Vehicle management system and vehicle inspection method

Abstract

The present disclosure relates to a vehicle management system and a vehicle inspection method. The vehicle inspection method includes a first transmission process and a second transmission process, and a first determination process and a second determination process. In the first transmission process, a vehicle transmits, to a server, a first state detected by a first sensor mounted on the vehicle in autonomous driving. In the first determination process, the server determines, using the first state received from the vehicle, whether the vehicle is good or bad for a first inspection item. In the second determination process, the vehicle determines, using a second state detected by a second sensor mounted on the vehicle in autonomous driving, whether the vehicle is good or bad for a second inspection item. In the second transmission process, in a case where the second inspection item is determined to be bad, the vehicle transmits, to the server, a determination result of the second inspection item.

Description

Technical Field

[0001] This disclosure relates to vehicle management systems and vehicle inspection methods. Background Technology

[0002] Japanese Patent Application Publication No. 2019-131187 discloses a technology for vehicle diagnostics using cloud services via the Internet. In the technology described in Japanese Patent Application Publication No. 2019-131187, if an anomaly is diagnosed through a primary diagnostic test on the vehicle and the driver can perceive the anomaly, the vehicle requests a secondary diagnostic test related to the anomaly from the cloud service provider's server. At this time, the vehicle sends data for the secondary diagnostic test to the server. In the technology described in Japanese Patent Application Publication No. 2019-131187, if the vehicle anomaly is minor (to a degree that the driver cannot perceive or that does not immediately affect the vehicle's operation), a secondary diagnostic test is not performed.

[0003] In recent years, MaaS (Mobility as a Service) has received much attention. To improve the convenience of MaaS, technologies such as car sharing and autonomous driving have been proposed.

[0004] The plan is to manage multiple autonomous vehicles via a server, enabling the provision of autonomous vehicles based on user requests. The provider of the autonomous vehicles is required to perform appropriate routine maintenance. To detect anomalies in the autonomous vehicles as early as possible, it is desirable to perform vehicle checks during autonomous driving.

[0005] To ensure the server accurately monitors vehicle status, it's desirable for vehicle status information detected within the vehicle to be sent to the server sequentially. Even minor anomalies should be reported to the server. However, as the amount of information sent from managed vehicles to the server increases, the server's processing load (e.g., the computational demands of information processing) increases, or communication costs rise. Summary of the Invention

[0006] This disclosure was made to address the aforementioned problems, with the aim of reducing the load on servers managing autonomous vehicles and ensuring proper maintenance of autonomous vehicles.

[0007] The vehicle management system of the first aspect of this disclosure includes a vehicle and a server. The server has a first inspection device that performs a first check to determine the quality of a first inspection item. The vehicle has a control device, a second inspection device, a first sensor, a second sensor, and a communication device. The control device is configured to perform control for enabling the vehicle to drive autonomously. The second inspection device is configured to perform a second check to determine the quality of a second inspection item different from the first inspection item. The first sensor is configured to detect a first state corresponding to the first inspection item. The second sensor is configured to detect a second state corresponding to the second inspection item. The communication device is configured to sequentially send to the server the first states detected by the first sensor during the vehicle's autonomous driving. The first inspection device is configured to perform a first check on the vehicle using the first states received sequentially from the vehicle. The second inspection device performs a second check using the second states detected by the second sensor during the vehicle's autonomous driving. Then, if the second check determines the vehicle is defective, the communication device sends the result of the second check to the server.

[0008] Based on the above configuration, the first state corresponding to the first inspection item is sequentially sent from the vehicle to the server. Therefore, the server can accurately grasp the state of the vehicle in autonomous driving (the first state detected by the first sensor) and can use the first states sequentially received from the vehicle in autonomous driving to determine the quality of the first inspection item.

[0009] Furthermore, based on the above configuration, the quality of the second inspection item is determined within the vehicle. The server can receive a notification from the vehicle indicating an anomaly related to the second inspection item if an anomaly occurs in the vehicle during autonomous driving. During the period when the second inspection is determined to be good, the server does not receive the result of the second inspection, thereby confirming that no anomalies related to the second inspection item have occurred in the vehicle during autonomous driving. During the period when the second inspection is determined to be good, neither the second status nor the result of the second inspection is sent from the vehicle to the server, thereby reducing the amount of information sent from the vehicle to the server. This reduces the server's load.

[0010] Based on the above configuration, the server receives information about a vehicle and the corresponding inspection items from the vehicle, thus enabling the server to easily and accurately grasp the status of the vehicle in autonomous driving. This allows for appropriate maintenance of the autonomous vehicle.

[0011] It should be noted that the vehicle's communication device can send vehicle-related information along with the vehicle's identification information (vehicle ID) to the server. The vehicle's control and second inspection devices can be implemented using a single computer or a separate computer. The vehicle's control system can consist of a single computer or include multiple computers.

[0012] In the aforementioned vehicle management system, the second inspection item may require higher real-time performance compared to the first inspection item.

[0013] Regarding inspection items, the shorter the required monitoring and judgment intervals, the higher the required real-time performance. In a vehicle management system with the above-described configuration, the second inspection item is monitored (detection of the second state) and judged within the vehicle, thus facilitating monitoring and judgment with short cycles. As mentioned above, by designating inspection items with low real-time performance requirements as the first inspection item and those with high real-time performance requirements as the second inspection item, it is easy to meet the requirements of each inspection item.

[0014] The first inspection item may include checking for any abnormalities in parts caused by years of deterioration. The second inspection item may include checking for any tire leaks.

[0015] There is a tendency to require highly sophisticated analysis to accurately determine whether anomalies in parts caused by years of deterioration are present. On the other hand, the presence or absence of tire leaks (e.g., slow leaks) can be easily determined based on tire pressure changes, even without sophisticated analysis. Generally, it is easier to improve the information processing capabilities of servers located outside the vehicle than to improve the information processing capabilities of the computer installed in the vehicle. Computers installed in vehicles are constrained by design in terms of size and cost. Therefore, servers are easier to analyze than vehicles. As described above, by designating inspection items requiring highly sophisticated analysis as the first inspection item and those not requiring highly sophisticated analysis as the second inspection item, it is easier to accurately determine each inspection item.

[0016] The first state may include at least one of the following: vehicle weight, vehicle speed, number of times the vehicle has stopped, number of times the vehicle has braked suddenly, vehicle position, and state of charge (SOC) of the vehicle's electrical storage device. The second state may include tire pressure.

[0017] Based on the above configuration, the server can easily and accurately determine whether an abnormality caused by years of deterioration exists in at least one of the propulsion device (e.g., drive motor), braking device, suspension, and energy storage device (e.g., drive battery) installed in the vehicle. Furthermore, based on the above configuration, the vehicle can easily and accurately determine whether tire leakage (e.g., slow leakage) exists based on tire pressure.

[0018] The communication device can be configured to send the first state detected by the first sensor to the server when the deviation between the first state detected by the first sensor and the most recently sent first state exceeds a predetermined level during autonomous driving of the vehicle. Alternatively, the communication device can be configured not to send the first state detected by the first sensor to the server if the deviation does not exceed the predetermined level.

[0019] Based on the above configuration, if the current first state detected by the first sensor in the vehicle has not changed significantly compared to the most recent first state sent from the vehicle to the server (i.e., the latest first state received by the server from the vehicle), the current first state detected by the first sensor is not sent to the server. The server does not receive the detection value from the first sensor from the vehicle, thereby ensuring that the first state has not changed significantly. Since the detection value from the first sensor is not sent from the vehicle to the server, the amount of information sent from the vehicle to the server is reduced. This reduces the server's load.

[0020] The vehicle management system of the second aspect of this disclosure includes: a first vehicle, a second vehicle, and a server. The server has a first inspection device that performs a first inspection to determine the quality of a first inspection item. The first vehicle and the second vehicle each have a control device, a second inspection device, a first sensor, a second sensor, and a communication device, as shown below. The control device is configured to perform control for enabling the vehicle to drive autonomously. The second inspection device is configured to perform a second inspection to determine the quality of a second inspection item different from the first inspection item. The first sensor is configured to detect a first state corresponding to the first inspection item. The second sensor is configured to detect a second state corresponding to the second inspection item. The communication device of the first vehicle is configured to sequentially send the first states detected by the first sensor during the autonomous driving of the first vehicle to the server. The first inspection device is configured to perform a first inspection on the first vehicle and the second vehicle respectively using the first states sequentially received from the vehicles. The second inspection devices of the first vehicle and the second vehicle each perform a second inspection using the second states detected by the second sensor during the autonomous driving of the vehicle, and send the result of the second inspection to the server if the second inspection determines that the vehicle is defective.

[0021] In the above configuration, a first check related to the second vehicle is performed using a first status (detection value obtained by the first sensor of the first vehicle) sequentially sent from the first vehicle to the server. The detection value obtained by the first sensor of the second vehicle is not sent from the second vehicle to the server, thereby reducing the amount of information sent from the second vehicle to the server. According to this configuration, the amount of information sent from each vehicle to the server can be reduced, and checks on many vehicles can be performed.

[0022] The first and second vehicles described above can operate simultaneously via autonomous driving. Due to this configuration, the conditions (weather conditions, etc.) for autonomous driving in both vehicles are largely the same, and the components of each vehicle tend to deteriorate with similar rates during autonomous driving. Therefore, the server can easily perform a first check related to the second vehicle using the detection values ​​obtained from the first sensor of the first vehicle.

[0023] The first and second vehicles mentioned above can be of the same model. Due to this configuration, the onboard parts in both vehicles are largely interchangeable, and during autonomous driving, these parts tend to deteriorate with similar rates. Therefore, the server can easily perform a first check related to the second vehicle using the detection values ​​obtained from the first sensor in the first vehicle.

[0024] The vehicle inspection method of the third aspect of this disclosure includes a first sending process and a second sending process, as well as a first determination process and a second determination process, as shown below.

[0025] In the first transmission process, the vehicle sends a first state detected by a first sensor mounted on the vehicle during autonomous driving to the server. In the first determination process, the server uses the first state received from the vehicle to determine whether a first inspection item is good or bad. In the second determination process, the vehicle uses a second state detected by a second sensor mounted on the vehicle during autonomous driving to determine whether a second inspection item is good or bad. In the second transmission process, if the second inspection item is determined to be bad, the vehicle sends the determination result of the second inspection item to the server.

[0026] The vehicle inspection method described above can also reduce the load on the server that manages autonomous vehicles, just like the vehicle management system described above, and allow for proper maintenance of autonomous vehicles.

[0027] According to this disclosure, the load on servers managing autonomous vehicles can be reduced, and the maintenance of autonomous vehicles can be performed appropriately. Attached Figure Description

[0028] Hereinafter, with reference to the accompanying drawings, the features, advantages, and technical and industrial significance of exemplary embodiments of the present invention will be described, wherein the same reference numerals denote the same elements, wherein:

[0029] Figure 1 This is a diagram illustrating the schematic configuration of a vehicle according to an embodiment of the present disclosure.

[0030] Figure 2 It means Figure 1 The diagram shows the detailed components of the vehicle.

[0031] Figure 3 This is a flowchart illustrating the processing procedure of automatic driving control according to an embodiment of the present disclosure.

[0032] Figure 4 This is a table summarizing the first and second checks of the embodiments of this disclosure.

[0033] Figure 5 This is a diagram illustrating the first and second sensors provided in a vehicle according to an embodiment of the present disclosure.

[0034] Figure 6 This is a diagram used to illustrate the configuration of a server in an embodiment of this disclosure.

[0035] Figure 7 This is a flowchart illustrating the process involving a first check performed by the control device of the vehicle according to an embodiment of the present disclosure.

[0036] Figure 8 This is a flowchart illustrating the process involving a second check performed by the control device of the vehicle according to an embodiment of the present disclosure.

[0037] Figure 9 This is a flowchart illustrating the process involving the first check performed by the server of an embodiment of this disclosure.

[0038] Figure 10 This is a flowchart illustrating the process involving the second check performed by the server of an embodiment of this disclosure.

[0039] Figure 11 This is a flowchart illustrating a variation of the first check, representing the request processing performed by the server.

[0040] Figure 12 This is a flowchart illustrating a variation of the first check, showing the transmission process performed by the vehicle.

[0041] Figure 13 This is a flowchart illustrating the decision-making process performed by the server for a variant of the first check. Detailed Implementation

[0042] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. It should be noted that the same or equivalent reference numerals are used to label the same parts in the drawings, and their descriptions will not be repeated.

[0043] Figure 1 This is a diagram illustrating a schematic configuration of a vehicle according to an embodiment of the present disclosure. (See also...) Figure 1 Vehicle 1 is equipped with an autonomous driving kit (hereinafter referred to as "ADK" 200) and a vehicle platform (hereinafter referred to as "VP" 2).

[0044] VP2 includes the control system of the base vehicle 100 and the vehicle control interface box (hereinafter referred to as "VCIB"). The VCIB 111 can communicate with the ADK200 via an in-vehicle network such as CAN (Controller Area Network). It should be noted that although in... Figure 1 The base vehicle 100 and ADK200 are shown in a separate position, but ADK200 is actually mounted on the base vehicle 100. In this embodiment, ADK200 is mounted on the roof of the base vehicle 100. However, the mounting position of ADK200 can be appropriately changed.

[0045] The base vehicle 100 is, for example, a commercially available xEV (electric vehicle). An xEV is a vehicle that uses electricity as its power source, either wholly or partially. In this embodiment, a BEV (battery electric vehicle) is used as the base vehicle 100. However, it is not limited to this; the base vehicle 100 can also be an xEV other than a BEV (HEV, PHEV, FCEV, etc.). The base vehicle 100 has, for example, four wheels. However, it is not limited to this; the base vehicle 100 can also have three wheels, or even five or more wheels.

[0046] In addition to the integrated control manager 115, the control system of the base vehicle 100 includes various systems and sensors for controlling the base vehicle 100. The integrated control manager 115 performs integrated control of various systems related to the operation of the base vehicle 100 based on signals (sensor detection signals) from the various sensors included in the base vehicle 100.

[0047] In this embodiment, the integrated control manager 115 includes a control device 150. The control device 150 includes a processor 151, RAM (Random Access Memory) 152, and a storage device 153. The processor 151 may be, for example, a CPU (Central Processing Unit). The RAM 152 functions as a temporary working memory for storing data processed by the processor 151. The storage device 153 is configured to store stored information. The storage device 153 may include, for example, ROM (Read Only Memory) and rewritable non-volatile memory. In addition to the program, the storage device 153 stores information used in the program (e.g., mapping diagrams, formulas, and various parameters). In this embodiment, the processor 151 executes the program stored in the storage device 153 to perform various vehicle controls (e.g., automatic driving control according to instructions from ADK200) and the subsequent processing involving checks (see below). Figure 7 and Figure 8 However, these processes can also be performed using dedicated hardware (electronic circuits) instead of software. It should be noted that the number of processors in the control device 150 is arbitrary, and processors can be prepared for each specified control.

[0048] The base vehicle 100 includes a braking system 121, a steering system 122, a powertrain system 123, an active safety system 125, and a body system 126. These systems are controlled by a unified control manager 115. In this embodiment, each system has a computer. Furthermore, the computer of each system communicates with the unified control manager 115 via an in-vehicle network (e.g., CAN). Hereinafter, the computer of each system will be referred to as an "ECU (Electronic Control Unit)".

[0049] The braking system 121 includes braking devices for each wheel of the base vehicle 100 and an ECU for controlling the braking devices. In this embodiment, a hydraulic disc brake device is used as the braking device. The base vehicle 100 is equipped with wheel speed sensors 127A and 127B. Wheel speed sensor 127A is located on the front wheels of the base vehicle 100 and detects the rotational speed of the front wheels. Wheel speed sensor 127B is located on the rear wheels of the base vehicle 100 and detects the rotational speed of the rear wheels. The ECU of the braking system 121 outputs the rotational direction and rotational speed of each wheel detected by the wheel speed sensors 127A and 127B to the integrated control manager 115.

[0050] The steering system 122 includes a steering mechanism of the base vehicle 100 and an ECU that controls the steering mechanism. The steering mechanism may include, for example, a rack and pinion EPS (Electric Power Steering) system capable of adjusting the steering angle via an actuator. The base vehicle 100 includes a pinion angle sensor 128. The pinion angle sensor 128 detects the rotation angle (pinion angle) of the pinion gear connected to the rotation shaft of the actuator constituting the steering mechanism. The ECU of the steering system 122 outputs the pinion angle detected by the pinion angle sensor 128 to the integrated control manager 115.

[0051] The powertrain 123 includes: an EPB (Electric Parking Brake) located on at least one of the wheels of the base vehicle 100; a P-Lock device located on the transmission of the base vehicle 100; a shift mechanism configured to select a gear; a drive source for the base vehicle 100; and an ECU for controlling the various devices included in the powertrain 123. The EPB is separate from the aforementioned braking device and uses an electric actuator to fix the wheels. The P-Lock device, for example, uses a parking lock pawl that can be driven by an actuator to fix the rotational position of the transmission output shaft. Details will be described later, but in this embodiment, a motor supplied with power from a battery is used as the drive source for the base vehicle 100 (see [reference]). Figure 5 The ECU of the powertrain system 123 outputs to the integrated control manager 115 the fixed presence or absence of the EPB and P-Lock devices, the gear selected by the shifting device, and the respective states of the battery and motor.

[0052] The active safety system 125 includes an ECU that determines the likelihood of a collision with the vehicle 1 while it is in motion. The base vehicle 100 is equipped with a camera 129A and radar sensors 129B and 129C that detect the surrounding conditions, including those in front of and behind the vehicle 1. The ECU of the active safety system 125 uses signals received from the camera 129A and radar sensors 129B and 129C to determine whether a collision is possible. If the active safety system 125 determines that a collision is possible, the integrated control manager 115 outputs a braking command to the braking system 121 to increase the braking force of the vehicle 1. The base vehicle 100 of this embodiment is equipped with the active safety system 125 from the outset (at the factory). However, it is not limited to this; an active safety system that can be added to the base vehicle may also be used.

[0053] The body system 126 includes body system components (such as a turn indicator, horn, and wipers) and an ECU that controls these components. In manual mode, the ECU of the body system 126 controls the body system components according to user operation; in autonomous mode, it controls the body system components according to instructions received from the ADK200 via the VCIB111 and the integrated control manager 115.

[0054] Vehicle 1 is configured for autonomous driving. VCIB111 functions as the vehicle control interface. When Vehicle 1 is driving autonomously, the integrated control manager 115 and ADK200 exchange signals via VCIB111, and the integrated control manager 115 executes driving control (i.e., autonomous driving control) in Autonomous Mode according to instructions from ADK200. It should be noted that ADK200 can also be removed from the base vehicle 100. Even with ADK200 removed, the base vehicle 100 can still be driven independently by the user. When driving independently, the control system of the base vehicle 100 executes driving control in Manual Mode (i.e., driving control corresponding to user operation).

[0055] In this embodiment, ADK200 exchanges signals with VCIB111 according to an API (Application Program Interface) that defines the various signals used in communication. ADK200 is configured to process the various signals defined by the aforementioned API. For example, ADK200 creates a driving plan for vehicle 1 and, according to the aforementioned API, outputs various commands to VCIB111 requesting control to make vehicle 1 drive according to the created driving plan. Hereinafter, each of the various commands output from ADK200 to VCIB111 will be referred to as an "API command". Furthermore, ADK200 receives various signals representing the state of the base vehicle 100 from VCIB111 according to the aforementioned API and reflects the received state of the base vehicle 100 in the creation of the driving plan. Hereinafter, each of the various signals received by ADK200 from VCIB111 will be referred to as an "API signal". Both API commands and API signals are equivalent to signals defined by the aforementioned API. A detailed description of the configuration of ADK200 will follow (see [link to documentation]). Figure 2 ).

[0056] The VCIB111 receives various API commands from the ADK200. When an API command is received from the ADK200, the VCIB111 converts the API command into a signal form that can be processed by the integrated control manager 115. Hereinafter, the API command converted into a signal form that can be processed by the integrated control manager 115 will be referred to as a "control command". When an API command is received from the ADK200, the VCIB111 integrated control manager 115 outputs the control command corresponding to that API command.

[0057] The control unit 150 of the integrated control manager 115 sends various signals (e.g., sensor signals or status signals) indicating the state of the base vehicle 100 detected in the control system of the base vehicle 100 to the ADK 200 via the VCIB 111. The VCIB 111 sequentially receives signals indicating the state of the base vehicle 100 from the integrated control manager 115. The VCIB 111 determines the value of the API signal based on the signals received from the integrated control manager 115. Furthermore, the VCIB 111 converts the signals received from the integrated control manager 115 into API signal form as needed. Then, the VCIB 111 outputs the obtained API signal to the ADK 200. The VCIB 111 sequentially outputs API signals indicating the state of the base vehicle 100 to the ADK 200 in real time.

[0058] In this embodiment, signals with low universality, defined by the automobile manufacturer, are exchanged between the integrated control manager 115 and VCIB 111, while signals with higher universality (e.g., signals defined through a publicly available API) are exchanged between ADK 200 and VCIB 111. VCIB 111 enables the integrated control manager 115 to control the vehicle according to instructions from ADK 200 by performing signal conversion between ADK 200 and the integrated control manager 115. However, the function of VCIB 111 is not limited to performing the aforementioned signal conversion. For example, VCIB 111 can also perform a predetermined judgment and send a signal based on the judgment result (e.g., a notification, instruction, or request signal) to at least one of the integrated control manager 115 and ADK 200. A detailed description of the configuration of VCIB 111 will follow (see [link to documentation]). Figure 2 ).

[0059] The base vehicle 100 also includes a communication device 130. The communication device 130 includes various communication I / Fs (interfaces). The control device 150 is configured to communicate with external devices of the vehicle 1 (e.g., the mobile terminal UT and server 500 described later) via the communication device 130. The communication device 130 includes a wireless communication device (e.g., a DCM (Data Communication Module)) capable of accessing a mobile communication network (in-vehicle information service). The communication device 130 communicates with the server 500 via the mobile communication network. The wireless communication device may include communication I / Fs corresponding to 5G (fifth-generation mobile communication system). Furthermore, the communication device 130 includes communication I / Fs for direct communication with the mobile terminal UT located within or around the vehicle. The communication device 130 and the mobile terminal UT can perform short-range communication such as wireless LAN (Local Area Network), NFC (Near Field Communication), or Bluetooth (registered trademark).

[0060] The mobile terminal UT is a terminal carried by the user of vehicle 1. In this embodiment, a smartphone with a touch panel display is used as the mobile terminal UT. However, it is not limited to this; any mobile terminal can be used as the mobile terminal UT, such as a laptop computer, tablet computer, wearable device (e.g., smartwatch or smart glasses), or electronic key.

[0061] The aforementioned vehicle 1 can be adopted as one of the components of a MaaS (Mobility as a Service) system. MaaS systems include, for example, MSPF (Mobility Service Platform). MSPF is a unified platform connecting various mobility services (e.g., various mobility services provided by ride-sharing providers, car-sharing providers, insurance companies, car rental providers, taxi providers, etc.). Server 500 is a computer in MSPF that manages and exposes information used for mobility services. Server 500 manages information on various mobility services and provides information (e.g., APIs and information related to cooperation between mobility services) upon requests from providers. Providers of services can utilize the various functionalities provided by MSPF using the APIs exposed on MSPF. For example, the APIs required for the development of ADK are exposed on MSPF.

[0062] Figure 2 This is a diagram showing the detailed configuration of vehicle 1. (Refer to...) Figure 1 and Figure 2ADK200 includes an autonomous driving system (hereinafter referred to as "ADS") 202 for performing autonomous driving of vehicle 1. ADS202 includes a computer 210, an HMI (Human Machine Interface) 230, a recognition sensor 260, a posture sensor 270, and a sensor cleaner 290.

[0063] Computer 210 includes a processor and a storage device for autonomous driving software utilizing APIs, and is configured to execute the autonomous driving software via the processor. The autonomous driving software performs controls related to autonomous driving (see below). Figure 3 The autonomous driving software can be updated sequentially via OTA (Over-The-Air). Computer 210 also includes communication modules 210A and 210B.

[0064] HMI 230 is a device for exchanging information between a user and computer 210. HMI 230 includes input devices and reporting devices. The user can use HMI 230 to give instructions or make requests to computer 210, or change the values ​​of parameters used in autonomous driving software (but only those parameters that are allowed to be changed). HMI 230 may be a touch panel display that functions as both an input device and a reporting device.

[0065] The identification sensor 260 includes various sensors that acquire information (hereinafter also referred to as "environmental information") for identifying the external environment of the vehicle 1. The identification sensor 260 acquires the environmental information of the vehicle 1 and outputs this environmental information to the computer 210. The environmental information is used for autonomous driving control. In this embodiment, the identification sensor 260 includes cameras that capture images of the area around the vehicle 1 (including the front and rear) and obstacle sensors (e.g., millimeter-wave radar and / or lidar) that sense obstacles using electromagnetic waves or sound waves. The computer 210 can, for example, use the environmental information received from the identification sensor 260 to identify people, objects (other vehicles, pillars, guardrails, etc.) and lines on the road (e.g., center lines) that are within the range that can be identified from the vehicle 1. Artificial intelligence (AI) or image processing processors can also be used for identification.

[0066] The attitude sensor 270 acquires information related to the attitude of vehicle 1 (hereinafter also referred to as "attitude information") and outputs this information to computer 210. The attitude sensor 270 includes various sensors that detect the acceleration, angular velocity, and position of vehicle 1. In this embodiment, the attitude sensor 270 includes an IMU (Inertial Measurement Unit) and a GPS (Global Positioning System) sensor. The IMU detects the accelerations of vehicle 1 in the forward, left, right, and up / down directions, and the angular velocities of vehicle 1 in the roll, pitch, and yaw directions. The GPS sensor uses signals received from multiple GPS satellites to detect the position of vehicle 1. In the fields of automobiles and aircraft, techniques for combining IMUs with GPS to measure attitude with high precision are well known. Computer 210 can, for example, utilize such known techniques to measure the attitude of vehicle 1 based on the aforementioned attitude information.

[0067] Sensor cleaner 290 is a device for removing dirt from sensors (such as identification sensor 260) exposed to outside air outside the vehicle. For example, sensor cleaner 290 can be configured to clean camera lenses and obstacle sensor nozzles using cleaning fluid and a wiper.

[0068] In vehicle 1, to improve safety, the prescribed functions (such as braking, steering, and vehicle fixation) are redundant. The control system 102 of the base vehicle 100 has multiple systems that perform equivalent functions. Specifically, the braking system 121 includes braking systems 121A and 121B. The steering system 122 includes steering systems 122A and 122B. The powertrain system 123 includes EPB system 123A and P-Lock system 123B. Each system has an ECU. Even if one of the multiple systems performing equivalent functions malfunctions, the other will still operate normally, thus ensuring that the function functions normally in vehicle 1.

[0069] VCIB111 includes VCIB111A and VCIB111B. Each of VCIB111A and VCIB111B includes a computer. Communication modules 210A and 210B of computer 210 are configured to communicate with the computers of VCIB111A and VCIB111B, respectively. VCIB111A and VCIB111B are connected in a manner that allows them to communicate with each other. Each of VCIB111A and VCIB111B can operate independently; even if one malfunctions, the other will operate normally, thus ensuring the normal operation of VCIB111. Both VCIB111A and VCIB111B are connected to the aforementioned systems via integrated control manager 115. However, as... Figure 2As shown, the connection destinations differ in parts of VCIB111A and VCIB111B.

[0070] In this embodiment, the function of accelerating vehicle 1 is not redundant. The powertrain 123 includes a propulsion system 123C as a system for accelerating vehicle 1.

[0071] Vehicle 1 is configured to switch between autonomous and manual modes. The API signals received by ADK200 from VCIB111 include a signal indicating whether Vehicle 1 is in autonomous or manual mode (hereinafter referred to as "autonomous mode"). The user can select either autonomous or manual mode via a designated input device (e.g., HMI230 or mobile terminal UT). When the user selects a driving mode, Vehicle 1 enters the selected driving mode, and the selection result is reflected in the autonomous mode. However, if Vehicle 1 is not in a state capable of autonomous driving, it will not transition to autonomous mode even if the user selects it. Switching between driving modes of Vehicle 1 can be performed by the integrated control manager 115. The integrated control manager 115 can also switch between autonomous and manual modes based on the status of Vehicle 1.

[0072] When vehicle 1 is in autonomous mode, computer 210 obtains the status of vehicle 1 from VP2 and sets the next action of vehicle 1 (such as acceleration, deceleration, and turning). Then, computer 210 outputs various instructions to implement the set next action of vehicle 1. By executing API software (i.e., autonomous driving software utilizing API) through computer 210, instructions related to autonomous driving control are sent from ADK200 to integrated control manager 115 via VCIB111.

[0073] Figure 3 This is a flowchart illustrating the processes performed by ADK200 in the autonomous driving control of this embodiment. The processes shown in this flowchart are repeatedly executed at a cycle corresponding to the API (API cycle) when vehicle 1 is in autonomous mode. When the driving mode of vehicle 1 is switched from manual mode to autonomous mode, a start signal indicating the start of autonomous driving, along with vehicle 1's identification information, is sent from vehicle 1 (communication device 130) to server 500, and the following description begins. Figure 3 The flowchart illustrates a series of processes. Hereafter, each step in the flowchart will be simply referred to as "S".

[0074] Reference Figure 1 , Figure 2 as well as Figure 3In S101, computer 210 acquires current vehicle 1 information. For example, computer 210 acquires environmental and posture information of vehicle 1 from recognition sensor 260 and posture sensor 270. Furthermore, computer 210 acquires API signals. In this embodiment, when vehicle 1 is in either autonomous or manual mode, API signals representing the state of vehicle 1 are sequentially output from VCIB 111 to ADK 200 in real time. To improve the accuracy of autonomous driving control, the state of vehicle 1 can also be sequentially sent from integrated control manager 115 to ADK 200 in autonomous mode at a shorter cycle than in manual mode. The API signals acquired by computer 210 include, in addition to the aforementioned autonomous state, signals representing the rotation direction and speed of each wheel detected by wheel speed sensors 127A and 127B.

[0075] In S102, computer 210 creates a driving plan based on the information about vehicle 1 obtained in S101. For example, computer 210 calculates the behavior of vehicle 1 (e.g., the posture of vehicle 1) and creates a driving plan suitable for the state of vehicle 1 and the external environment. The driving plan is data representing the behavior of vehicle 1 within a specified period. If a driving plan already exists, it can also be modified in S102.

[0076] In S103, computer 210 extracts controllable physical quantities (acceleration, tire angle, etc.) from the driving plan created in S102. In S104, computer 210 divides the physical quantities extracted in S103 into segments according to each API cycle. In S105, computer 210 uses the physical quantities segmented in S104 to execute the API software. Thus, through the execution of the API software, API commands (propulsion direction command, propulsion command, braking command, vehicle fixation command, etc.) requesting control of the physical quantities according to the driving plan are sent from ADK200 to VCIB111. VCIB111 sends control commands corresponding to the received API commands to the integrated control manager 115, and the integrated control manager 115 performs automatic driving control of vehicle 1 according to the control commands. The state of vehicle 1 during automatic driving is sequentially recorded in the storage device of computer 210.

[0077] In the next step, S106, computer 210 determines whether vehicle 1 is in autonomous mode. During the period of autonomous mode ("YES" in S106), automatic driving of vehicle 1 is performed by repeatedly executing the processes described in S101 to S105. On the other hand, when vehicle 1 enters manual mode ("NO" in S106), in S107, after sending a termination signal indicating the end of automatic driving along with vehicle 1's identification information from vehicle 1 (communication device 130) to server 500, Figure 3 The series of processes shown has ended. In this embodiment, computer 210, VCIB 111, and integrated control manager 115 cooperate to perform control for enabling vehicle 1 to drive autonomously. Computer 210, VCIB 111 (more specifically, the computer included in VCIB 111), and integrated control manager 115 (more specifically, control device 150) are each an example of the "control device" of this disclosure. In this embodiment, it is assumed that autonomous driving of vehicle 1 is performed when vehicle 1 is occupied. However, it is not limited to this; it can also be configured to perform autonomous driving of vehicle 1 when vehicle 1 is unoccupied. Autonomous driving control is not limited to... Figure 3 The control shown can also be other controls (known automatic driving controls).

[0078] In this embodiment, server 500 performs a first check to determine whether a first inspection item is good or bad. Furthermore, control device 150 mounted on vehicle 1 performs a second check to determine whether a second inspection item, different from the first inspection item, is good or bad. In server 500, an example of the "first inspection device" of this disclosure is implemented by a processor (processor 501 described later) and a program executed by the processor. Furthermore, in control device 150, an example of the "second inspection device" of this disclosure is implemented by a processor 151 and a program executed by the processor 151.

[0079] Figure 4 This is a table summarizing the first and second checks in this embodiment. (See reference...) Figure 4 Regarding the first and second checks in this embodiment, the second check requires higher real-time performance compared to the first check item. That is, the second check requires shorter monitoring and judgment intervals compared to the first check item. Specifically, the first check item is to confirm the presence or absence of abnormalities in parts caused by years of deterioration. The second check item is to confirm the presence or absence of tire leaks.

[0080] In this embodiment, server 500 performs the first inspection based on a first state corresponding to the first inspection item. Details will be described later, but the first state is detected by the first sensor of vehicle 1 during autonomous driving and is sequentially sent from vehicle 1 to server 500. Server 500 performs the inspection of vehicle 1 remotely. In the vehicle inspection method of this embodiment, the first state includes the weight of vehicle 1, the speed of vehicle 1, the number of times vehicle 1 stops, the number of times vehicle 1 brakes suddenly, the position of vehicle 1, and the battery storage device mounted on vehicle 1 (described later). Figure 5 The state of charge (SOC) of the battery 160 shown is described below. The relationship between the above first state and the annual degradation of various vehicle components (first inspection item) will be described later.

[0081] In this embodiment, the control device 150 mounted on vehicle 1 performs the second inspection based on a second state corresponding to the second inspection item. Details will be described later, but the second state is detected by a second sensor provided by vehicle 1 during autonomous driving. In this embodiment, tire pressure is used as the second state. When a tire leaks air, the tire pressure drops. In the case of a slow leak, the tire pressure gradually decreases. The control device 150 can determine whether a tire leak has occurred based on the change in tire pressure.

[0082] Figure 5 This diagram illustrates the first and second sensors provided by vehicle 1. (Refer to...) Figure 1 , Figure 2 as well as Figure 5 The vehicle 1 is equipped with a battery 160 that supplies power to the propulsion system 123C. The battery 160 can be a known vehicle energy storage device (e.g., a liquid secondary battery, a solid-state secondary battery, or a battery pack). Examples of vehicle secondary batteries include lithium-ion batteries and nickel-metal hydride batteries.

[0083] A monitoring module 160a is provided in the battery 160. The monitoring module 160a includes various sensors that detect the state of the battery 160 (e.g., voltage, current, and temperature) and outputs the detection results to the integrated control manager 115. The monitoring module 160a may also be a BMS (Battery Management System) that has SOC (State of Charge) estimation function in addition to the above-mentioned sensor functions. The control device 150 can obtain the state of the battery 160 (e.g., temperature, current, voltage, and SOC) based on the output of the monitoring module 160a. SOC represents the remaining capacity, for example, expressed as 0% to 100% of the current capacity relative to the capacity of a fully charged state.

[0084] Vehicle 1 also includes a weight sensor 170a for detecting the weight of vehicle 1. The weight of vehicle 1 detected by weight sensor 170a is the total weight obtained by adding the weight of the vehicle body, the weight of the people riding in vehicle 1, and the weight of the items loaded in vehicle 1. In this embodiment, a load sensor mounted on the suspension 170 of the base vehicle 100 is used as weight sensor 170a. However, it is not limited to this; instead of load sensor, pressure sensors provided in each seat of the base vehicle 100 may be used as weight sensor 170a, or pressure sensors provided in each seat of the base vehicle 100 may be used in addition to load sensor. The weight of vehicle 1 detected by weight sensor 170a is output to integrated control manager 115.

[0085] The propulsion system 123C includes an MG (Motor Generator) 20, an ECU 21, and a PCU (Power Control Unit) 22. The propulsion system 123C uses electricity stored in the battery 160 to generate the driving force for the vehicle 1. The MG 20 is, for example, a three-phase AC motor generator. The PCU 22 includes, for example, an inverter, a converter, and a relay (hereinafter referred to as "SMR (System Main Relay)"). The PCU 22 is controlled by the ECU 21. The SMR is configured to switch the connection / disconnection of the circuit from the battery 160 to the MG 20. The SMR is in the closed state (connected state) when the vehicle 1 is in motion.

[0086] MG20 is driven by PCU22, causing the drive wheels W of vehicle 1 to rotate. Furthermore, MG20 regenerates electricity and supplies the generated power to battery 160. PCU22 uses the power supplied from battery 160 to drive MG20. The number of driving motors (MG20) in vehicle 1 is arbitrary; it can be one, two, or more than three. The driving motors can be in-wheel motors. Figure 5 Only one drive wheel W is schematically shown, but the number of drive wheels W and the drive method in vehicle 1 are arbitrary. The drive method of vehicle 1 can be any of front-wheel drive, rear-wheel drive, or four-wheel drive.

[0087] Each wheel (including the drive wheel W) of the vehicle 1 is equipped with: a tire pressure sensor 20b for detecting the tire pressure; a braking device 180, included in the braking system 121; and a brake sensor 180a for detecting the braking force applied to the wheel by the braking device 180. The tire pressure sensor 20b may be a TPMS (Tire Pressure Monitoring System) that monitors both tire pressure and tire temperature. The brake sensor 180a may be a hydraulic sensor that detects the hydraulic pressure applied to the brake pads (or wheel cylinders). The tire pressure and braking force (e.g., the hydraulic pressure corresponding to the braking force) of each wheel detected by the four tire pressure sensors 20b and the four brake sensors 180a are output to the integrated control manager 115.

[0088] In this embodiment, wheel speed sensors 127A and 127B ( Figure 1 ), attitude sensor 270 ( Figure 2 ), monitoring module 160a ( Figure 5 ), weight sensor 170a ( Figure 5 ) and brake sensor 180a ( Figure 5 Each of these functions as a first sensor. The communication device 130 sequentially sends the first state detected by the first sensor during the autonomous driving of vehicle 1 to the server 500.

[0089] In this embodiment, the four pressure sensors 20b function as second sensors. The control device 150 performs a second check using the second state (tire pressure) detected by the second sensors (pressure sensors 20b) during the autonomous driving of the vehicle 1. Then, if the second check determines that the vehicle is in poor condition, the communication device 130 sends a signal indicating the result of the second check to the server 500.

[0090] Figure 6 This diagram illustrates the configuration of server 500. (Refer to...) Figure 1 , Figure 2 as well as Figure 6 The server 500 includes a processor 501, RAM 502, and a storage device 503. The storage device 503 is configured to store information. In addition to the program, the storage device 503 also stores information used in the program (e.g., mappings, formulas, and various parameters). In this embodiment, the processor 501 executes the program stored in the storage device 503 to perform the checks described later (see [reference]). Figure 9 and Figure 10 However, such processing can also be performed without software, but through dedicated hardware (electronic circuits).

[0091] The storage device 503 also stores an estimation algorithm E. The estimation algorithm E defines the relationship between specified input information and specified output information. When specified input information is input to the estimation algorithm E, the estimation algorithm E outputs specified output information according to the aforementioned relationship.

[0092] In this embodiment, the first state described above, namely the weight of vehicle 1, the speed of vehicle 1, the number of stops of vehicle 1, the number of emergency brakings of vehicle 1, the position of vehicle 1, and the SOC of battery 160, corresponds to the aforementioned input information of estimation algorithm E. The speed of vehicle 1 and the number of stops are detected, for example, by wheel speed sensors 127A and 127B, respectively. Furthermore, the weight of vehicle 1, the number of emergency brakings of vehicle 1, the position of vehicle 1, and the SOC of battery 160 are detected by weight sensor 170a, brake sensor 180a, attitude sensor 270, and monitoring module 160a, respectively.

[0093] In this embodiment, the degradation progress of a specified object part (e.g., part A, part B, part C, part D, ...) mounted on vehicle 1 corresponds to the aforementioned output information of estimation algorithm E. Specifically, when a first state is input to estimation algorithm E, estimation algorithm E outputs the degree of degradation progress of the object part (degradation progress of the object part) caused by vehicle 1 performing autonomous driving in that first state.

[0094] In this embodiment, the MG20 (drive motor), battery 160 (drive battery), suspension 170, and braking device 180 mounted on vehicle 1 are used as target components. Specifically, the greater the weight of vehicle 1 in autonomous driving, the more easily the MG20, suspension 170, and braking device 180 deteriorate. The more times vehicle 1 brakes suddenly (cumulative times), the more easily the suspension 170 and braking device 180 deteriorate. The longer the state of charge (SOC) of battery 160 deviates from the appropriate range, the more easily the battery 160 deteriorates. The more times vehicle 1 stops (cumulative times), the more easily the braking device 180 deteriorates. Furthermore, since vehicle 1 continues to drive and starts after stopping, the more times vehicle 1 stops, the more times vehicle 1 starts, and the more easily the MG20 deteriorates.

[0095] The input information for the estimation algorithm E may also include meteorological information (information on the weather in the area where vehicle 1 is located), traffic information (information on the traffic conditions around vehicle 1), and road surface information (information related to the road surface on which vehicle 1 is traveling) obtained based on the location information of vehicle 1. Examples of meteorological information include temperature and weather (e.g., sunny, cloudy, rainy, or snowy). Examples of traffic information include congestion information. Examples of road surface information include types of road surfaces such as flat, uphill, downhill, and rough roads. The longer the temperature (or road surface temperature) deviates from the appropriate range, the more easily rubber products (e.g., tires) deteriorate. In addition, rubber products may also deteriorate due to sunlight. When vehicle 1 is traveling on a congested road, MG20 and braking system 180 are prone to deterioration. When vehicle 1 is traveling uphill, MG20 is prone to deterioration. When vehicle 1 is traveling downhill, braking system 180 is prone to deterioration. When vehicle 1 is traveling on a rough road, suspension 170 is prone to deterioration.

[0096] In this embodiment, an algorithm based on AI (Artificial Intelligence) is used as the estimation algorithm E. The estimation algorithm E can be a fully learned model that has undergone machine learning using large datasets (e.g., data measured in vehicles with the same technical specifications as vehicle 1). However, it is not limited to this; the estimation algorithm E can also be a rule-based algorithm. The estimation algorithm E can also be, for example, a formula or mapping graph representing the aforementioned relationship (predestination). The estimation algorithm E can be updated sequentially via OTA (Over-The-Air).

[0097] Server 500 manages vehicle-related information (hereinafter also referred to as "vehicle information"). Vehicle information for multiple vehicles is stored in storage device 503 of server 500. Specifically, identification information (vehicle ID) is assigned to each vehicle, and server 500 manages vehicle information differently based on the vehicle ID. Vehicle information includes, for example, vehicle model, technical specifications, and vehicle condition (e.g., whether it is in autonomous driving mode). In this embodiment, vehicle information also includes the degree of degradation of each component. Figure 6 Table T1 in the table represents the vehicle information for each vehicle. In table T1, "V-1" corresponds to the vehicle ID of vehicle 1. Figure 6 The table only shows vehicle information related to vehicle 1 (V-1) (especially the degree of degradation of each object part), but table T1 shows vehicle information related to all vehicles registered to server 500.

[0098] Server 500 sequentially inputs the first states received from vehicle 1 during autonomous driving into estimation algorithm E, and adds the degradation progress of each object part output from estimation algorithm E to the degradation degree of each object part shown in table T1. The degradation progress of each object part during autonomous driving is estimated by estimation algorithm E and added to the corresponding degradation degree of the object part in table T1. Table T1 is thus updated. Server 500 can obtain the degradation progress of each object part in autonomous driving of vehicle 1 by accumulating the degradation progress of each object part output from estimation algorithm E. It should be noted that the estimation method for the degradation progress of object parts outside of autonomous driving is arbitrary. Server 500, for example, can use a prescribed mapping diagram to estimate the degradation progress of object parts outside of autonomous driving.

[0099] The control device 150 is configured to perform automatic driving of the vehicle 1 during a predetermined period (hereinafter referred to as the "operation period"). During the automatic driving of the vehicle 1, the following actions are performed: Figure 3 The processing shown involves the control unit 150 responding to instructions from ADK200 to various systems of vehicle 1 (e.g., Figure 2 The vehicle 1 is controlled by the braking system 121, steering system 122, powertrain system 123, active safety system 125, and body system 126 shown. The vehicle 1 can also provide prescribed services (e.g., logistics services or passenger transport services) via automatic driving during operation. In this embodiment, the vehicle 1, which provides passenger transport services via automatic driving, travels along a predetermined path within the operating area. However, it is not limited to this; the vehicle 1 can also determine a path based on each request and perform autonomous driving according to the determined path (on-demand path).

[0100] Figure 7 This is a flowchart illustrating the process involving the first check performed by the control unit 150 of vehicle 1. For example, when autonomous driving by vehicle 1 begins, Figure 7 The series of processes shown begins and is repeatedly executed in a predetermined first cycle during autonomous driving. Figure 7 The series of processes shown. For example, when the driving mode of vehicle 1 is switched from manual mode to autonomous mode, control device 150 determines that autonomous driving performed by vehicle 1 has started.

[0101] Reference Figures 1-6 as well as Figure 7 In S11, the control device 150 acquires the current first state detected by the first sensor (more specifically, the weight of vehicle 1, the speed of vehicle 1, the number of stops of vehicle 1, the number of emergency brakings of vehicle 1, the position of vehicle 1, and the SOC of battery 160), and saves the first state in the storage device 153.

[0102] In the next step, S12, the control device 150 determines whether at least one of the first states acquired in S11 has changed significantly since the last transmission (S13 described later). Specifically, the control device 150 determines whether the deviation of the first state detected in S11 from the first state most recently transmitted to the server 500 (hereinafter also referred to as "state change amount") exceeds a predetermined level. The deviation of the previous value (the most recently transmitted value) from the current value (the current sensor detection value) (state change amount) can be expressed, for example, by difference or ratio. The larger the difference (absolute value), the larger the state change amount. Furthermore, the closer the ratio is to 1, the smaller the state change amount. The predetermined level can be arbitrarily set for each first state.

[0103] The control device 150 determines whether the state change exceeds a predetermined level for each first state. If the state change exceeds the predetermined level in at least one first state, it is determined as "yes" in S12. If the state change does not exceed the predetermined level in any first state, it is determined as "no" in S12. In the initial processing routine (the processing routine immediately following the start of automatic driving of vehicle 1), there is no previous value, therefore, it is determined as "yes" in S12.

[0104] If the determination in S12 is "yes", the communication device 130 will send all the signals indicating the first state (hereinafter also referred to as "first check signals") acquired in S11 to the server 500 along with the vehicle ID of vehicle 1 in S13. After that, the process proceeds to S14. On the other hand, if the determination in S12 is "no", the process proceeds to S14 without sending the first check signals (S13).

[0105] In the next step, S14, the control device 150 determines whether the vehicle 1 is in autonomous driving mode. For example, if the vehicle 1 is in autonomous mode, the control device 150 determines that the vehicle 1 is in autonomous driving mode; if the vehicle 1 is in manual mode, the control device 150 determines that the vehicle 1 is not in autonomous driving mode. If the vehicle 1 is in autonomous driving mode ("Yes" in S14), the process returns to the initial step (S11). If the vehicle 1 is not in autonomous driving mode ("No" in S14),... Figure 7 The series of processes shown has ended.

[0106] As described above, vehicle 1 (communication device 130) is configured to sequentially send to server 500 the first state detected by the first sensor during autonomous driving of vehicle 1. In this embodiment, in Figure 7 In S13, the vehicle 1 sends a first check signal, which is detected by the first sensor and indicates the first state, to the server 500 in sequence.

[0107] Figure 8 This is a flowchart illustrating the process involving the second check performed by the control unit 150 of vehicle 1. For example, when autonomous driving by vehicle 1 begins, Figure 8 The series of processes shown begins and is repeated in a prescribed second cycle in autonomous driving. Figure 8 The process is illustrated in the diagram. To improve the real-time performance of the second check, the second cycle (the execution cycle of the second check) can be made shorter than the first cycle (the detection cycle of the first state).

[0108] Reference Figures 1-6 as well as Figure 8 In S21, the control device 150 acquires the current second state (tire pressure) detected by the second sensor (pressure sensor 20b) and saves the second state in the storage device 153. Next, in S22, the control device 150 uses the second state acquired in S21 to perform a second check. In the second check, it is determined whether the second state is abnormal. Specifically, the control device 150 determines whether a tire leak has occurred for each wheel of the vehicle 1 based on the change in tire pressure. A tire leak means that the tire pressure (second state) is abnormal. The control device 150 can also determine that a tire leak has occurred if, in S22, a drop in tire pressure exceeding a reference level is confirmed several times consecutively.

[0109] If at least one wheel of vehicle 1 experiences a tire leak, a negative determination is made through the second check ("Yes" in S22), and the process proceeds to S23. In S23, the communication device 130 sends a signal indicating the result of the second check (abnormal tire pressure) (hereinafter also referred to as the "second check signal") along with the vehicle ID of vehicle 1 to the server 500. After that, the process proceeds to S24. On the other hand, if none of the wheels of vehicle 1 experience a tire leak, a positive determination is made through the second check ("No" in S22), and the process proceeds to S24 without sending the second check signal (S23).

[0110] In the following S24, in conjunction with the above Figure 7 Similarly, in S14, the control device 150 determines whether the vehicle 1 is in autonomous driving mode. Then, if the vehicle 1 is in autonomous driving mode ("Yes" in S24), the process returns to the initial step (S21). If the vehicle 1 is not in autonomous driving mode ("No" in S24), Figure 8 The series of processes shown has ended.

[0111] As described above, the control device 150 performs a second check (S21 and S22) using the second state detected by the second sensor in the autonomous driving of the vehicle 1. If the second check is determined to be bad ("yes" in S22), the communication device 130 sends a second check signal (a signal indicating the result of the second check) to the server 500 (S23).

[0112] Figure 9 This is a flowchart illustrating the process involving the first check executed by server 500. The process shown in this flowchart is repeatedly executed during the autonomous driving of vehicle 1. For example, when server 500 receives a start signal indicating the commencement of autonomous driving of vehicle 1, the following is described... Figure 9 The series of processes shown begins.

[0113] Reference Figures 1-6 as well as Figure 9 In S31, server 500 uses the first state received sequentially from vehicle 1 (i.e., in...). Figure 7 The server 500 uses the first check signal sent in S13 to indicate the first state to estimate the current degradation of each component (MG20, battery 160, suspension 170, braking system 180) of vehicle 1. Specifically, the server 500 uses the estimation algorithm E( Figure 6 Based on the current first state indicated by the most recently received first inspection signal, the server 500 estimates the degradation progress of each object component caused by years of degradation in autonomous driving. The server 500 updates table T1 by adding the estimated degradation progress of each object component to the corresponding degradation degree of the object component in table T1. Figure 6 Then, server 500 retrieves the current degradation level of each object part from the updated table T1. It should be noted that server 500 considers the first state indicated by the most recently received first check signal to be maintained until the next first check signal is received.

[0114] In the following S32, server 500 determines whether any object part in vehicle 1 has experienced an anomaly. Specifically, server 500 determines whether the current degree of degradation exceeds a predetermined threshold for each object part installed in vehicle 1. In this embodiment, the inspection of the vehicle-mounted parts performed in S31 and S32 is equivalent to a first inspection related to vehicle 1. The aforementioned threshold can be arbitrarily set for each object part. If the degradation degree of at least one object part exceeds the threshold, a defect determination is made through the first inspection ("yes" in S32), and the process proceeds to S33. A defect determination through the first inspection means that an anomaly caused by years of degradation has occurred in any object part.

[0115] In S33, server 500 performs a prescribed replacement process on vehicle 1. This prescribed replacement process includes recording, reporting, and sending at least one of the following: the result of a first inspection. The result of the first inspection includes information indicating which parts need to be replaced (i.e., parts whose deterioration exceeds a threshold). Server 500 may also record the result of the first inspection in storage device 503. Server 500 may also send the result of the first inspection to vehicle 1 or a designated terminal, and cause a designated reporting device (e.g., HMI 230 or mobile terminal UT) to perform a reporting process prompting the user of vehicle 1 to replace the parts. Server 500 may also disable the use of vehicle 1 in S33 and perform processing to arrange a replacement vehicle.

[0116] When the process described in S33 is executed, the process proceeds to S34. On the other hand, if the degradation degree of any object part in vehicle 1 does not exceed the threshold, a good judgment is made through the first check ("No" in S32), and the process proceeds to S34 without performing replacement processing (S33). In S34, the server 500 determines whether vehicle 1 is in autonomous driving mode. For example, if the server 500 receives an end signal indicating that autonomous driving of vehicle 1 has ended, it determines that autonomous driving of vehicle 1 has ended. If vehicle 1 is in autonomous driving mode ("Yes" in S34), the process returns to the initial step (S31). If vehicle 1 is not in autonomous driving mode ("No" in S34), Figure 9 The series of processes shown has ended.

[0117] Figure 10 This is a flowchart illustrating the process involving the second check performed by server 500. The process shown in the flowchart begins, for example, each time server 500 receives a second check signal from vehicle 1. Server 500 receiving the second check signal from vehicle 1 signifies that a tire leak (blowout) has occurred in vehicle 1.

[0118] Reference Figures 1-6 as well as Figure 10 In S40, server 500 performs the prescribed replacement process on vehicle 1. In S40, it can also be used in conjunction with... Figure 9 Similarly, S33 performs at least one of the following: recording, reporting, and sending the inspection results (results of the second inspection). The results of the second inspection include information indicating which tires need to be replaced or repaired (tires that have leaked air). When the process in S40 is performed, Figure 10 The series of processes shown has ended.

[0119] As explained above, the vehicle inspection method of this embodiment includes Figures 7-10 The processing shown. In Figure 7In S13 (first transmission process), vehicle 1 sends a signal (first check signal) to server 500 indicating a first state detected by a first sensor mounted on vehicle 1 during autonomous driving. Figure 9 In S32 (first determination process), server 500 uses the first state indicated by the first inspection signal received from vehicle 1 to determine whether the first inspection item of vehicle 1 is good or bad. Figure 8 In S22 (second determination process), vehicle 1 uses the second state detected by the second sensor mounted on vehicle 1 during autonomous driving to determine the quality of the second inspection item. Figure 8 In step S23 (second transmission process), if the second inspection item is determined to be defective, vehicle 1 sends a signal (second inspection signal) indicating the determination result of the second inspection item to server 500. This vehicle inspection method reduces the load on server 500, which manages autonomous vehicles (e.g., vehicle 1), and allows for proper maintenance of the autonomous vehicles.

[0120] The processing involving the first and second checks is not limited to the above-described scheme. For example, the processing involving the first check can also be modified as described below. Hereinafter, using... Figures 11-13 A variation of the first inspection will be explained.

[0121] In the variations described below, server 500 executes... Figure 11 The series of processes shown. Furthermore, the control unit 150 of vehicle 1 executes... Figure 12 The series of processes shown are used to replace Figure 7 The process is shown. Furthermore, server 500 executes... Figure 13 The series of processes shown are used to replace Figure 9 The processing is shown.

[0122] Figure 11 This is a flowchart illustrating a variation of the first check, showing the request processing performed by server 500. The process shown in this flowchart is repeatedly executed at a predetermined interval.

[0123] Reference Figures 1-6 as well as Figure 11 In S51, server 500 retrieves the vehicles in autonomous driving from multiple registered vehicles. In this variant, each vehicle registered to server 500 has... Figure 1 , Figure 2 as well as Figure 5 The configuration shown is configured to be... Figure 3 The process shown is used for autonomous driving. Server 500 can also perform autonomous driving based on the start and end signals described above (see reference). Figure 3 This is used to determine whether each vehicle is in autonomous driving mode.

[0124] In the following S52, server 500 classifies vehicles in autonomous driving based on vehicle model. Vehicles of the same model are classified into the same group. Figure 11 Table T2 shows that among the multiple vehicles registered to server 500, those identified by vehicle IDs "V-12", "V-16", "V-37", ... are all in autonomous driving mode and belong to the same vehicle model (Model A). Additionally, Table T2 shows that among the multiple vehicles registered to server 500, those identified by vehicle IDs "V-6", "V-35", "V-58", ... are all in autonomous driving mode and belong to the same vehicle model (Model B). The vehicle model classification can also be determined according to the automobile manufacturer's product catalog.

[0125] In the following S53, server 500 selects a representative vehicle for each group (by each vehicle model). The method for selecting the representative vehicle is arbitrary. However, once a representative vehicle is selected, it remains unchanged until that representative vehicle ceases autonomous driving. The representative vehicle can be selected randomly or according to prescribed criteria. The vehicle with the smallest vehicle ID in the group can be selected as the representative vehicle. For example, the vehicle identified by vehicle ID "V-12" in group A of vehicle model A, or the vehicle identified by vehicle ID "V-6" in group B of vehicle model B, can be selected as the representative vehicle. Alternatively, vehicles with higher specifications related to sensing in each group can be prioritized as representative vehicles.

[0126] In the next step S54, server 500 sends a signal requesting the first state (hereinafter also referred to as the "request signal") to the representative vehicles of each group. When the processing of S54 is executed, the process returns to the initial step (S51).

[0127] Figure 12 This is a flowchart illustrating a variation of the first check, performed by a representative vehicle. For example, the process shown in this flowchart begins when the representative vehicle receives a request signal from server 500.

[0128] Reference Figures 1-6 as well as Figure 12 The vehicle control unit 150 performs operations in S11A and S13A respectively with... Figure 7 The same process as S11 and S13 involves sending a first check signal indicating a first state, detected by a first sensor mounted on the vehicle representative, along with the vehicle ID of the vehicle representative, to server 500. When the transmission of the first check signal related to the vehicle representative (S13A) is completed, Figure 12 The series of processes shown has ended. Figure 12The series of processes shown is performed solely by the representative vehicle. Due to the aforementioned processes, the representative vehicle's power is consumed; therefore, the vehicle manager can pay incentives (rewards) to the users of the representative vehicles. Each user's incentives can be managed by server 500.

[0129] Figure 13 This is a flowchart illustrating a variation of the decision-making process performed by server 500 regarding the first check. For example, the process shown in this flowchart begins when server 500 receives the first check signal from a representative vehicle.

[0130] Reference Figures 1-6 as well as Figure 13 In S31A, server 500 performs communication with... Figure 9 The same process as S31 is used to estimate the current degree of degradation of each component representing the vehicle (MG20, battery 160, suspension 170, braking system 180). Next, server 500 performs the same process as in S32A. Figure 9 The same process as S32 determines whether any object part in the representative vehicle has an anomaly. In this variation, the on-board part checks performed in S31A and S32A are equivalent to the first check related to the representative vehicle. When a defective determination is made through the first check related to the representative vehicle ("Yes" in S32A), the process proceeds to S33A. If the server 500 determines that a defective part caused by years of deterioration has occurred in all vehicles belonging to the same group as the representative vehicle, it determines that a defective part caused by years of deterioration has occurred.

[0131] In S33A, server 500 performs the prescribed replacement process for all vehicles belonging to the same group as the vehicle representing it. Figure 9 Similarly, in S33, the prescribed replacement procedure can be at least one of the recording, reporting, and sending of the results of the first inspection. However, in S33A, the prescribed replacement procedure is performed not only on the representative vehicle but also on all vehicles belonging to the same group as the representative vehicle. For example, in connection with... Figure 11 If the first inspection related to the representative vehicle of group A (e.g., the vehicle identified by vehicle ID "V-12") is deemed defective ("Yes" in S32A), then in S33A, the prescribed replacement process is performed on each vehicle identified by vehicle IDs "V-12", "V-16", "V-37", ... Figure 13 The series of processes shown has ended.

[0132] On the other hand, if the deterioration degree of any object part in the representative vehicle does not exceed the specified threshold, a good judgment is made through the first inspection ("No" in S32A). Figure 13 The series of processes shown ends without performing a replacement process (S33A).

[0133] As explained above, in the aforementioned variation, the multiple vehicles managed by server 500 each possess a control device 150, a first sensor (e.g., wheel speed sensors 127A, 127B, posture sensor 270, monitoring module 160a, weight sensor 170a, and brake sensor 180a), a second sensor (e.g., air pressure sensor 20b), and a communication device 130 (see reference). Figure 1 , Figure 2 as well as Figure 5 The control unit 150 mounted on the vehicle is configured to perform controls for enabling the vehicle to operate autonomously (see reference). Figure 3 Server 500 selects a representative vehicle (the first vehicle) from multiple vehicles (see reference). Figure 11 The communication device 130 representing the vehicle sequentially sends to the server 500 the first state detected by the first sensor during the autonomous driving of the vehicle (refer to...). Figure 11 and Figure 12 Server 500 uses the first status received sequentially from the representative vehicle to perform a first check on each of the multiple vehicles (first vehicle and second vehicle) belonging to the same group as the representative vehicle (see reference). Figure 13 Vehicles belonging to the same group are of the same model and operate simultaneously via autonomous driving. Server 500 functions as an example of the "first inspection device" of this disclosure.

[0134] In the above configuration, a first check related to a second vehicle (a vehicle other than the representative vehicle belonging to the same group as the representative vehicle) is performed using a first status sequentially sent from the first vehicle (representative vehicle) to the server 500. The amount of information sent from the second vehicle to the server 500 can be reduced by not sending the detection values ​​obtained from the second vehicle's first sensor to the server 500. According to this configuration, the amount of information sent from each vehicle to the server 500 can be reduced, and checks on many vehicles can be performed. It should be noted that the classification (grouping) of each vehicle is not limited to groups based on each vehicle model. The grouping method can be appropriately modified.

[0135] Regarding the second inspection, it is performed in the same manner as in the above-described embodiment in the modified example. That is, the control device 150 of each vehicle performs... Figure 8 The process shown is executed by server 500. Figure 10The processing is shown. The control units 150 of each vehicle, managed by server 500, function as an example of the "second inspection device" of this disclosure. Each vehicle's control unit 150 performs a second inspection using a second state detected by a second sensor during the vehicle's autonomous driving process. If the second inspection determines the condition to be unsatisfactory, it sends the result of the second inspection to server 500 (see reference). Figure 8 ) Execute on a per vehicle basis Figure 8 The process is shown, and a second inspection is performed on each vehicle. With this configuration, in addition to the first inspection described above, a second inspection with high real-time requirements can also be appropriately performed (see [reference]). Figure 4 ).

[0136] The first and second inspection items are not limited to Figure 4 The items shown can be modified as appropriate. For example, as a second inspection item, checking for leaks (e.g., brake fluid leaks) can be used instead of checking for tire leaks, or checking for leaks (e.g., brake fluid leaks) can be used in addition to checking for tire leaks. In vehicles equipped with an engine (internal combustion engine), checking for abnormal engine coolant temperature can also be used as a second inspection item.

[0137] The vehicle configuration is not limited to the configuration described in the above embodiments (see reference). Figure 1 , Figure 2 as well as Figure 5 The base vehicle can also have autonomous driving capabilities without any modifications. The level of autonomous driving can be either fully autonomous (Level 5) or conditionally automated (e.g., Level 4). The vehicle configuration can also be appropriately modified for dedicated driverless operation. For example, a dedicated driverless vehicle may not have components for human operation (such as a steering wheel). The vehicle can be equipped with solar panels and may also have flight capabilities. The vehicle is not limited to cars; it can also be a bus or a truck. The vehicle can also be a privately owned vehicle (POV). The vehicle can also be a multi-purpose vehicle customized according to the user's intended use. The vehicle can also be a mobile shop vehicle, a robotaxi, an automated guided vehicle (AGV), or agricultural machinery. The vehicle can also be a small, driverless or single-passenger BEV (e.g., a micro pallet).

[0138] The embodiments disclosed herein should be considered exemplary in all respects, not limiting. The scope of the technology shown in this disclosure is illustrated by the claims rather than by the description of the embodiments described above, and is intended to include all modifications of the same meaning and scope as the claims.

Claims

1. A vehicle management system, comprising a vehicle and a server, wherein, The server includes a first inspection device, which performs a first inspection to determine whether a first inspection item is good or bad. The vehicle has the following features: The control device performs controls to enable the vehicle to operate via automatic driving. The second inspection device performs a second inspection to determine whether a second inspection item, which is different from the first inspection item, is good or bad. The first sensor detects the first state corresponding to the first inspection item; The second sensor detects the second state corresponding to the second inspection item; as well as communication device, The communication device is configured to sequentially send to the server the first state detected by the first sensor during the vehicle's autonomous driving process. The first inspection device is configured to perform the first inspection on the vehicle using the first state received sequentially from the vehicle. The second inspection device performs the second inspection using the second state detected by the second sensor during the vehicle's autonomous driving process. If the second inspection determines the condition to be unsatisfactory, the communication device sends the result of the second inspection to the server. The first check is performed repeatedly at a predetermined first cycle when autonomous driving by the vehicle begins. Compared to the first inspection item, the second inspection item requires higher real-time performance.

2. The vehicle management system according to claim 1, wherein, The first inspection item includes confirming the presence of any abnormalities caused by years of deterioration in the parts. The second inspection item includes checking for tire leaks.

3. The vehicle management system according to claim 1 or 2, wherein, The first state includes at least one of the following: the vehicle's weight, the vehicle's speed, the number of times the vehicle has stopped, the number of times the vehicle has braked suddenly, the vehicle's position, and the State of Charge (SOC) of the battery storage device mounted on the vehicle. The second state includes tire pressure.

4. The vehicle management system according to claim 1 or 2, wherein, If, during the autonomous driving of the vehicle, the deviation between the first state detected by the first sensor and the most recently transmitted first state exceeds a predetermined level, the communication device transmits the first state detected by the first sensor to the server. If the deviation does not exceed the specified level, the communication device does not send the first state detected by the first sensor to the server.

5. A vehicle management system, comprising a first vehicle, a second vehicle, and a server, wherein, The server includes a first inspection device, which performs a first inspection to determine whether a first inspection item is good or bad. The first vehicle and the second vehicle respectively possess: The control device performs controls to enable the vehicle to operate via automatic driving. The second inspection device performs a second inspection to determine whether a second inspection item, which is different from the first inspection item, is good or bad. The first sensor detects the first state corresponding to the first inspection item; The second sensor detects the second state corresponding to the second inspection item; as well as communication device, The communication device of the first vehicle is configured to sequentially send to the server the first state detected by the first sensor of the first vehicle during autonomous driving of the first vehicle. The first inspection device is configured to perform the first inspection on both the first vehicle and the second vehicle, respectively, using the first state received sequentially from the first vehicle. The second inspection device of each of the first and second vehicles performs the second inspection using the second state detected by the second sensor during the autonomous driving of the vehicle. If the second inspection determines that the vehicle is defective, the device sends the result of the second inspection to the server. The first check is performed repeatedly at a predetermined first cycle when autonomous driving by the vehicle begins. Compared to the first inspection item, the second inspection item requires higher real-time performance.

6. The vehicle management system according to claim 5, wherein, The first vehicle and the second vehicle are both operating via autonomous driving.

7. The vehicle management system according to claim 5 or 6, wherein, The first vehicle and the second vehicle are of the same model.

8. A vehicle inspection method, comprising: The vehicle sends the first state detected by the first sensor mounted on the vehicle during autonomous driving to the server. The server uses the first status received from the vehicle to determine whether the first inspection item of the vehicle is good or bad. The vehicle uses a second state detected by a second sensor mounted on the vehicle in autonomous driving to determine the quality of the second inspection item. as well as If the second inspection item is determined to be defective, the vehicle sends the determination result of the second inspection item to the server. The first check is performed repeatedly at a predetermined first cycle when autonomous driving by the vehicle begins. Compared to the first inspection item, the second inspection item requires higher real-time performance.

9. The vehicle inspection method according to claim 8, wherein, The first inspection item includes confirming the presence of any abnormalities caused by years of deterioration in the parts. The second inspection item includes checking for tire leaks.

10. The vehicle inspection method according to claim 8 or 9, wherein, The first state includes at least one of the following: the vehicle's weight, the vehicle's speed, the number of times the vehicle has stopped, the number of times the vehicle has braked suddenly, the vehicle's position, and the State of Charge (SOC) of the battery storage device mounted on the vehicle. The second state includes tire pressure.

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