (2): In the embodiment of (1), the dirt determination unit determines that dirt to be removed is attached to the vehicle-mounted laser radar device when a third condition is satisfied in addition to the first and second conditions, and the third condition is that the fluctuation of the dirt value does not meet a specified ratio within the past determination time when the dirt value exceeds a threshold value.

[0013] (3): In the embodiment of (2), the dirt determination unit determines that dirt to be removed is attached to the vehicle-mounted laser radar device when a fourth condition is satisfied in addition to the first condition, the second condition and the third condition, and the fourth condition is that the driving speed of the vehicle equipped with the vehicle-mounted laser radar device does not fall below a prescribed lower limit for a prescribed time.

[0014] (4) In the embodiment of any one of (1) to (3), it further includes a notification unit, which notifies the vehicle-mounted laser radar device of the situation when the dirt determination unit determines that the dirt to be removed is attached to the vehicle-mounted laser radar device.

[0015] (5): In the embodiments of any one of (1) to (4), when the dirt value in all sections is below a specified threshold, the dirt determination unit determines that the vehicle-mounted laser radar device has recovered from a state in which dirt to be removed is attached to a state in which the dirt to be removed is not attached.

[0016] (6): In an identification method of an embodiment of the present invention, a vehicle-mounted laser radar device that detects an object using light or electromagnetic waves close to light calculates a dirtiness value indicating the degree of dirtiness of the device based on the detection result of the object for each of the segments obtained by dividing the detection range of the object into a plurality of segments, and a dirtiness determination device determines that dirt to be removed is attached to the vehicle-mounted laser radar device when a first condition and a second condition are met. The first condition is that a specified time has passed since the dirtiness value exceeded a specified threshold, and the second condition is that the difference between the maximum and minimum values ​​of the dirtiness value within the specified time is within a specified range.

[0017] [Effects of the Invention]

[0018] According to (1) to (6), a vehicle-mounted laser radar device that detects objects using light or electromagnetic waves close to light calculates a dirtiness value indicating the degree of dirtiness of the device for each of the segments obtained by dividing the detection range of the object into a plurality of segments based on the detection result of the object. A dirtiness determination device determines whether dirt to be removed is attached to the vehicle-mounted laser radar device when a first condition and a second condition are satisfied. The first condition is that a specified time has passed since the dirtiness value exceeded a specified threshold value, and the second condition is that the difference between the maximum and minimum values ​​of the dirtiness value within the specified time is within a specified range. This prevents the control function of the vehicle from being excessively inhibited due to the attachment of dirt to the LIDAR. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a configuration diagram of a vehicle system using the vehicle control device according to the first embodiment.

[0020] Figure 2 It is a functional configuration diagram of the first control unit and the second control unit in the first embodiment.

[0021] Figure 3A This is a diagram showing an example of the detection range of the LIDAR mounted on the vehicle in the vehicle system according to the first embodiment.

[0022] Figure 3B This is a diagram showing an example of the detection range of the LIDAR mounted on the vehicle in the vehicle system according to the first embodiment.

[0023] Figure 4 This is a diagram showing an example of threshold information in the first embodiment.

[0024] Figure 5 It is a configuration diagram of a vehicle system using the vehicle control device according to the second embodiment.

[0025] Figure 6 This is a diagram showing an example of condition information in the second embodiment.

[0026] Figure 7 This is a flowchart showing an example of a method in which the contamination determination unit manages the contamination mark in the object recognition device according to the second embodiment.

[0027] [Explanation of Symbols]

[0028] 1A, 1B: Vehicle systems

[0029] 10: Camera

[0030] 12: Radar device

[0031] 14A, 14B: LIDAR (laser radar)

[0032] 151: Dirt detection unit

[0033] 16A, 16B: Object recognition device

[0034] 171A, 171B: Contamination determination unit

[0035] 172: Threshold information

[0036] 173: Condition Information

[0037] 20: Communication device

[0038] 30: HMI (Human Machine Interface)

[0039] 40: Vehicle Sensors

[0040] 50: Navigation device

[0041] 51: GNSS (Global Navigation Satellite System) Receiver

[0042] 52: Navigation HMI

[0043] 53: Path determination unit

[0044] 54: First map information

[0045] 60: MPU (Map Positioning Unit)

[0046] 61: Recommended lane determination unit

[0047] 62: Second map information

[0048] 80: Driving operation parts

[0049] 100: Automatic driving control device

[0050] 100-1: Communication controller

[0051] 100-2: CPU (Central Processing Unit)

[0052] 100-3: RAM (Random Access Memory)

[0053] 100-4: ROM (read-only memory)

[0054] 100-5: Storage Device

[0055] 100-5a: Procedure

[0056] 100-6: Drive device

[0057] 120: First control unit

[0058] 130: Identification Department

[0059] 140: Action Plan Generation Department

[0060] 160: Second control unit

[0061] 164: Speed ​​control unit

[0062] 166: Steering control unit

[0063] 180: Inform the control department

[0064] 200: Driving force output device

[0065] 210: Brake device

[0066] 220: Steering device DETAILED DESCRIPTION

[0067] Hereinafter, embodiments of the vehicle recognition system and recognition method according to the present invention will be described with reference to the drawings.

[0068] <First embodiment>

[0069] [Overall structure]

[0070] Figure 1 1 is a structural diagram of a vehicle system 1A using the vehicle control device of the first embodiment. The vehicle equipped with the vehicle system 1A is, for example, a two-wheel, three-wheel, or four-wheel vehicle, and its driving source is an internal combustion engine such as a diesel engine or a gasoline engine, an electric motor, or a combination thereof. The electric motor is operated using the generated power generated by a generator connected to the internal combustion engine, or the discharged power of a secondary battery or a fuel cell.

[0071] The vehicle system 1A includes, for example, a camera 10, a radar device 12, a light detection and ranging (LIDAR) 14A, an object recognition device 16A, a communication device 20, a human machine interface (HMI) 30, a vehicle sensor 40, a navigation device 50, a map positioning unit (MPU) 60, a driving operating part 80, an automatic driving control device 100, a driving drive force output device 200, a brake device 210, and a steering device 220. These devices or machines are connected to each other through multiple communication lines such as a controller area network (CAN) communication line or a serial communication line, a wireless communication network, etc. In addition, Figure 1 The structure shown is just an example, and a part of the structure may be omitted or other structures may be further added.

[0072] The camera 10 is, for example, a digital camera using a solid-state imaging element such as a charge coupled device (CCD) or a complementary metal oxide semiconductor (CMOS). The camera 10 is installed at any position of a vehicle (hereinafter referred to as the vehicle) equipped with the vehicle system 1A. When shooting the front, the camera 10 is installed on the upper part of the front windshield or on the back of the rearview mirror inside the vehicle. The camera 10, for example, repeatedly and periodically shoots the surroundings of the vehicle. The camera 10 may also be a stereo camera.

[0073] The radar device 12 transmits radio waves such as millimeter waves to the surroundings of the vehicle, and detects the radio waves (reflected waves) reflected by the object to detect at least the position (distance and direction) of the object. The radar device 12 is installed at any part of the vehicle. The radar device 12 can also detect the position and speed of the object by using a frequency modulated continuous wave (FM-CW) method.

[0074] The LIDAR 14A irradiates light (or electromagnetic waves with a wavelength close to light) to the periphery of the vehicle and measures the scattered light. For example, the LIDAR 14A irradiates infrared light. The LIDAR 14A detects the distance of the object based on the time from light emission to light reception. The irradiated light is, for example, pulsed laser light. The LIDAR 14A is installed at any part of the vehicle. In addition, in addition to the basic function (hereinafter referred to as "LIDAR function"), the LIDAR 14A in this embodiment also has a function of detecting dirt attached to the light emitting part or the light receiving part (hereinafter referred to as "LIDAR dirt"). In order to realize the above function, the LIDAR 14A in this embodiment includes a dirt detection unit 151. The dirt detection unit 151 detects LIDAR dirt based on the detection result of the distance (reflection point) obtained by the LIDAR function and the intensity of the reflected light observed during the distance detection (hereinafter referred to as "reflection intensity"). In addition, the reflection point is an example of a "detection point".

[0075] The dirt detection unit 151 is implemented, for example, by a hardware processor such as a central processing unit (CPU) executing a program (software). In addition, the dirt detection unit 151 can also be implemented by hardware (including a circuit unit (circuitry)) such as a large-scale integrated circuit (LSI) or an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a graphics processing unit (GPU), etc., or can be implemented by the collaboration of software and hardware. The program can be pre-stored in a storage device such as an HDD or a flash memory of the LIDAR 14A (including a storage device of a non-disposable storage medium), or can be pre-stored in a removable storage medium such as a digital versatile disk (DVD) or a read-only disk (CD-ROM), and installed in the HDD or flash memory of the LIDAR 14A by installing the storage medium (non-disposable storage medium) in a drive device. LIDAR 14A is an example of a "vehicle-mounted laser radar device".

[0076] Specifically, the dirt detection unit 151 calculates an index value indicating the degree of dirtiness of the LIDAR (hereinafter referred to as "dirtiness value") based on the detection result obtained by the LIDAR function and the reflection intensity. In addition, the dirtiness value may be any value as long as it indicates the degree of dirtiness of the LIDAR, and may be calculated using any method. For example, the dirtiness detection unit 151 calculates the dirtiness value based on the number of reflection points near the LIDAR 14A, the distance to the reflection point, and the reflection intensity. The dirtiness detection unit 151 calculates the dirtiness value by dividing the detection range of the LIDAR 14A in the horizontal direction into a prescribed number of regions. Hereinafter, each region into which the detection range is divided into a prescribed number is referred to as a segment. In the present embodiment, the case where the detection range of each LIDAR 14A is divided into 10 segments is described. The dirtiness detection unit 151 outputs the calculated dirtiness value to the object recognition device 16A.

[0077] The object recognition device 16A performs sensor fusion processing on the detection results obtained by part or all of the camera 10, the radar device 12, and the LIDAR 14A to recognize the position, type, speed, etc. of the object. The object recognition device 16A outputs the recognition result to the automatic driving control device 100. In addition, in addition to the basic function (hereinafter referred to as the "object recognition function"), the object recognition device 16A in this embodiment also has the function of outputting a dirt mark for each LIDAR 14A. The dirt mark is a mark indicating whether each LIDAR 14A is in a state where the LIDAR dirt needs to be removed (hereinafter referred to as the "dirty state"). In order to realize the above function, for example, the object recognition device 16A includes a dirt determination unit 171A and stores threshold information 172. The dirt determination unit 171A or the threshold information 172 may also be included in the LIDAR 14A.

[0078] The dirt determination unit 171A is implemented, for example, by executing a program (software) through a hardware processor such as a CPU. In addition, the dirt determination unit 171A may also be implemented by hardware (including a circuit unit (circuitry)) such as an LSI or ASIC, FPGA, GPU, or the like, or may be implemented by the collaboration of software and hardware. The program may be pre-stored in a storage device such as an HDD or flash memory of the object recognition device 16A (including a storage device of a non-disposable storage medium), or may be pre-stored in a removable storage medium such as a DVD or CD-ROM, and installed in the HDD or flash memory of the object recognition device 16A by installing the storage medium (non-disposable storage medium) in a drive device. The object recognition device 16A is an example of a "dirt determination device".

[0079] Here, the threshold information 172 is information used when determining whether each LIDAR 14A is in a dirty state, and is information indicating a threshold value of the dirtiness value. The dirtiness determination unit 171A determines whether each LIDAR 14A is in a dirty state by comparing the dirtiness value notified from the LIDAR 14A with the threshold information 172. Hereinafter, the determination is referred to as "dirty determination". The dirtiness determination unit 171A updates the dirtiness mark according to the result of the dirtiness determination, and notifies the automatic driving control device 100 of the value of the updated dirtiness mark. For example, the dirtiness determination unit 171A sets up a dirtiness mark (sets the value of the dirtiness mark to 1) when it is determined that the LIDAR 14A is in a dirty state, and removes the dirtiness mark (sets the value of the dirtiness mark to 0) when it is determined that the LIDAR 14A is not in a dirty state.

[0080] The communication device 20 communicates with other vehicles located around the vehicle, or communicates with various server devices via a wireless base station, for example, using a cellular network or a Wireless Fidelity (Wi-Fi) network, Bluetooth (registered trademark), Dedicated Short Range Communication (DSRC), etc.

[0081] The HMI 30 presents various information to the occupants of the vehicle and accepts input operations performed by the occupants. The HMI 30 includes various display devices, speakers, buzzers, touch screens, switches, keys, etc. For example, the HMI 30 performs an action of notifying the LIDAR 14A that it is dirty according to the instruction of the automatic driving control device 100 (hereinafter referred to as "dirt notification action"). For example, the HMI 30 performs an action such as displaying a message urging the LIDAR to remove dirt or outputting a sound as the dirt notification action.

[0082] The vehicle sensor 40 includes a vehicle speed sensor for detecting the speed of the vehicle, an acceleration sensor for detecting acceleration, a yaw rate sensor for detecting the angular velocity around a vertical axis, an azimuth sensor for detecting the orientation of the vehicle, and the like.

[0083] The navigation device 50 includes, for example, a Global Navigation Satellite System (GNSS) receiver 51, a navigation HMI 52, and a path determination unit 53. The navigation device 50 stores first map information 54 in a storage device such as a hard disk drive (HDD) or a flash memory. The GNSS receiver 51 determines the position of the vehicle based on signals received from GNSS satellites. The position of the vehicle can also be determined or supplemented by an inertial navigation system (INS) using the output of the vehicle sensor 40. The navigation HMI 52 includes a display device, a speaker, a touch screen, keys, etc. The navigation HMI 52 can also be partially or completely shared with the aforementioned HMI 30. The path determination unit 53, for example, refers to the first map information 54 to determine a path (hereinafter referred to as a path on the map) from the position of the vehicle determined by the GNSS receiver 51 (or an input arbitrary position) to the destination input by the occupant using the navigation HMI 52. The first map information 54 is, for example, information that expresses the shape of a road using links representing roads and nodes connected by the links. The first map information 54 may also include information such as the curvature of the road or points of interest (POI). The path on the map is output to the MPU 60. The navigation device 50 may also provide path guidance using the navigation HMI 52 based on the path on the map. The navigation device 50 may also be implemented, for example, by the functions of terminal devices such as smartphones or tablet terminals held by passengers. The navigation device 50 may also send the current location and destination to the navigation server via the communication device 20, and obtain a path equivalent to the path on the map from the navigation server.

[0084] The MPU 60 includes, for example, a recommended lane determination unit 61, and the second map information 62 is stored in a storage device such as a HDD or a flash memory. The recommended lane determination unit 61 divides the path on the map provided by the navigation device 50 into a plurality of blocks (for example, divided into each 100 [m] with respect to the vehicle's traveling direction), and determines a recommended lane for each block with reference to the second map information 62. The recommended lane determination unit 61 determines the lane on which the vehicle should travel from the left. When there is a branch point in the path on the map, the recommended lane determination unit 61 determines the recommended lane in a manner that allows the vehicle to travel on a reasonable path for traveling to the branch destination.

[0085] The second map information 62 is map information with higher accuracy than the first map information 54. The second map information 62 includes, for example, information on the center of a lane or information on a lane boundary. In addition, the second map information 62 may include road information, traffic restriction information, address information (address, zip code), facility information, telephone number information, etc. The second map information 62 may be updated at any time by allowing the communication device 20 to communicate with other devices.

[0086] The driving operation member 80 includes, for example, an accelerator pedal, a brake pedal, a shift lever, a steering wheel, a special-shaped steering wheel, a joystick, and other operating members. A sensor for detecting the amount of operation or the presence or absence of operation is installed on the driving operation member 80, and the detection result is output to the automatic driving control device 100, or part or all of the driving force output device 200, the brake device 210, and the steering device 220.

[0087] The automatic driving control device 100 is a device for controlling the automatic driving (including driving assistance) of the vehicle. The automatic driving control device 100 includes, for example, a first control unit 120, a second control unit 160, and a notification control unit 180. The first control unit 120, the second control unit 160, and the notification control unit 180 are respectively implemented by executing a program (software) by a hardware processor such as a CPU. In addition, part or all of these components can also be implemented by hardware (including a circuit unit (circuitry)) such as LSI or ASIC, FPGA, GPU, etc., or by the collaboration of software and hardware. The program can be pre-stored in a storage device such as an HDD or flash memory of the automatic driving control device 100 (including a storage device of a non-disposable storage medium), or can be pre-stored in a removable storage medium such as a DVD or CD-ROM, and installed in the HDD or flash memory of the automatic driving control device 100 by installing the storage medium (non-disposable storage medium) in a drive device. In addition, the combination of the HMI 30 and the notification control unit 180 is an example of a "notification unit".

[0088] Figure 2It is a functional structure diagram of the first control unit 120 and the second control unit 160. The first control unit 120, for example, includes a recognition unit 130 and an action plan generation unit 140. The first control unit 120, for example, implements in parallel functions performed with the help of artificial intelligence (AI) and functions performed with the help of a pre-given model. For example, the "intersection recognition" function can be achieved by performing in parallel the recognition of intersections performed with the help of deep learning, etc., and the recognition based on pre-given conditions (signals that can be pattern matched, road signs, etc.), and scoring both for comprehensive evaluation. In this way, the reliability of autonomous driving is ensured.

[0089] The recognition unit 130 recognizes the position, speed, acceleration, and other states of objects located around the vehicle based on information input from the camera 10, the radar device 12, and the LIDAR 14A via the object recognition device 16A. The position of the object is, for example, recognized as a position on an absolute coordinate with a representative point (center of gravity or drive shaft center, etc.) of the vehicle as the origin, and is used for control. The position of the object can be represented by a representative point such as the center of gravity or corner of the object, or by an area to be expressed. The so-called "state" of an object may also include the acceleration or jerk of the object, or the "action state" (for example, whether a lane change is being made or a lane change is intended).

[0090] In addition, the recognition unit 130 recognizes, for example, the lane in which the vehicle is traveling (driving lane). For example, the recognition unit 130 recognizes the driving lane by comparing the pattern of road dividing lines obtained from the second map information 62 (for example, the arrangement of solid lines and dotted lines) with the pattern of road dividing lines around the vehicle recognized from the image taken by the camera 10. In addition, not limited to road dividing lines, the recognition unit 130 can also recognize the running lane by recognizing the runway boundary (road boundary) including road dividing lines or shoulders, curbs, central isolation strips, guardrails, etc. In the above recognition, the position of the vehicle obtained from the navigation device 50 or the processing result obtained by the INS can also be taken into account. In addition, the recognition unit 130 recognizes temporary stop lines, obstacles, red light signals, toll booths, and other road objects / events.

[0091] When identifying the driving lane, the recognition unit 130 recognizes the position or posture of the vehicle relative to the driving lane. For example, the recognition unit 130 may recognize the deviation of the reference point of the vehicle from the center of the lane and the angle formed by the travel direction of the vehicle relative to the line connecting the centers of the lanes as the relative position and posture of the vehicle relative to the driving lane. Alternatively, the recognition unit 130 may recognize the position of the reference point of the vehicle relative to either side end of the driving lane (road dividing line or road boundary) as the relative position of the vehicle relative to the driving lane.

[0092] The action plan generation unit 140 generates a target trajectory for the vehicle to automatically (independent of the driver's operation) travel in the future, so that in principle it travels on the recommended lane determined by the recommended lane determination unit 61, and can thus cope with the surrounding conditions of the vehicle. The target trajectory includes, for example, a speed element. For example, the target trajectory is expressed as a sequence of locations (track points) that the vehicle should arrive at. The track point is the location that the vehicle should arrive at every specified driving distance (for example, a few [m] or so) on the track distance. Different from this, the target speed and target acceleration at every specified sampling time (for example, a few tenths [sec] or so) are generated as part of the target trajectory. In addition, the track point can also be the position that the vehicle should arrive at at the sampling time every specified sampling time. At this time, the information on the target speed or target acceleration is expressed at intervals between track points.

[0093] The action plan generation unit 140 may set an event for autonomous driving each time the target trajectory is generated. The events for autonomous driving include a constant speed driving event, a low speed following driving event, a lane change event, a diverging event, a merging event, a takeover event, etc. The action plan generation unit 140 generates a target trajectory corresponding to the activated event.

[0094] The second control unit 160 controls the travel driving force output device 200 , the brake device 210 , and the steering device 220 so that the host vehicle passes through the target track generated by the action plan generation unit 140 at a predetermined timing.

[0095] In addition, the first control unit 120 or the second control unit 160 can also be configured to determine whether driving assistance or automatic driving can be performed based on the determination result of the dirt determination unit 171A, and determine the execution, temporary suspension, stop, restart, end, etc. of processing related to driving assistance or automatic driving based on the determination result.

[0096] return Figure 2, the second control unit 160 includes, for example, an acquisition unit 162, a speed control unit 164, and a steering control unit 166. The acquisition unit 162 acquires the information of the target track (track point) generated by the action plan generation unit 140, and stores it in a memory (not shown). The speed control unit 164 controls the travel drive force output device 200 or the brake device 210 based on the speed element attached to the target track stored in the memory. The steering control unit 166 controls the steering device 220 according to the curvature of the target track stored in the memory. The processing of the speed control unit 164 and the steering control unit 166 is achieved, for example, by a combination of feedforward control and feedback control. As an example, the steering control unit 166 combines the execution of feedforward control corresponding to the curvature of the road ahead of the vehicle and feedback control based on the deviation from the target track.

[0097] return Figure 1 The notification control unit 180 has a function of instructing the HMI 30 to perform a contamination notification operation according to the value of the contamination flag notified from the object recognition device 16A. For example, when the notification control unit 180 is notified of 1 as the value of the contamination flag, it instructs the HMI 30 to perform a contamination notification operation, and when the notification control unit 180 is notified of 0 as the value of the contamination flag, it does not instruct the HMI 30 to perform a contamination notification operation.

[0098] The driving force output device 200 outputs the driving force (torque) for driving the vehicle to the driving wheels. The driving force output device 200 includes, for example, a combination of an internal combustion engine, an electric motor, and a transmission, and an electronic control unit (ECU) for controlling them. The ECU controls the structure according to information input from the second control unit 160 or information input from the driving operation member 80.

[0099] The brake device 210 includes, for example, a brake caliper, a cylinder that transmits hydraulic pressure to the brake caliper, an electric motor that generates hydraulic pressure in the cylinder, and a brake ECU. The brake ECU controls the electric motor based on information input from the second control unit 160 or information input from the driving operating member 80 to output brake torque corresponding to the braking operation to each wheel. The brake device 210 may include a mechanism that transmits the hydraulic pressure generated by the operation of the brake pedal included in the driving operating member 80 to the cylinder via a master cylinder as a backup. In addition, the brake device 210 is not limited to the structure described above, and may also be an electronically controlled hydraulic brake device that controls an actuator based on information input from the second control unit 160 to transmit the hydraulic pressure of the master cylinder to the cylinder.

[0100] The steering device 220 includes, for example, a steering ECU and an electric motor. The electric motor, for example, applies force to a rack-and-pinion mechanism to change the direction of the steering wheel. The steering ECU drives the electric motor to change the direction of the steering wheel based on information input from the second control unit 160 or information input from the driving operating member 80.

[0101] Figure 3A and Figure 3B 1 is a diagram showing an example of a detection range of the LIDAR 14A mounted on the host vehicle M in the vehicle system 1A according to the first embodiment. Figure 3A and Figure 3B The detection range of a total of five LIDARs 14A is shown, one each at the front right, front left, rear center, rear right, and rear left of the vehicle M. Figure 3A In FIG. 1 , LIDAR 14A-FR represents the front right LIDAR 14A, and LIDAR 14A-FL represents the front left LIDAR. Figure 3B In the figure, LIDAR 14A-RR represents the rear right LIDAR, LIDAR 14A-RL represents the rear left LIDAR 14A, and LIDAR 14A-RC represents the rear center LIDAR 14A. .

[0102] exist Figure 3A and Figure 3B , the detection ranges DR-FR, DR-FL, DR-RR, DR-RL, and DR-RC represent the detection ranges of the LIDAR 14A-FR, LIDAR 14A-FL, LIDAR 14A-RR, LIDAR 14A-RL, and LIDAR 14A-RC of the front right, front left, rear right, rear left, and rear center, respectively.

[0103] Furthermore, as described above, in the vehicle system 1A of the present embodiment, the calculation of the dirtiness value is performed based on the detection range of each LIDAR 14A divided into 10 segments. Specifically, the detection range DR-FR is divided into segments FR01 to FR10, the detection range DR-FL is divided into segments FL01 to FL10, the detection range DR-RR is divided into segments RR01 to RR10, the detection range DR-RL is divided into segments RL01 to RL10, and the detection range DR-RC is divided into segments RC01 to RC10.

[0104] However, in the automatic driving control of the vehicle, generally speaking, it is important to detect the distances directly in front of, directly behind, and diagonally behind the vehicle M. For distance detection in these directions, higher detection accuracy is required than for other areas. Therefore, for the LIDAR 14A used for detection in these directions, it is ideal to eliminate LIDAR contamination when the degree of contamination is relatively light. Therefore, in the vehicle system 1A of the present embodiment, the threshold value for contamination determination is set for each section of the detection range. In this way, local LIDAR contamination can be detected, and LIDAR contamination in a section with a high priority can be detected at a relatively early stage.

[0105] also, Figure 3A and Figure 3B The directions of the detection ranges of the LIDARs 14A and the number of segments constituting each detection range shown in the example are examples and may be changed to other values ​​as required. Figure 3A and Figure 3B In addition, the number or installation position of the LIDAR 14A installed in the vehicle M may be changed to the same Figure 3A and Figure 3B Different forms. For example, the detection range can be divided into more than 11 segments, or it can be divided into less than 9 segments. In addition, the detection range can be divided not only in the horizontal direction, but also in the vertical direction, or only in the vertical direction. In addition, for example, multiple LIDARs 14A can be set so that each detection range is symmetrical left-right or top-bottom with respect to a specified axis (for example, the center axis of the vehicle or the direction of travel), or it can be set asymmetrically.

[0106] Figure 4 1 is a diagram showing an example of the threshold information 172 in the first embodiment. Figure 4 As shown, the threshold information 172 is stored in the object recognition device 16A as a table showing the correspondence between the segment identification (identification, ID) of each segment and the threshold value of the contamination value in the contamination determination of each segment. Figure 4 , an example of threshold information 172-FL related to the LIDAR 14A-FL installed at the front left part of the host vehicle M is shown, and an example of threshold information 172-FR related to the LIDAR 14A-FR installed at the front right part of the host vehicle M is shown. In addition, Figure 4 , an example of threshold information 172-RL related to the LIDAR 14A-RL disposed at the rear left portion of the vehicle M is shown, an example of threshold information 172-RC related to the LIDAR 14A-RC disposed at the rear center portion of the vehicle M is shown, and an example of threshold information 172-RR related to the LIDAR 14A-RR disposed at the rear right portion of the vehicle M is shown. Figure 4 In the example, the segment ID value is Figure 3A and Figure 3B Corresponding to the segment ID recorded in.

[0107] As described above, in the automatic driving control of the host vehicle M, the distance detection of the front front, rear front, and left and right oblique rear of the host vehicle M becomes important. Therefore, in the example of the threshold information 172-FL, the thresholds of the sections FL03 to FL06 corresponding to the front front of the host vehicle M are set to 50% which is relatively low compared to other sections. Similarly, in the example of the threshold information 172-FR, the thresholds of the sections FR05 to FR08 corresponding to the front front of the host vehicle M are set to 50% which is relatively low compared to other sections.

[0108] On the other hand, Figure 4 In the example of the threshold information 172-RL shown in FIG. 1 , the thresholds of the sections RL06 to RL08 corresponding to the left oblique rear of the vehicle M are set to 60% which is relatively low compared to the other sections. Figure 4 In the example of the threshold information 172-RC shown in FIG. 1 , the thresholds of the segments RC04 to RC07 corresponding to the rear front of the host vehicle M are set to 50% which is relatively low compared to the other segments. Figure 4 In the example of the threshold value information 172 -RR shown, the threshold values ​​of the sections RR03 to RR05 corresponding to the right oblique rear of the host vehicle M are set to 60% which is relatively low compared to the other sections.

[0109] In this way, in the sections corresponding to the front or rear of the vehicle M among the multiple sections (for example, sections FL03 to FL06, sections FR05 to FR08, sections RC04 to RC07, sections RL06 to RL08, sections RR03 to RR05), a threshold lower than that of other areas is set in the same detection range, and in the sections in the lateral direction of the vehicle (for example, sections other than sections FL03 to FL06, sections FR05 to FR08, sections RC04 to RC07, sections RL06 to RL08, sections RR03 to RR05), a threshold higher than that of other areas is set.

[0110] At this time, in the automatic driving control device 100, the contamination determination unit 171A compares the contamination value (hereinafter referred to as "measurement value") notified to each LIDAR 14A for each section with the threshold value set for each section. If there is a section where the measurement value is greater than the threshold value, the contamination determination unit 171A sets a contamination flag for the LIDAR 14A having this section within the detection range and notifies the automatic driving control device 100. In the automatic driving control device 100 that receives the notification, the notification control unit 180 instructs the HMI 30 to perform a contamination notification operation on the LIDAR 14A.

[0111] For example, in Figure 4 In the example, when 55% is measured as the contamination value in the segment FL05, since the measured value is greater than the threshold value 50% of the segment FL05, the contamination determination unit 171A sets a contamination flag for the LIDAR 14A-FL having the segment FL05 in the detection range and notifies the automatic driving control device 100. In the automatic driving control device 100 that receives the notification, the notification control unit 180 instructs the HMI 30 to perform a contamination notification operation on the LIDAR 14A-FL.

[0112] In the vehicle system 1A of the first embodiment configured as above, each LIDAR 14A mounted on the vehicle calculates a contamination value for each segment obtained by dividing the detection range in the horizontal direction into a predetermined number, and the automatic driving control device 100 determines whether to perform a contamination notification operation for each LIDAR 14A based on the contamination value calculated for each segment and the threshold value of the contamination value set in the corresponding segment. By including such a structure, the vehicle system 1A of the embodiment can detect local LIDAR contamination and detect LIDAR contamination at a timing corresponding to the priority of each segment. That is, according to the vehicle system 1A of the embodiment, the control function of the vehicle can be prevented from being excessively inhibited due to the adhesion of contamination to the LIDAR.

[0113] <Second embodiment>

[0114] Figure 5 1 is a structural diagram of a vehicle system 1B using the vehicle control device of the second embodiment. The difference between the vehicle system 1B and the vehicle system 1A of the first embodiment is that the LIDAR 14B is included instead of the LIDAR 14A, and the object recognition device 16B is included instead of the object recognition device 16A. In addition, the difference from the object recognition device 16A of the first embodiment is that the object recognition device 16B includes a dirt determination unit 171B instead of the dirt determination unit 171A, and storage condition information 173 instead of threshold information 172. The rest of the structure of the vehicle system 1B is the same as that of the vehicle system 1A. Therefore, in Figure 5 In the middle, mark and Figure 1 The same symbols are used to omit the description of their same structures.

[0115] The difference from the contamination determination unit 171A is that the contamination determination unit 171A of the first embodiment manages the contamination flag based on the contamination value notified from the LIDAR 14A, whereas the contamination determination unit 171B manages the contamination flag based on the speed of the vehicle in addition to the contamination value. Specifically, the contamination determination unit 171B manages the contamination flag based on the results of the contamination determination under the plurality of determination conditions defined by the condition information 173.

[0116] Figure 6 1 is a diagram showing an example of condition information 173 in the second embodiment. For example, in the condition information 173, the names of a plurality of determination conditions for soil determination (condition names), the contents of the determination conditions (condition contents), and the categories of the determination conditions (condition categories) are registered in correspondence. Figure 6 In the example of condition information 173, as the condition for setting the dirt mark (mark on (ON) condition), the dirt threshold condition, the dirt value fluctuation condition and the vehicle speed condition are registered, and as the condition for removing the dirt mark (mark off (OFF) condition), the recovery condition is set. The details of each mark on condition and mark off condition are as follows. The vehicle speed condition can also be omitted.

[0117] [Dirty threshold condition]

[0118] The dirt threshold condition is a condition for determining whether the amount of material (dirt) attached to the LIDAR exceeds a certain amount. Generally speaking, when a vehicle is traveling at high speed in a low-temperature environment, water droplets on the surface of the LIDAR 14B may sometimes adhere for a short time like dew. Therefore, in this situation, the dirt value may sometimes rise temporarily, so it is possible to mistakenly detect this state as a dirty state. In addition, when the vehicle is just starting and traveling at a low speed, the possibility of water droplets brought by rainfall staying on the surface of the LIDAR 14B is low, and basically the dirt value will not exceed the threshold. Therefore, in this embodiment, the condition that makes the judgment result true when the dirt value exceeds the threshold and does not fall below the threshold for a specified time (for example, 300 seconds) is set as the dirt value condition. Hereinafter, the specified time when judging the dirt threshold condition is referred to as the judgment time.

[0119] [Conditions for fluctuation of dirtiness value]

[0120] The dirt value fluctuation condition is a condition for determining whether the LIDAR dirt is dirt that needs to be wiped off. Specifically, the dirt value fluctuation condition is a condition that makes the determination result true when the magnitude of the fluctuation of the dirt value within the past determination time (for example, 300 seconds) that has passed when the dirt value exceeds the threshold value is less than a specified ratio (for example, the difference between the maximum value and the minimum value is less than 10%). This is based on the following insights obtained, that is, as an example of dirt that needs to be wiped off, when a mixture of oil and sand is attached to the surface of the LIDAR 14B, the magnitude of the fluctuation of the dirt value sometimes exceeds 10% before the determination time has passed. If the determination time is too long, there is a concern that the dirt that needs to be wiped off cannot be detected. In addition, it usually takes about several minutes to stop the vehicle in order to wipe off the LIDAR dirt, so the determination time can also be set to, for example, about 300 seconds.

[0121] [Speed ​​conditions]

[0122] The vehicle speed condition is a condition for determining whether the vehicle is traveling at a speed that promotes LIDAR contamination. It is generally believed that LIDAR contamination may be promoted when loading and unloading goods while parking, or when the vehicle is slowing down at a very close distance to an object (for example, traveling at a speed of less than 10 km per hour). Therefore, in this embodiment, a condition that makes the determination result true when the speed of the vehicle exceeds a prescribed upper speed limit (for example, 20 km per hour) and does not fall below a prescribed lower speed limit (for example, 10 km per hour) for a prescribed time (for example, 8 seconds) is set as the vehicle speed condition. This is based on the following insight, that is, when the vehicle starts normal driving (for example, driving at a speed of more than 20 km per hour) from a state of being parked at a very close distance to an object, LIDAR contamination will be fully removed by driving for 8 seconds.

[0123] [Restoration conditions]

[0124] As described above, the recovery condition is a condition for determining whether the dirt mark erected when the mark opening condition is satisfied can be removed. Therefore, the recovery condition needs to be a condition that can determine that the vehicle is not in a dirty state. Therefore, in this embodiment, the condition that makes the determination result true when the dirt value in all sections is below a threshold value (for example, 30%) is set as the recovery condition. The threshold value in the above case can be designed in consideration of the following aspects: even if there are scratches or dirt that do not affect the detection performance on the surface of the LIDAR 14B, the dirt mark can be removed, and the dirt mark is not turned on and off frequently.

[0125] Figure 7This is a flowchart showing an example of a method for managing a dirt mark by the dirt determination unit 171B in the object recognition device 16B of the second embodiment. Here, it is assumed that the dirt mark is managed separately for each LIDAR 14B, and the processing flow for managing the dirt mark of a certain LIDAR 14B is described. First, the dirt determination unit 171B determines whether the dirt values ​​of all sections meet the dirt value condition (step S101). Here, in the case where it is determined that the dirt values ​​of all sections meet the dirt value condition, the dirt determination unit 171B determines whether the dirt values ​​of all sections meet the dirt value fluctuation condition (step S102). Here, in the case where it is determined that the dirt values ​​of all sections meet the dirt value fluctuation condition, the dirt determination unit 171B determines whether the speed of the vehicle meets the vehicle speed condition (step S104). Here, in the case where it is determined that the speed of the vehicle meets the vehicle speed condition, the dirt determination unit 171B sets a dirt mark (step S105).

[0126] On the other hand, in step S101, when it is determined that the contamination value of any section does not satisfy the contamination value condition, or in step S102, when it is determined that the contamination value of any section does not satisfy the contamination value fluctuation condition, or in step S104, when it is determined that the speed of the vehicle does not satisfy the vehicle speed condition, the contamination determination unit 171B determines whether the recovery condition is satisfied (step S106). Here, if it is determined that the recovery condition is satisfied, the contamination determination unit 171B removes the contamination mark (step S107) and returns the process to step S101. On the other hand, in step S106, if it is determined that the recovery condition is not satisfied, the contamination determination unit 171B does not remove the contamination mark and returns the process to step S101.

[0127] In the vehicle system 1B of the second embodiment configured as above, the object recognition device 16B includes a dirt determination unit 171B that determines whether each LIDAR 14B is in a dirty state using a combination of a plurality of conditions including a condition related to the dirt value. By including such a structure, the vehicle system 1B of the embodiment can determine whether the LIDAR 14B is in a dirty state with higher accuracy. That is, according to the vehicle system 1B of the embodiment, the control function of the vehicle can be prevented from being excessively inhibited due to the dirtiness of the LIDAR.

[0128] <Modification>

[0129] The object recognition device 16A (or 16B, the same below) can directly output the detection results of the camera 10, the radar device 12, and the LIDAR 14A (or 14B, the same below) to the automatic driving control device 100. In addition, in this case, the automatic driving control device 100 may include a dirt determination unit 171B instead of the object recognition device 16A, and the threshold value information (or condition information) may be retained. In this case, the object recognition device 16A may be omitted from the vehicle system 1A (or 1B, the same below).

[0130] In the first control unit 120 and the second control unit 160, each functional unit such as the recognition unit 130 or the action plan generation unit 140, the acquisition unit 162, the speed control unit 164, or the steering control unit 166 may also be configured to branch or change the processing based on the value of the dirt mark notified from the LIDAR 14A via the object recognition device 16A (or 16B). Similarly, the object recognition device 16A (or 16B) may also be configured to branch or change the processing based on the value of the dirt mark notified from the LIDAR 14A. For example, the first control unit 120 and the second control unit 160 may also be configured to retreat the action related to the automatic driving of the vehicle when the notified dirt mark shows that any LIDAR 14A (or 14B) is in a dirty state. In addition, the automatic driving control device 100 may also notify the notified dirt mark to other devices such as the navigation device 50 or the MUP 60. In this case, the other device may be configured to branch or change the processing of the other device based on the value of the contamination flag.

[0131] The notification control unit 180 may cause a device other than the HMI 30 to perform a contamination notification operation, or may perform a contamination notification operation itself. For example, the notification control unit 180 may send an email to a user to whom the LIDAR is to be notified of contamination, or may send a message notification to a terminal device used by the user.

[0132] As mentioned above, although the form for implementing this invention was demonstrated using embodiment, this invention is not limited to this embodiment at all, Various deformation|transformation and substitution can be added in the range which does not deviate from the summary of this invention.

Claims

1. A vehicle identification system, comprising: A vehicle-mounted laser radar device that detects an object using light or electromagnetic waves close to light and includes a dirt detection unit that calculates a dirt value indicating a degree of dirtiness of the device for each of a plurality of segments obtained by dividing a detection range of the object based on a detection result of the object; as well as The dirt determination device includes a dirt determination unit, which determines whether dirt to be removed is attached to the vehicle-mounted laser radar device when a first condition, a second condition and a third condition are met. The first condition is judged to be true when a first specified time or more has passed since the dirt value exceeded a specified threshold value, the second condition is judged to be true when the difference between the maximum and minimum values ​​of the dirt value within the first specified time is within a specified range, and the third condition is judged to be true when the driving speed of the vehicle equipped with the vehicle-mounted laser radar device exceeds a specified upper limit value and then does not fall below a specified lower limit value for a second specified time.

2. The vehicle identification system according to claim 1, wherein The vehicle-mounted laser radar device further includes a notification unit that notifies the vehicle-mounted laser radar device of the situation when the dirt determination unit determines that the dirt to be removed is attached to the vehicle-mounted laser radar device.

3. A recognition method, wherein A vehicle-mounted LiDAR device that detects objects using light or electromagnetic waves close to light. Based on the detection result of the object, a contamination value indicating the degree of contamination of the device is calculated for each of the multiple segments obtained by dividing the detection range of the object, By dirt determination device When the first, second and third conditions are met, it is determined that dirt that should be removed is attached to the vehicle-mounted laser radar device. The first condition is determined to be true when a first specified time has passed since the dirt value exceeded a specified threshold value. The second condition is determined to be true when the difference between the maximum and minimum values ​​of the dirt value within the first specified time is within a specified range. The third condition is determined to be true when the driving speed of the vehicle equipped with the vehicle-mounted laser radar device exceeds a specified upper limit and then does not fall below a specified lower limit for a second specified time.

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