Autopilot system, autopilot control method, and non-transitory storage medium

Abstract

The present invention relates to an autonomous driving system, an autonomous driving control method, and a non-transitory storage medium. The autonomous driving system includes: one or more storage devices that store specific location information indicating specific locations where remote support may be required; and one or more processors configured to: set a first target route as a route to a destination, i.e., a target route; determine whether an abnormality has occurred in a remote support system configured to provide remote support to an autonomous driving vehicle that is an object of remote support; in the case where an abnormality of the remote support system is detected, search for an alternative route based on the specific location information, the alternative route being a route to the destination in which the number of specific locations through which the autonomous driving vehicle passes is smaller than the number of specific locations through which the vehicle passes in the first target route; in the case where an alternative route is found, change the target route from the first target route to the alternative route; and control the autonomous driving vehicle.

Description

Technical Field

[0001] The present disclosure relates to an autonomous driving system, an autonomous driving control method, and a non-transitory storage medium. Background Art

[0002] Japanese Unexamined Patent Application Publication No. 2018-077649 discloses a remote driving control device that performs remote driving of a vehicle. The remote driving control device performs remote driving of the vehicle by communicating with the vehicle.

[0003] Consider a remote support technology for remotely supporting the driving of an autonomous driving vehicle. Remote support requires communication between a remote support device and the autonomous driving vehicle. A "remote support system" includes components and functions for providing remote support to an autonomous driving vehicle. For example, the remote support system includes a remote support device, a communication network, a communication device mounted on the autonomous driving vehicle, and the like. In the case where an abnormality occurs in at least a part of the remote support system, remote support cannot be provided to the autonomous driving vehicle, or the accuracy of the remote support decreases. Summary of the Invention

[0004] The present disclosure provides a technology capable of appropriately controlling an autonomous driving vehicle when an abnormality occurs in a remote support system that provides remote support to the autonomous driving vehicle.

[0005] The autonomous driving system according to the first aspect of the present disclosure includes: one or more storage devices that store specific position information indicating a specific position where remote support may be required; and one or more processors configured to: set a first target route as a route to a destination, that is, a target route, determine whether an abnormality has occurred in a remote support system configured to provide remote support to an autonomous driving vehicle as an object of remote support, and in the case where an abnormality in the remote support system is detected, search for an alternative route based on the specific position information, where the alternative route is a route to the destination in which the number of specific positions passed through by the autonomous driving vehicle is smaller than the number of specific positions passed through in the first target route, and in the case where an alternative route is found, change the target route from the first target route to the alternative route and control the autonomous driving vehicle.

[0006] The automatic driving control method of the second solution of the present disclosure includes: setting a first target route as the route to the destination, i.e., the target route; determining whether an abnormality has occurred in the remote support system, where the remote support system is configured to provide remote support for an autonomous vehicle that is the object of remote support; in the case of detecting an abnormality in the remote support system, searching for an alternative route based on specific location information indicating specific locations where remote support may be required, where the alternative route is a route to the destination with a smaller number of specific locations passed by the autonomous vehicle than the number of specific locations passed by in the first target route; in the case of finding an alternative route, changing the target route from the first target route to the alternative route; and controlling the autonomous vehicle.

[0007] The non-transitory storage medium of the third solution of the present disclosure stores an automatic driving control program, which can be executed by one or more processors and causes the one or more processors to execute the following functions. The functions include: setting a first target route as the route to the destination, i.e., the target route; determining whether an abnormality has occurred in the remote support system, where the remote support system is configured to provide remote support for an autonomous vehicle that is the object of remote support; in the case of detecting an abnormality in the remote support system, searching for an alternative route based on specific location information indicating specific locations where remote support may be required, where the alternative route is a route to the destination with a smaller number of specific locations passed by the autonomous vehicle than the number of specific locations passed by in the first target route; in the case of finding an alternative route, changing the target route from the first target route to the alternative route; and controlling the autonomous vehicle.

[0008] According to the present disclosure, in the case of detecting an abnormality in the remote support system, the automatic driving system searches for an alternative route in which the number of specific locations passed by the autonomous vehicle is smaller than the number of specific locations passed by in the first target route. In the case of finding such an alternative route, the target route to the destination is changed from the first target route to the alternative route. Since the number of specific locations passed by the autonomous vehicle is reduced, the overall probability of requiring remote support is reduced. As a result, the probability that the autonomous vehicle can reach the destination increases. Even in the case of detecting an abnormality in the remote support system, there is no need to end the automatic driving near the current location. By performing the route change process, the automatic driving can be continued as much as possible. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Hereinafter, with reference to the drawings, the features, advantages, and technical and industrial significance of the exemplary embodiments of the present invention will be described, where the same reference numerals denote the same elements, where:

[0010] Figure 1 It is a conceptual diagram of a remote support system showing an embodiment of the present disclosure.

[0011] Figure 2 It is a conceptual diagram for explaining an overview of remote support for an embodiment of the present disclosure.

[0012] Figure 3 It is a conceptual diagram for explaining an example of a specific location of an embodiment of the present disclosure.

[0013] Figure 4 It is a conceptual diagram for explaining the processing when an abnormality occurs in the remote support system of an embodiment of the present disclosure.

[0014] Figure 5 It is a conceptual diagram for explaining an example of the processing when an abnormality occurs in the remote support system of an embodiment of the present disclosure.

[0015] Figure 6 It is a conceptual diagram for explaining another example of the processing when an abnormality occurs in the remote support system of an embodiment of the present disclosure.

[0016] Figure 7 It is a conceptual diagram for explaining an example of the fallback processing of an embodiment of the present disclosure.

[0017] Figure 8 It is a conceptual diagram for explaining an example of a parking candidate area of an embodiment of the present disclosure.

[0018] Figure 9 It is a conceptual diagram for explaining an example of a high-priority area and a low-priority area of an embodiment of the present disclosure.

[0019] Figure 10 It is a block diagram showing a configuration example of an autonomous driving system of an embodiment of the present disclosure.

[0020] Figure 11 It is a block diagram showing an example of driving environment information of an embodiment of the present disclosure.

[0021] Figure 12 It is a flowchart showing an example of processing performed by the autonomous driving system of an embodiment of the present disclosure.

[0022] Figure 13 It is a flowchart showing a first example of step S300 of an embodiment of the present disclosure.

[0023] Figure 14 It is a flowchart showing a second example of step S300 of an embodiment of the present disclosure.

[0024] Figure 15It is a flowchart showing a third example of step S300 of an embodiment of the present disclosure. Detailed implementation mode

[0025] With reference to the accompanying drawings, embodiments of the present disclosure will be described.

[0026] 1. Outline of remote support

[0027] Figure 1 It is a conceptual diagram showing the remote support system of this embodiment. The remote support system includes an autonomous vehicle 1, a remote support device 2, and a communication network 3.

[0028] The autonomous vehicle 1 is a vehicle capable of autonomous driving. As the autonomous driving here, autonomous driving on the premise that the driver does not have to focus 100% on driving (so-called level 3 or higher autonomous driving) is assumed. The autonomous vehicle 1 may also be a level 4 or higher autonomous vehicle without a driver. The autonomous vehicle 1 is the object of remote support in this embodiment.

[0029] The remote support device 2 is a device for remotely supporting the autonomous vehicle 1 and is operated by a remote operator. The autonomous vehicle 1 and the remote support device 2 are connected via the communication network 3 so as to be able to communicate with each other. The remote support device 2 communicates with the autonomous vehicle 1 via the communication network 3 and remotely supports the driving of the autonomous vehicle 1. More specifically, the remote operator operates the remote support device 2 to remotely support the driving of the autonomous vehicle 1. The remote support device 2 can also be said to be a device that assists the remote operator in remotely supporting the autonomous vehicle 1.

[0030] The communication network 3 includes a wireless base station, a wireless communication network, a wired communication network, etc. As the wireless communication network, for example, a 5G (5th Generation Mobile Communication Technology) network can be exemplified.

[0031] Figure 2 It is a conceptual diagram for explaining the outline of the remote support of this embodiment. The autonomous driving system 10 controls the autonomous vehicle 1. In autonomous driving, the autonomous driving system 10 performs various vehicle processes. As representative vehicle processes in autonomous driving, the following processes can be listed.

[0032] (1) Recognition process: The autonomous driving system 10 uses recognition sensors to recognize the surrounding conditions of the autonomous vehicle 1. For example, the autonomous driving system 10 uses a camera to recognize the signal display of traffic lights (for example: green light, yellow light, red light, right turn signal, etc.).

[0033] (2) Action determination process: The autonomous driving system 10 determines whether to perform an action based on the result of the recognition process. Examples of actions include starting, stopping, turning right, turning left, lane change, etc.

[0034] (3) Timing determination process: The autonomous driving system 10 determines the execution timing of performing the above actions.

[0035] Typically, the situation where remote support by a remote operator is required is a situation where autonomous driving is difficult. For example, at Figure 3 the intersection shown, remote support may be required.

[0036] For example, when sunlight shines on the traffic signal installed at the intersection, the recognition accuracy of the signal display may decrease. When the signal display cannot be accurately discriminated through the recognition process, the autonomous driving system 10 requires remote support for signal recognition. In addition, when the signal display cannot be discriminated, it is also difficult to determine at which timing which action should be performed. Therefore, the autonomous driving system 10 also requires remote support for the action determination process and the timing determination process.

[0037] It is also possible to consider a situation where it is difficult to determine whether an action can actually be performed even if the signal display is discriminated. For example, although the signal display observed from the autonomous driving system 10 becomes "turn right", sometimes oncoming vehicles may enter the intersection, or oncoming vehicles and preceding vehicles may be stuck in the intersection. In such a case, the autonomous driving system 10 can also request remote support for the action determination process and the timing determination process in a state where the autonomous driving vehicle 1 is stopped.

[0038] As another example, it is also considered a situation where it is difficult to determine whether to change lanes when there is a construction section in front of the autonomous driving vehicle 1. In this case, the autonomous driving system 10 can also request remote support for the action determination process.

[0039] The autonomous driving system 10 can also request the remote operator to perform remote driving (remote operation) of the autonomous driving vehicle 1. "Remote support" in the present embodiment is a concept that includes not only at least one of the recognition process, the action determination process, and the timing determination process, but also remote driving (remote operation).

[0040] When it is determined that remote support is required, the autonomous driving system 10 sends a remote support request REQ to the remote support device 2 via the communication network 3. The remote support request REQ is information for requesting the remote operator to provide remote support for the autonomous driving vehicle 1. The remote support device 2 notifies the received remote support request REQ to the remote operator. In response to the remote support request REQ, the remote operator starts remote support for the autonomous driving vehicle 1.

[0041] During the remote support process, the autonomous driving system 10 sends vehicle information VCL to the remote support device 2 via the communication network 3. The vehicle information VCL indicates the state of the autonomous driving vehicle 1, the surrounding conditions, the results of the vehicle processing performed by the autonomous driving system 10, etc. The remote support device 2 presents the vehicle information VCL received from the autonomous driving system 10 to the remote operator. For example, Figure 2 As shown, the remote support device 2 displays image information IMG captured by a camera mounted on the autonomous driving vehicle 1 on a display device.

[0042] The remote operator remotely supports the autonomous vehicle 1 while referring to the vehicle information VCL. The operator instruction INS is an instruction input by the remote operator to the autonomous vehicle 1. The remote support device 2 receives the operator instruction INS input from the remote operator. The remote support device 2 then transmits the operator instruction INS to the autonomous vehicle 1 via the communication network 3. The autonomous driving system 10 receives the operator instruction INS from the remote support device 2 and controls the autonomous vehicle 1 according to the received operator instruction INS.

[0043] 2. Handling of abnormalities in the remote support system

[0044] 2-1. Remote support system anomalies

[0045] In this embodiment, the "remote support system 4" refers to the structure and function for providing remote support to the autonomous driving vehicle 1. For example, the remote support system 4 includes a remote support device 2, a communication network 3, a communication device installed in the autonomous driving vehicle 1, etc. (see Figure 1 ) Examples of the communication device mounted on the autonomous driving vehicle 1 include a communication ECU (Electronic Control Unit), a communication module, a transceiver circuit, and the like.

[0046] Hereinafter, a case will be considered where an “abnormality” occurs in at least a portion of the remote support system 4 that provides remote support to the autonomous driving vehicle 1 .

[0047] For example, an abnormality of the remote support system 4 includes a "functional failure" in which the function of the remote support system 4 is lost. One example of a functional failure of the remote support system 4 is a communication interruption. For example, when a problem (trouble) occurs in the communication network 3, a communication interruption may occur. Another example of a functional failure of the remote support system 4 is a failure (shutdown) of the remote support device 2. Yet another example of a functional failure of the remote support system 4 is a failure of the communication device mounted on the autonomous driving vehicle 1. In the event of a functional failure of the remote support system 4, remote support cannot be provided to the autonomous driving vehicle 1.

[0048] An abnormality in the remote support system 4 may also include "performance degradation," which is a reduction in the functionality of the remote support system 4. One example of performance degradation in the remote support system 4 is a significant decrease in communication speed or throughput. Another example of performance degradation in the remote support system 4 is a significant increase in communication latency. Yet another example of performance degradation in the remote support system 4 is a decrease in the internal communication speed or computing speed of the communication ECU installed in the autonomous vehicle 1. If performance degradation in the remote support system 4 occurs, the accuracy of remote support may be reduced.

[0049] 2-2. Route change processing

[0050] If an anomaly occurs in the remote support system 4, remote support for the autonomous vehicle 1 may become unavailable, or the accuracy of remote support for the autonomous vehicle 1 may be reduced. However, it is not necessary to immediately bring the autonomous vehicle 1 to an emergency stop upon detecting an anomaly in the remote support system 4. This is because the autonomous driving system 10 can continue autonomous driving as normal when remote support is not required. In other words, even if an anomaly in the remote support system 4 is detected, there is no need to hastily terminate autonomous driving. According to this embodiment, the autonomous driving system 10 considers the possibility of remote support being required and continues autonomous driving as much as possible.

[0051] Hereinafter, the location where remote support of the autonomous driving vehicle 1 may be required is referred to as a “specific location PS”. For example, the specific location PS is Figure 3As another example, the specific location PS may be a location outside the operational design domain (ODD), which is an area designed for the automated driving system to operate appropriately. As another example, the specific location PS may include a construction site, a congested section, an accident location, etc. Typically, the specific location PS is pre-registered in map information. Alternatively, information on specific locations PS such as congested sections and accident locations may be acquired in real time.

[0052] Figure 4 The figure shows an example of an autonomous driving situation at the time when an abnormality in the remote support system 4 is detected. The current position and destination of the autonomous driving vehicle 1 are represented by the reference numerals "P1" and "DST," respectively. The autonomous driving system 10 sets a target route RT from the current position P1 to the destination DST, which is the route to the autonomous driving vehicle 1. For convenience, the current target route RT is referred to as the "first target route RT1." The autonomous driving system 10 controls the autonomous driving vehicle 1 to travel along the first target route RT1 to the destination DST.

[0053] At the time when an abnormality in the remote support system 4 is detected, a specific position PS exists on the first target route RT1 to the destination DST. Figure 4 In the example shown, there are multiple specific locations PS1, PS2, and PS3 on the first target route RT1. In this case, the autonomous driving system 10 searches for an "alternative route RT2," which differs from the first target route RT1, as the target route RT to the destination DST. Specifically, the autonomous driving system 10 searches for an alternative route RT2 that passes through fewer specific locations PS than the first target route RT1. If such an alternative route RT2 is found, the autonomous driving system 10 performs a "route change process" to change the target route RT to the destination DST from the first target route RT1 to the alternative route RT2.

[0054] Figure 5 This is a conceptual diagram showing an example of an alternative route RT2. Figure 5 In the example shown, the autonomous vehicle 1 travels from its current position P1 to its destination DST via alternative route RT2, bypassing the specific location PS. Since alternative route RT2 bypasses the specific location PS, the autonomous driving system 10 can continue its normal autonomous driving to the destination DST without requiring remote support. In other words, the autonomous vehicle 1 can reach the destination DST without being affected by any anomalies in the remote support system 4.

[0055] Figure 6 This is a conceptual diagram showing another example of alternative route RT2. Figure 6 In the example shown, the autonomous vehicle 1 travels from its current position P1 via alternative route RT2, passing through only one specific location PS1 to reach its destination DST. Specifically, the number of specific locations PS passed by the autonomous vehicle 1 on alternative route RT2 is smaller than that passed by the first target route RT1. Since the number of specific locations PS passed by the autonomous vehicle 1 is reduced, the overall probability of requiring remote support decreases. Consequently, the probability that the autonomous vehicle 1 will reach its destination DST increases.

[0056] It should be noted that in Figure 6 In the example shown, specific location PS1 is a location where remote support may be required, but remote support is not necessarily required at specific location PS1. If remote support is not required at specific location PS1, autonomous driving vehicle 1 can pass through specific location PS1 using normal autonomous driving. Even if remote support is required at specific location PS1, if the abnormality in remote support system 4 is "performance degradation," remote support can still be provided despite the slow response of remote support system 4.

[0057] 2-3. Backoff Processing

[0058] If the alternative route RT2 cannot be found, the autonomous driving system 10 may also execute a “retreat process” to cause the autonomous driving vehicle 1 to retreat safely.

[0059] Figure 7 This is a conceptual diagram for explaining an example of a retraction process. The "target retraction position PE" is the target stop position when the autonomous driving vehicle 1 is stopped by the retraction process. The target retraction position PE can also be set to a safe position on the road. Figure 7 In the example shown, the target retreat position PE is set to the road shoulder.

[0060] The autonomous driving system 10 sets a target retraction position PE on and around the road along the first target route RT1. The autonomous driving system 10 then controls the autonomous driving vehicle 1 to travel toward and stop at the target retraction position PE. For example, the autonomous driving system 10 generates a target trajectory TR in which the autonomous driving vehicle 1 travels from its current position toward and stops at the target retraction position PE. The autonomous driving system 10 then controls the autonomous driving vehicle 1 to follow the target trajectory TR.

[0061] The partition that can be used as the target retreat position PE in the retreat process may be defined in advance. Hereinafter, the partition that can be used as the target retreat position PE in the retreat process is referred to as a "candidate parking partition AC."

[0062] Figure 8 This is a conceptual diagram for explaining an example of a parking candidate zone AC. To explain the parking candidate zone AC, first, the "parking prohibited zone AX" will be explained. The parking prohibited zone AX is a zone where vehicles are prohibited from parking, and is pre-defined by the Road Traffic Act, etc. Figure 8 In the example shown, no-parking zone AX includes a crosswalk and its surrounding zones of a predetermined width. No-parking zone AX may also include an intersection and its surrounding zones of a predetermined width. In addition, zones in front of firefighting equipment are also included in no-parking zone AX.

[0063] The parking candidate zone AC is selected from zones other than the parking prohibited zone AX on the road. Typically, the parking candidate zone AC is a portion of the zones other than the parking prohibited zone AX. For example, the parking candidate zone AC is selected from the perspective of ensuring the safety of the autonomous driving vehicle 1 after parking. Figure 8 As illustrated, the candidate parking section AC may be a section closer to the road edge. The candidate parking section AC may be set to include the road shoulder and the roadside strip.

[0064] like Figure 9 As shown, priorities can also be set for the parking candidate zones AC. The high priority zone ACH is a parking candidate zone AC with a higher priority, and the low priority zone ACL is a parking candidate zone AC with a lower priority. Figure 9 In the example shown, the straight road section is set as the high-priority zone ACH, and the curved road section is set as the low-priority zone ACL.

[0065] Candidate parking zones AC and prohibited parking zones AX are pre-registered in map information, for example. During the backoff process, the automated driving system 10 may also set the target backoff position PE to be included in the candidate parking zones AC. When prioritizing the candidate parking zones AC, the automated driving system 10 sets the target backoff position PE to be included in the candidate parking zones AC with the highest possible priority.

[0066] 2-4. Effect

[0067] As described above, according to the present embodiment, when an abnormality of the remote support system 4 is detected, the autonomous driving system 10 searches for an alternative route RT2 such that the number of specific positions PS through which the autonomous driving vehicle 1 passes is smaller than the number of specific positions PS through which the vehicle passes in the first target route RT1. When such an alternative route RT2 is found, the target route RT to the destination DST is changed from the first target route RT1 to the alternative route RT2. Since the number of specific positions PS through which the autonomous driving vehicle 1 passes is reduced, the probability of requiring remote support is generally reduced as a whole. As a result, the probability that the autonomous driving vehicle 1 can reach the destination DST increases. Even when an abnormality of the remote support system 4 is detected, it is not necessary to end the autonomous driving near the current position P1. By performing the route change process, the autonomous driving can be continued as much as possible.

[0068] The autonomous driving system 10 may also search for an alternative route RT2 that reaches the destination DST without passing through the specific position PS. In this case, there is no opportunity to require remote support, so the autonomous driving system 10 can continue the autonomous driving to the destination DST as usual. That is, the autonomous driving vehicle 1 can reach the destination DST without being affected by the abnormality of the remote support system 4.

[0069] Hereinafter, the autonomous driving system 10 of the present embodiment will be described in further detail.

[0070] 3. Example of Autonomous Driving System

[0071] 3-1. Configuration Example

[0072] The autonomous driving system 10 controls the autonomous driving vehicle 1. Typically, the autonomous driving system 10 is mounted on the autonomous driving vehicle 1. Alternatively, at least a part of the autonomous driving system 10 may be configured in an external device outside the autonomous driving vehicle 1 to remotely control the autonomous driving vehicle 1. That is, the autonomous driving system 10 may be dispersedly configured in the autonomous driving vehicle 1 and the external device.

[0073] Figure 10 It is a block diagram showing a configuration example of the autonomous driving system 10 of the present embodiment. The autonomous driving system 10 includes a sensor group 20, a driving device 30, a communication device 40, and a control device 100.

[0074] The sensor group 20 is mounted on the autonomous vehicle 1. The sensor group 20 includes a vehicle state sensor, an identification sensor, a position sensor, etc. The vehicle state sensor detects the state of the autonomous vehicle 1. As the vehicle state sensor, a vehicle speed sensor, a yaw rate sensor, a lateral acceleration sensor, a steering angle sensor, etc. can be exemplified. The identification sensor detects the conditions around the autonomous vehicle 1. As the identification sensor, a camera, a lidar (Laser Imaging Detection and Ranging), a radar, etc. can be exemplified. The position sensor detects the position and orientation of the autonomous vehicle 1. As the position sensor, a GPS (Global Positioning System) sensor can be exemplified.

[0075] The traveling device 30 is mounted on the autonomous vehicle 1. The traveling device 30 includes a steering device, a driving device, and a braking device. The steering device steers the wheels. For example, the steering device includes an electric power steering (EPS) device. The driving device is a power source that generates a driving force. As the driving device, an engine, an electric motor, an in-wheel motor, etc. can be exemplified. The braking device generates a braking force.

[0076] The communication device 40 communicates with the outside of the autonomous vehicle 1. For example, the communication device 40 communicates with the remote support device 2 via the communication network 3 (refer to Figure 1 , Figure 2 ). The communication device 40 can communicate with the management server. The communication device 40 can also perform V2I (vehicle-to-infrastructure) communication (road-vehicle communication) with the surrounding infrastructure. The communication device 40 can also perform V2V (vehicle-to-vehicle) communication (vehicle-to-vehicle communication) with the surrounding vehicles. The communication device 40 includes a communication ECU (Electronic Control Unit), a communication module, a transceiver circuit, etc.

[0077] The control device 100 controls the autonomous driving vehicle 1. The control device 100 includes one or more processors 110 (hereinafter, only referred to as the processor 110) and one or more storage devices 120 (hereinafter, only referred to as the storage device 120). The processor 110 performs various processes. For example, the processor 110 includes a CPU (Central Processing Unit). The storage device 120 stores various information. Examples of the storage device 120 include a volatile memory, a non-volatile memory, an HDD (Hard Disk Drive), an SSD (Solid State Drive), etc. The control device 100 may also include one or more ECUs. A part of the control device 100 may also be an information processing device external to the autonomous driving vehicle 1.

[0078] The autonomous driving control program PROG is a computer program for controlling the autonomous driving vehicle 1. Various processes performed by the control device 100 are implemented by the processor 110 executing the autonomous driving control program PROG. The autonomous driving control program PROG is stored in the storage device 120. Alternatively, the autonomous driving control program PROG may also be recorded on a computer-readable recording medium.

[0079] 3-2. Driving environment information

[0080] The driving environment information 200 represents the driving environment of the autonomous driving vehicle 1. The driving environment information 200 is stored in the storage device 120.

[0081] Figure 11 is a block diagram showing an example of the driving environment information 200. The driving environment information 200 includes map information 210, specific location information 220, evacuation zone information 230, vehicle state information 240, surrounding condition information 250, vehicle position information 260, and distribution information 270.

[0082] The map information 210 includes a general navigation map. The map information 210 may also represent the lane configuration, road shape, etc. The map information 210 may also include the position information of signals, signs, etc. The processor 110 obtains the map information of the required section from the map database. The map database may be stored in a prescribed storage device mounted on the autonomous driving vehicle 1 or in an external management server. In the latter case, the processor 110 communicates with the management server to obtain the required map information.

[0083] The specific location information 220 indicates a specific location PS where remote support may be required for the autonomous vehicle 1. For example, the specific location information 220 is prepared in advance. The specific location information 220 may also be included in the map information 210. As described later, the specific location information 220 may also be added in real time.

[0084] The avoidance section information 230 indicates the positions of the parking candidate section AC and the parking prohibited section AX (see Figure 8 The avoidance zone information 230 may also indicate the priority of the parking candidate zones AC (see Figure 9 ). The avoidance partition information 230 is created in advance. The avoidance partition information 230 may also be included in the map information 210.

[0085] The vehicle state information 240 is information indicating the state of the autonomous driving vehicle 1. The processor 110 acquires the vehicle state information 240 from a vehicle state sensor.

[0086] Surrounding condition information 250 is information indicating the surrounding conditions of the autonomous vehicle 1. Processor 110 uses recognition sensors to acquire surrounding condition information 250. For example, surrounding condition information 250 includes image information IMG captured by a camera. Surrounding condition information 250 also includes object information related to objects surrounding the autonomous vehicle 1. Examples of objects include pedestrians, bicycles, other vehicles (preceding vehicles, parked vehicles, etc.), road structures (white lines, curbs, guardrails, walls, medians, roadside structures, etc.), signs, and obstacles. Object information indicates the relative position and relative speed of an object relative to the autonomous vehicle 1.

[0087] Vehicle position information 260 indicates the position of autonomous driving vehicle 1. Processor 110 obtains vehicle position information 260 from detection results obtained by the position sensor. Alternatively, processor 110 can obtain highly accurate vehicle position information 260 through a known process of estimating the vehicle's position (localization) using object information and map information 210.

[0088] The distribution information 270 includes road traffic information, road construction information, traffic control information, etc. The processor 110 receives the distribution information 270 from an information providing server or roadside infrastructure via the communication device 40 .

[0089] The processor 110 can grasp the construction section, congested section, accident location, etc. based on the distribution information 270. In this case, the processor 110 can also add the construction section, congested section, accident location, etc. to the specific location information 220.

[0090] 3-3. Vehicle driving control and autonomous driving control

[0091] The processor 110 performs "vehicle driving control" to control the driving of the autonomous driving vehicle 1. Vehicle driving control includes steering control, acceleration control, and deceleration control. The processor 110 performs vehicle driving control by controlling the driving device 30 (steering device, drive device, brake device). Specifically, the processor 110 performs steering control by controlling the steering device. In addition, the processor 110 performs acceleration control by controlling the drive device. In addition, the processor 110 performs deceleration control by controlling the brake device.

[0092] Furthermore, the processor 110 performs autonomous driving control based on the driving environment information 200. More specifically, the processor 110 sets a target route RT to the destination DST based on map information 210 and the like. Furthermore, the processor 110 controls vehicle travel based on the driving environment information 200 so that the autonomous driving vehicle 1 travels along the target route RT to the destination DST.

[0093] More specifically, processor 110 generates a driving plan for autonomous vehicle 1 based on driving environment information 200. This driving plan includes maintaining the current lane, making lane changes, and avoiding obstacles. Furthermore, processor 110 generates a target trajectory TR required for autonomous vehicle 1 to follow the driving plan. Target trajectory TR includes a target position and a target speed. Processor 110 then controls vehicle driving to ensure the autonomous vehicle 1 follows target route RT and target trajectory TR.

[0094] 3-4. Processing related to remote support

[0095] During autonomous driving, processor 110 determines whether remote support from a remote operator is necessary. Typically, situations requiring remote support from a remote operator are those in which autonomous driving becomes difficult. For example, processor 110 determines that remote support from a remote operator is necessary when at least one of the aforementioned recognition, action determination, and timing determination processes is difficult to perform.

[0096] If it is determined that remote support is required, the processor 110 transmits a remote support request REQ to the remote support apparatus 2 via the communication device 40. The remote support request REQ requests the remote operator to provide remote support to the autonomous driving vehicle 1.

[0097] Furthermore, the processor 110 transmits vehicle information VCL to the remote support device 2 via the communication device 40. The vehicle information VCL includes at least a portion of the driving environment information 200. For example, the vehicle information VCL includes image information IMG captured by a camera. The vehicle information VCL may include object information. The vehicle information VCL may also include vehicle status information 240 and vehicle position information 260. The vehicle information VCL may also include the results of the recognition processing, the action determination processing, and the timing determination processing.

[0098] Furthermore, the processor 110 receives an operator instruction INS from the remote support apparatus 2 via the communication device 40. The operator instruction INS is an instruction input by the remote operator to the autonomous vehicle 1. Upon receiving the operator instruction INS, the processor 110 controls the vehicle according to the received operator instruction INS.

[0099] 4. Processing flow when an exception occurs in the remote support system

[0100] Figure 12 : is a flowchart showing an example of processing of the automatic driving system 10 according to this embodiment. In particular, Figure 12 The flowchart shows the process flow associated with the occurrence of an abnormality in the remote support system 4 .

[0101] 4-1. Step S100

[0102] In step S100 , the processor 110 determines whether an abnormality occurs in the remote support system 4 providing remote support to the autonomous driving vehicle 1 . For example, the remote support system 4 includes a remote support device 2 , a communication network 3 , and a communication device 40 of the autonomous driving system 10 .

[0103] Abnormalities in the remote support system 4 include "functional failures," which are the loss of functionality of the remote support system 4. For example, the processor 110 monitors the communication status (e.g., throughput, communication speed) with the remote support device 2. If communication with the remote support device 2 is interrupted, the processor 110 determines that a functional failure has occurred in the remote support device 2 or the communication network 3. As another example, the communication device 40 (e.g., the communication ECU) of the autonomous driving system 10 has a self-diagnostic function. The processor 110 can use this self-diagnostic function to detect functional failures in the communication device 40.

[0104] An abnormality in the remote support system 4 may also include a performance degradation, such as a reduction in the functionality of the remote support system 4. For example, the processor 110 monitors the communication status (e.g., throughput, communication speed, and communication delay) with the remote support device 2. If the throughput or communication speed falls below a threshold, the processor 110 determines that the performance of the remote support system 4 has degraded. As another example, if the communication delay exceeds a threshold, the processor 110 determines that the performance of the remote support system 4 has degraded.

[0105] If no abnormality is detected in the remote support system 4 (step S100 ; No), the process in this loop ends. On the other hand, if an abnormality is detected in the remote support system 4 (step S100 ; Yes), the process proceeds to step S200 .

[0106] 4-2. Step S200

[0107] In step S200, processor 110 determines whether a specific location PS exists on first target route RT1 from current location P1 to destination DST. First target route RT1 is set and known by processor 110. Specific location PS is obtained from specific location information 220. Thus, processor 110 can determine whether specific location PS exists on first target route RT1 based on specific location information 220.

[0108] If the specific position PS exists on the first target route RT1 (step S200 returns Yes), the process proceeds to step S300. On the other hand, if the specific position PS does not exist on the first target route RT1 (step S200 returns No), the process in this loop ends.

[0109] 4-3. Step S300

[0110] In step S300, the processor 110 searches for an alternative route RT2 that is different from the first target route RT1 and serves as the target route RT to the destination DST. Specifically, the processor 110 searches for an alternative route RT2 in which the autonomous driving vehicle 1 passes through fewer specific locations PS than the first target route RT1. The processor 110 can search for such an alternative route RT2 based on the map information 210 and the specific location information 220.

[0111] If the alternative route RT2 is found (step S300; Yes), the process proceeds to step S400. On the other hand, if the alternative route RT2 is not found (step S300; No), the process proceeds to step S600. Several examples of step S300 are described below.

[0112] 4-3-1. The first example

[0113] Figure 13 This is a flowchart showing a first example of step S300.

[0114] In step S320, processor 110 searches for an alternative route RT2 that reaches destination DST from current position P1 without passing through specific position PS. If such an alternative route RT2 is found (step S320: Yes), processing proceeds to step S400. On the other hand, if such an alternative route RT2 is not found (step S320: No), processing proceeds to step S600.

[0115] According to the first example, the alternative route RT2 that is not affected by the abnormality of the remote support system 4 can be searched.

[0116] 4-3-2. Second Example

[0117] Figure 14 This is a flowchart showing a second example of step S300. Step S320 is the same as in the first example. If no alternative route RT2 that does not pass through the specific location PS is found (step S320; No), the process proceeds to step S330.

[0118] In step S330, the processor 110 searches for an alternative route RT2 in which the autonomous driving vehicle 1 passes through fewer specific locations PS than the first target route RT1. If such an alternative route RT2 is found (step S330: Yes), the process proceeds to step S400. On the other hand, if such an alternative route RT2 is not found (step S330: No), the process proceeds to step S600.

[0119] According to the second example, the selection range of the alternative route RT2 can be expanded. In other words, the conditions imposed on the alternative route RT2 can be relaxed.

[0120] 4-3-3. The third example

[0121] Figure 15 This is a flowchart showing a third example of step S300.

[0122] In step S310 , the processor 110 determines whether the abnormality of the remote support system 4 is a malfunction or a performance degradation.

[0123] If the abnormality of the remote support system 4 is a malfunction (step S310; Yes), the process proceeds to step S320. Steps after step S320 are the same as those in the first example described above.

[0124] On the other hand, when the abnormality in the remote support system 4 is a performance degradation (step S310; No), the process proceeds to step S330. After step S330, it is the same as in the second case. It should be noted that the alternative route RT2 here also includes an alternative route RT2 that does not pass through the specific location PS.

[0125] According to the third case, when the abnormality in the remote support system 4 is a performance degradation, the selection range of the alternative route RT2 can be expanded. That is, when the abnormality in the remote support system 4 is a performance degradation, the conditions attached to the alternative route RT2 can be relaxed.

[0126] 4 - 4. Step S400

[0127] In step S400, the processor 110 performs route change processing. Specifically, the processor 110 changes the target route RT to the destination DST from the first target route RT1 to the alternative route RT2. After that, the process proceeds to step S500.

[0128] 4 - 5. Step S500

[0129] In step S500, the processor 110 performs vehicle driving control based on the driving environment information 200 so that the autonomous driving vehicle 1 travels along the alternative route RT2 to the destination DST.

[0130] 4 - 6. Step S600

[0131] In step S600, the processor 110 executes an evacuation process to safely evacuate the autonomous driving vehicle 1.

[0132] Specifically, the processor 110 sets a target evacuation position PE on and around the road passed by the first target route RT1. At this time, the processor 110 sets the target evacuation position PE to a position where the autonomous driving vehicle 1 can actually stop based on the current position P1, vehicle speed, motion performance, etc. of the autonomous driving vehicle 1. The processor 110 can also refer to the evacuation zone information 230 to set the target evacuation position PE. The evacuation zone information 230 indicates the positions of the parking candidate zones AC and the parking prohibited zones AX. The processor 110 avoids the parking prohibited zones AX and sets the target evacuation position PE in the parking candidate zones AC. The evacuation zone information 230 can also indicate the priorities of the parking candidate zones AC. In this case, the processor 110 sets the target evacuation position PE to be included in the parking candidate zone AC with the highest possible priority.

[0133] Furthermore, the processor 110 controls the vehicle so that the autonomous driving vehicle 1 travels to the target retreat position PE and stops at the target retreat position PE. For example, the processor 110 generates a target trajectory TR such that the autonomous driving vehicle 1 travels from the current position P1 to the target retreat position PE and stops at the target retreat position PE. Furthermore, the autonomous driving system 10 controls the vehicle so that the autonomous driving vehicle 1 follows the target trajectory TR (see FIG. Figure 7 ).

Claims

1. An autonomous driving system, characterized in that, Comprising: One or more storage devices storing specific location information representing a specific location where remote support may be required; And One or more processors, The one or more processors being configured to: Set a first target route as the route to the destination, i.e., the target route; Determine whether an abnormality has occurred in the remote support system, where the remote support system is configured to provide the remote support to an autonomous vehicle that is the object of the remote support; In the case where the abnormality of the remote support system is detected, search for an alternative route based on the specific location information, where, in the case where the abnormality is a malfunction of the remote support system, the alternative route is a route for the autonomous vehicle to reach the destination without passing through the specific location, and in the case where the abnormality is a reduction in the performance of the remote support system, the alternative route is a route for the autonomous vehicle to reach the destination with a smaller number of specific locations passed through than the number of specific locations passed through in the first target route; In the case where the alternative route is found, change the target route from the first target route to the alternative route; and Control the autonomous vehicle.

2. The autonomous driving system according to claim 1, wherein The one or more processors are configured to: search for the alternative route for the autonomous vehicle to reach the destination without passing through the specific location based on the specific location information.

3. The autonomous driving system according to claim 1, wherein The one or more processors are configured to: Search for the alternative route for the autonomous vehicle to reach the destination without passing through the specific location based on the specific location information; In the case where the alternative route for the autonomous vehicle to reach the destination without passing through the specific location cannot be found, search for the alternative route with more than one specific location passed through by the autonomous vehicle based on the specific location information.

4. The autonomous driving system according to any one of claims 1 to 3, wherein The one or more processors are configured to, in the case where the alternative route cannot be found, Set a target evacuation position on the first target route; and Control the autonomous vehicle to stop at the target evacuation position.

5. The autonomous driving system according to claim 1, wherein The one or more processors are configured to control the autonomous vehicle in such a manner that the autonomous vehicle travels along the target route to the destination.

6. The autonomous driving system according to claim 1, wherein It further comprises: A communication device configured to communicate with the outside of the autonomous vehicle, Wherein the one or more processors are configured to: in the case where distribution information is received from an information providing server or roadside infrastructure via the communication device, append the specific location to the specific location information based on the distribution information.

7. The autonomous driving system according to claim 1, wherein The one or more storage devices store map information, And, the map information includes the specific location information.

8. The autonomous driving system according to claim 1, wherein the specific location includes an intersection.

9. The autonomous driving system according to claim 1, wherein the specific location includes a location outside the operational design domain.

10. The autonomous driving system according to claim 1, wherein the specific location includes a construction section, a congested section, and an accident location.

11. An automatic driving control method, characterized in that, comprising: setting a first target route as the route to the destination, i.e., the target route; determining whether an abnormality has occurred in a remote support system, where the remote support system is configured to provide the remote support to an autonomous driving vehicle that is the object of the remote support; in the case of detecting the abnormality of the remote support system, searching for an alternative route based on specific location information indicating a specific location where the remote support may be required, where, in the case where the abnormality is a malfunction of the remote support system, the alternative route is the route for the autonomous driving vehicle to reach the destination without passing through the specific location, and in the case where the abnormality is a degradation in the performance of the remote support system, the alternative route is the route for the autonomous driving vehicle to reach the destination with a smaller number of the specific locations passed through than the number of the specific locations passed through in the first target route; in the case of finding the alternative route, changing the target route from the first target route to the alternative route; and controlling the autonomous driving vehicle.

12. A non-transitory storage medium storing an autonomous driving control program, the autonomous driving control program being executable by one or more processors and causing the one or more processors to perform the following functions, wherein the non-transitory storage medium is characterized in that the functions include: setting a first target route as the route to the destination, i.e., the target route; determining whether an abnormality has occurred in a remote support system, where the remote support system is configured to provide the remote support to an autonomous driving vehicle that is the object of the remote support; in the case of detecting the abnormality of the remote support system, searching for an alternative route as the route to the destination based on specific location information indicating a specific location where the remote support may be required, where, in the case where the abnormality is a malfunction of the remote support system, the alternative route is the route for the autonomous driving vehicle to reach the destination without passing through the specific location, and in the case where the abnormality is a degradation in the performance of the remote support system, the alternative route is the route for the autonomous driving vehicle to reach the destination with a smaller number of the specific locations passed through than the number of the specific locations passed through in the first target route; in the case of finding the alternative route, changing the target route from the first target route to the alternative route; and controlling the autonomous driving vehicle.

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