AUTONOMOUS DRIVING SYSTEM, AUTONOMOUS DRIVING CONTROL METHOD, AND AUTONOMOUS DRIVING CONTROL PROGRAM

Abstract

To appropriately control an automatic driving vehicle when an abnormality occurs in a remote support system for providing remote support to the automatic driving vehicle.SOLUTION: An automatic driving system controls an automatic driving vehicle which is an object of remote support. Specific position information indicates specific positions where there is a possibility of the remote support being required. The automatic driving system sets a first target route as a target route to a destination. The automatic driving system determines whether there is an abnormality in a remote support system for providing the remote support to the automatic driving vehicle. When the abnormality in the remote support system is detected, the automatic driving system searches for an alternative route having a smaller number of the specific positions through which the automatic driving vehicle travels than the first target route, on the basis of the specific position information. When the alternative route is found, the automatic driving system changes the target route from the first target route to the alternative route.SELECTED DRAWING: Figure 5

Description

[Technical field]

[0001] The present disclosure relates to a technology for controlling an autonomous vehicle that is the target of remote assistance. [Background technology]

[0002] Patent Document 1 discloses a remote driving control device that remotely drives a vehicle. The remote driving control device remotely drives the vehicle by communicating with the vehicle. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2018-077649 A Summary of the Invention [Problem to be solved by the invention]

[0004] Consider remote assistance technology that remotely supports the driving of an autonomous vehicle. Remote assistance requires communication between a remote assistance device and the autonomous vehicle. A "remote assistance system" includes configurations and functions for providing remote assistance to an autonomous vehicle. For example, the remote assistance system includes a remote assistance device, a communication network, a communication device mounted on the autonomous vehicle, and the like. If an abnormality occurs in at least a part of the remote assistance system, it becomes impossible to provide remote assistance to the autonomous vehicle, or the accuracy of the remote assistance decreases.

[0005] One objective of the present disclosure is to provide a technology that can appropriately control an autonomous vehicle when an abnormality occurs in a remote assistance system that provides remote assistance to the autonomous vehicle. [Means for solving the problem]

[0006] The first aspect relates to an autonomous driving system that controls an autonomous vehicle that is the target of remote assistance. The automated driving system is one or more processors; one or more storage devices for storing specific location information indicating specific locations where remote assistance may be required; Equipped with. The one or more processors Set the first target route as the target route to the destination, Determine whether there are any abnormalities in the remote support system that provides remote support to autonomous vehicles, When an abnormality in the remote assistance system is detected, an alternative route is searched for based on the specific position information, the alternative route having a smaller number of specific positions through which the autonomous vehicle passes than the first target route; If an alternative route is found, the target route is changed from the first target route to the alternative route.

[0007] The second aspect relates to an autonomous driving control method for controlling an autonomous vehicle that is the target of remote assistance. The specific location information indicates a specific location where remote assistance may be required. The automatic driving control method is A process of setting a first target route as a target route to a destination; A process for determining whether or not there is an abnormality in a remote assistance system that provides remote assistance to an autonomous vehicle; When an abnormality in the remote assistance system is detected, a process of searching for an alternative route through which the autonomous vehicle passes, the alternative route including fewer specific positions than the first target route, based on the specific position information; If an alternative route is found, a process of changing the target route from the first target route to the alternative route is performed. Includes.

[0008] The third aspect relates to an autonomous driving control program that is executed by a computer and controls an autonomous vehicle that is the subject of remote assistance. The specific location information indicates a specific location where remote assistance may be required. The automatic driving control program is A process of setting a first target route as a target route to a destination; A process for determining whether or not there is an abnormality in a remote assistance system that provides remote assistance to an autonomous vehicle; When an abnormality in the remote assistance system is detected, a process of searching for an alternative route through which the autonomous vehicle passes, the alternative route including fewer specific positions than the first target route, based on the specific position information; If an alternative route is found, a process of changing the target route from the first target route to the alternative route is performed. to be executed by the computer. Effect of the Invention

[0009] According to the present disclosure, when an abnormality in the remote assistance system is detected, an alternative route is searched for that reduces the number of specific positions through which the autonomous vehicle passes compared to the first target route. When such an alternative route is found, the target route to the destination is changed from the first target route to the alternative route. Since the number of specific positions through which the autonomous vehicle passes is reduced, the probability that remote assistance is required is reduced overall. Thus, the probability that the autonomous vehicle can reach the destination is increased. Even when an abnormality in the remote assistance system is detected, there is no need to end autonomous driving near the current position. By performing a route change process, it is possible to continue autonomous driving as long as possible. This is preferable from the viewpoint of the continuity of autonomous driving. [Brief description of the drawings]

[0010] [Figure 1] 1 is a conceptual diagram illustrating a remote support system according to an embodiment of the present disclosure. [Diagram 2] FIG. 1 is a conceptual diagram for explaining an overview of remote support according to an embodiment of the present disclosure. [Diagram 3] FIG. 1 is a conceptual diagram for explaining an example of a specific position according to an embodiment of the present disclosure. [Figure 4] 1 is a conceptual diagram for explaining processing when an abnormality occurs in a remote support system according to an embodiment of the present disclosure. FIG. [Diagram 5] 11 is a conceptual diagram for explaining an example of processing when an abnormality occurs in a remote support system according to an embodiment of the present disclosure. FIG. [Figure 6] 11 is a conceptual diagram for explaining another example of processing when an abnormality occurs in the remote support system according to the embodiment of the present disclosure. FIG. [Figure 7] FIG. 11 is a conceptual diagram for explaining an example of a save process according to an embodiment of the present disclosure. [Figure 8] 1 is a conceptual diagram for explaining an example of a candidate stopping area according to an embodiment of the present disclosure. [Figure 9] 1 is a conceptual diagram for explaining an example of a high priority area and a low priority area according to an embodiment of the present disclosure. [Figure 10] 1 is a block diagram illustrating a configuration example of an autonomous driving system according to an embodiment of the present disclosure. FIG. [Figure 11] 2 is a block diagram showing an example of driving environment information according to an embodiment of the present disclosure. FIG. [Figure 12] 1 is a flowchart illustrating an example of processing by an autonomous driving system according to an embodiment of the present disclosure. [Figure 13] 11 is a flowchart showing a first example of step S300 according to an embodiment of the present disclosure. [Figure 14] 13 is a flowchart showing a second example of step S300 according to the embodiment of the present disclosure. [Figure 15] 13 is a flowchart showing a third example of step S300 according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Embodiments of the present disclosure will be described with reference to the accompanying drawings.

[0012] 1. Overview of remote support 1 is a conceptual diagram showing a remote assistance system according to the present embodiment. The remote assistance system includes an autonomous driving vehicle 1, a remote assistance device 2, and a communication network 3.

[0013] The autonomous vehicle 1 is a vehicle capable of autonomous driving. The autonomous driving here is assumed to be based on the premise that the driver does not necessarily have to concentrate 100% on driving (so-called autonomous driving of level 3 or higher). The autonomous vehicle 1 may be an autonomous vehicle of level 4 or higher that does not require a driver. The autonomous vehicle 1 is the target of remote assistance in this embodiment.

[0014] The remote assistance device 2 is a device for remotely assisting the autonomous vehicle 1, and is operated by a remote operator. The autonomous vehicle 1 and the remote assistance device 2 are communicably connected to each other via a communication network 3. The remote assistance device 2 communicates with the autonomous vehicle 1 via the communication network 3, and remotely assists the traveling of the autonomous vehicle 1. More specifically, the remote operator operates the remote assistance device 2 to remotely assist the traveling of the autonomous vehicle 1. It can also be said that the remote assistance device 2 is a device that assists the remote operator in remotely assisting the autonomous vehicle 1.

[0015] The communication network 3 includes a wireless base station, a wireless communication network, a wired communication network, etc. An example of the wireless communication network is a 5G network.

[0016] 2 is a conceptual diagram for explaining an overview of remote assistance according to the present embodiment. An autonomous driving system 10 controls an autonomous driving vehicle 1. During autonomous driving, the autonomous driving system 10 executes various vehicle processes. Representative vehicle processes during autonomous driving include the following:

[0017] (1) Recognition process: The autonomous driving system 10 uses a recognition sensor to recognize the situation around the autonomous driving vehicle 1. For example, the autonomous driving system 10 uses a camera to recognize the signal display of a traffic light (e.g., green light, yellow light, red light, right turn signal, etc.). (2) Action Determination Process: The autonomous driving system 10 determines whether or not to execute an action based on the result of the recognition process. Examples of actions include starting, stopping, turning right, turning left, changing lanes, and the like. (3) Timing Determination Process: The autonomous driving system 10 determines the execution timing for executing the above action.

[0018] Typically, situations where remote assistance by a remote operator is required are situations where autonomous driving is difficult. For example, remote assistance may be required at an intersection as shown in Figure 3.

[0019] For example, when sunlight is shining on a traffic light installed at an intersection, the accuracy of recognizing the traffic light display may decrease. If the traffic light display cannot be accurately determined by the recognition process, the autonomous driving system 10 requires remote support for the traffic light recognition. In addition, if the traffic light display cannot be determined, it is difficult to determine what action should be performed and when. Therefore, the autonomous driving system 10 requires remote support for the action determination process and the timing determination process.

[0020] Even if the signal display is identified, there may be a situation where it is difficult to determine whether or not an action can actually be executed. For example, even after the signal display from the autonomous driving system 10 indicates "right turn permitted," an oncoming vehicle may enter the intersection, or an oncoming vehicle or a preceding vehicle may remain in the intersection. In such a case, the autonomous driving system 10 may request remote assistance for the action determination process and timing determination process while remaining stopped.

[0021] As yet another example, a situation may be considered in which it is difficult to determine whether or not to change lanes when a construction section is present ahead of the autonomous vehicle 1. In this case, the autonomous vehicle system 10 may request remote assistance for the action determination process.

[0022] The autonomous driving system 10 may request a remote operator to remotely drive (remotely operate) the autonomous driving vehicle 1. In the present embodiment, "remote assistance" is a concept that includes not only assistance in at least one of the recognition process, the action determination process, and the timing determination process, but also remote driving (remote operation).

[0023] When it is determined that remote assistance is necessary, the autonomous driving system 10 transmits a remote assistance request REQ to the remote assistance device 2 via the communication network 3. The remote assistance request REQ is information requesting the remote operator to provide remote assistance for the autonomous driving vehicle 1. The remote assistance device 2 notifies the remote operator of the received remote assistance request REQ. In response to the remote assistance request REQ, the remote operator starts remote assistance for the autonomous driving vehicle 1.

[0024] During remote assistance, the autonomous driving system 10 transmits vehicle information VCL to the remote assistance device 2 via the communication network 3. The vehicle information VCL indicates the state of the autonomous driving vehicle 1, the surrounding circumstances, the results of vehicle processing by the autonomous driving system 10, etc. The remote assistance device 2 presents the vehicle information VCL received from the autonomous driving system 10 to the remote operator. For example, as shown in FIG. 2, the remote assistance device 2 displays image information IMG captured by a camera mounted on the autonomous driving vehicle 1 on a display device.

[0025] The remote operator provides remote assistance to the autonomously driven vehicle 1 while referring to the vehicle information VCL. The operator instruction INS is an instruction for the autonomously driven vehicle 1 input by the remote operator. The remote assistance device 2 accepts input of the operator instruction INS from the remote operator. Then, the remote assistance device 2 transmits the operator instruction INS to the autonomously driven vehicle 1 via the communication network 3. The autonomous driving system 10 receives the operator instruction INS from the remote assistance device 2, and controls the autonomously driven vehicle 1 in accordance with the received operator instruction INS.

[0026] 2. Handling abnormalities in the remote support system 2-1. Remote support system abnormality In this embodiment, the "remote assistance system 4" refers to configurations and functions for providing remote assistance to the autonomously driven vehicle 1. For example, the remote assistance system 4 includes a remote assistance device 2, a communication network 3, a communication device mounted on the autonomously driven vehicle 1, and the like (see FIG. 1). Examples of the communication device mounted on the autonomously driven vehicle 1 include a communication ECU (Electronic Control Unit), a communication module, a transmission / reception circuit, and the like.

[0027] Hereinafter, a case will be considered in which an “abnormality” occurs in at least a part of the remote assistance system 4 that provides remote assistance to the autonomously driven vehicle 1.

[0028] For example, an abnormality in 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, if a problem 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 (down) of the remote support device 2. Yet another example of a functional failure of the remote support system 4 is a failure of a communication device mounted on the autonomous vehicle 1. If a functional failure occurs in the remote support system 4, it will be impossible to provide remote support to the autonomous vehicle 1.

[0029] The abnormality of the remote support system 4 may include a "performance degradation" in which the function of the remote support system 4 is degraded. One example of a performance degradation of the remote support system 4 is a significant decrease in communication speed or throughput. Another example of a performance degradation of the remote support system 4 is a significant increase in communication delay. Yet another example of a performance degradation of the remote support system 4 is a decrease in the internal communication speed or calculation speed in the communication ECU mounted on the autonomous driving vehicle 1. When a performance degradation occurs in the remote support system 4, the accuracy of the remote support may decrease.

[0030] 2-2. Route change processing When an abnormality occurs in the remote assistance system 4, it becomes impossible to provide remote assistance to the autonomous vehicle 1, or the accuracy of the remote assistance decreases. However, it is not necessarily necessary to make an emergency stop of the autonomous vehicle 1 immediately after detecting an abnormality in the remote assistance system 4. This is because the autonomous driving system 10 can continue autonomous driving as usual in a situation where remote assistance is not required. In other words, there is no need to hastily end autonomous driving just because an abnormality in the remote assistance system 4 is detected. According to this embodiment, the autonomous driving system 10 continues autonomous driving as long as possible, taking into account the possibility that remote assistance will be required.

[0031] A location where remote assistance for the autonomous vehicle 1 may be required is hereinafter referred to as a "specific location PS." For example, the specific location PS is an intersection as shown in FIG. 3. As another example, the specific location PS may be a location outside an operational design domain (ODD), which is an area where autonomous driving is possible. As yet another example, the specific location PS may include a construction section, a congested section, an accident location, and the like. Typically, the specific location PS is registered in advance in map information. Alternatively, information on the specific location PS, such as a congested section or an accident location, may be acquired in real time.

[0032] FIG. 4 shows an example of the autonomous driving situation at the time when an abnormality in the remote assistance system 4 is detected. The current position and destination of the autonomous vehicle 1 are indicated by the symbols "P1" and "DST", respectively. A target route RT from the current position P1 of the autonomous vehicle 1 to the destination DST is set by the autonomous driving system 10. For convenience, the current target route RT is referred to as the "first target route RT1". The autonomous driving system 10 controls the autonomous vehicle 1 to head toward the destination DST along the first target route RT1.

[0033] At the time when an abnormality in the remote support system 4 is detected, a specific position PS exists on a first target route RT1 to the destination DST. In the example shown in FIG. 4, a plurality of specific positions PS1, PS2, and PS3 exist on the first target route RT1. In this case, the autonomous driving system 10 searches for an "alternative route RT2" different from the first target route RT1 as the target route RT to the destination DST. In particular, the autonomous driving system 10 searches for an alternative route RT2 in which the number of specific positions PS through which the autonomous vehicle 1 passes is smaller than that of the first target route RT1. When 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.

[0034] Fig. 5 is a conceptual diagram showing an example of the alternative route RT2. In the example shown in Fig. 5, the alternative route RT2 reaches the destination DST from the current position P1 without passing through the specific position PS. Because the alternative route RT2 does not pass through the specific position PS, the autonomous driving system 10 can continue autonomous driving as usual to the destination DST without requiring remote assistance. In other words, the autonomous driving vehicle 1 can reach the destination DST without being affected by an abnormality in the remote assistance system 4.

[0035] FIG. 6 is a conceptual diagram showing another example of the alternative route RT2. In the example shown in FIG. 6, the alternative route RT2 reaches the destination DST from the current position P1 via only one specific position PS1. That is, in the case of the alternative route RT2, the number of specific positions PS through which the autonomously driven vehicle 1 passes is fewer than in the case of the first target route RT1. Because the number of specific positions PS through which the autonomously driven vehicle 1 passes is reduced, the probability that remote assistance will be required decreases overall. Thus, the probability that the autonomously driven vehicle 1 can reach the destination DST increases.

[0036] In the example shown in Fig. 6, the specific position PS1 is a position where remote assistance may be required, but remote assistance is not necessarily required at the specific position PS1. If remote assistance is not required at the specific position PS1, the autonomous vehicle 1 can pass through the specific position PS1 by normal autonomous driving. Even if remote assistance is required at the specific position PS1, if the abnormality in the remote assistance system 4 is "performance degradation," remote assistance is possible, albeit slowly.

[0037] 2-3. Evacuation process If the alternative route RT2 cannot be found, the autonomous driving system 10 may execute an "evacuation process" to safely evacuate the autonomous driving vehicle 1.

[0038] Fig. 7 is a conceptual diagram for explaining an example of the evacuation process. The "target evacuation position PE" is a target stopping position when the autonomously driven vehicle 1 is stopped by the evacuation process. Preferably, the target evacuation position PE is set to a safe position on the road. In the example shown in Fig. 7, the target evacuation position PE is set to the shoulder of the road.

[0039] The autonomous driving system 10 sets a target evacuation position PE from within the first target route RT1. Then, the autonomous driving system 10 controls the autonomous driving vehicle 1 so that it travels toward the target evacuation position PE and stops at the target evacuation position PE. For example, the autonomous driving system 10 generates a target trajectory TR such that the autonomous driving vehicle 1 travels from a current position toward the target evacuation position PE and stops at the target evacuation position PE. Then, the autonomous driving system 10 controls the travel of the autonomous driving vehicle 1 so that the autonomous driving vehicle 1 follows the target trajectory TR.

[0040] The area that can be used as the target evacuation position PE in the evacuation process may be determined in advance. The area that can be used as the target evacuation position PE in the evacuation process will be referred to as a "candidate stopping area AC" hereinafter.

[0041] FIG. 8 is a conceptual diagram for explaining an example of a candidate stopping area AC. To explain the candidate stopping area AC, first, a "no stopping area AX" will be explained. The no stopping area AX is an area where parking and stopping of vehicles is prohibited, and is determined in advance by the Road Traffic Act and the like. In the example shown in FIG. 8, the no stopping area AX includes a crosswalk and an area of ​​a predetermined width around it. The no stopping area AX may also include an intersection and an area of ​​a predetermined width around it. In addition, the area in front of firefighting equipment and the like is also included in the no stopping area AX.

[0042] The stop candidate area AC is selected from among areas on the road other than the no-stopping area AX. Typically, the stop candidate area AC is a part of an area other than the no-stopping area AX. For example, the stop candidate area AC is selected from the perspective of ensuring the safety of the stopped autonomous vehicle 1. As illustrated in FIG. 8, the stop candidate area AC may be an area relatively close to the edge of the road. Preferably, the stop candidate area AC is set to include a road shoulder or a shoulder strip.

[0043] As shown in Fig. 9, priorities may be set for the stop candidate areas AC. A high priority area ACH is a stop candidate area AC with a relatively high priority, and a low priority area ACL is a stop candidate area AC with a relatively low priority. In the example shown in Fig. 9, straight sections are set as high priority areas ACH, and curved sections are set as low priority areas ACL.

[0044] The stop candidate areas AC and the no-stop areas AX are, for example, registered in advance in map information. In the evacuation process, it is preferable that the autonomous driving system 10 sets the target evacuation position PE so that it is included in the stop candidate areas AC. When priorities are set for the stop candidate areas AC, the autonomous driving system 10 sets the target evacuation position PE so that it is included in the stop candidate areas AC with the highest priority.

[0045] 2-4.Effects As described above, according to the present embodiment, when an abnormality in the remote assistance system 4 is detected, an alternative route RT2 is searched for that reduces the number of specific positions PS through which the autonomous vehicle 1 passes compared to 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 vehicle 1 passes is reduced, the probability that remote assistance is required is reduced overall. Thus, the probability that the autonomous vehicle 1 can reach the destination DST is increased. Even when an abnormality in the remote assistance system 4 is detected, it is not necessary to end autonomous driving in the vicinity of the current position P1. By performing a route change process, it is possible to continue autonomous driving as long as possible. This is preferable from the viewpoint of the continuity of autonomous driving.

[0046] An alternative route RT2 may be searched for that reaches the destination DST without passing through the specific position PS. In this case, since there is no opportunity for remote assistance to be required, the autonomous vehicle 1 can continue normal autonomous driving to the destination DST. In other words, the autonomous vehicle 1 can reach the destination DST without being affected by an abnormality in the remote assistance system 4.

[0047] The autonomous driving system 10 according to this embodiment will be described in more detail below.

[0048] 3. Examples of autonomous driving systems 3-1. Configuration example 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 arranged in an external device outside the autonomous driving vehicle 1, and may remotely control the autonomous driving vehicle 1. In other words, the autonomous driving system 10 may be arranged in a distributed manner between the autonomous driving vehicle 1 and the external device.

[0049] 10 is a block diagram showing an example of the configuration of an autonomous driving system 10 according to this embodiment. The autonomous driving system 10 includes a sensor group 20, a driving device 30, a communication device 40, and a control device 100.

[0050] The sensor group 20 is mounted on the autonomously driven vehicle 1. The sensor group 20 includes a vehicle state sensor, a recognition sensor, a position sensor, etc. The vehicle state sensor detects the state of the autonomously driven vehicle 1. Examples of the vehicle state sensor include a vehicle speed sensor, a yaw rate sensor, a lateral acceleration sensor, a steering angle sensor, etc. The recognition sensor detects the situation around the autonomously driven vehicle 1. Examples of the recognition sensor include a camera, a LIDAR (Laser Imaging Detection and Ranging), a radar, etc. The position sensor detects the position and orientation of the autonomously driven vehicle 1. Examples of the position sensor include a GPS (Global Positioning System) sensor.

[0051] The traveling device 30 is mounted on the autonomously driven vehicle 1. The traveling device 30 includes a steering device, a drive device, and a braking device. The steering device steers the wheels. For example, the steering device includes an electric power steering (EPS) device. The drive device is a power source that generates a driving force. Examples of the drive device include an engine, an electric motor, and an in-wheel motor. The braking device generates a braking force.

[0052] The communication device 40 communicates with the outside of the autonomous driving vehicle 1. For example, the communication device 40 communicates with the remote assistance device 2 via the communication network 3 (see Figures 1 and 2). The communication device 40 may communicate with a management server. The communication device 40 may perform V2I communication (road-to-vehicle communication) with surrounding infrastructure. The communication device 40 may perform V2V communication (vehicle-to-vehicle communication) with surrounding vehicles. The communication device 40 includes a communication ECU (Electronic Control Unit), a communication module, a transmission / reception circuit, etc.

[0053] The control device 100 controls the autonomous vehicle 1. The control device 100 includes one or more processors 110 (hereinafter simply referred to as processor 110) and one or more storage devices 120 (hereinafter simply referred to as storage devices 120). The processor 110 executes 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, a HDD (Hard Disk Drive), and an SSD (Solid State Drive). The control device 100 may include one or more ECUs. A part of the control device 100 may be an information processing device external to the autonomous vehicle 1.

[0054] The autonomous driving control program PROG is a computer program for controlling the autonomous driving vehicle 1. The processor 110 executes the autonomous driving control program PROG to realize various processes by the control device 100. The autonomous driving control program PROG is stored in the storage device 120. Alternatively, the autonomous driving control program PROG may be recorded in a computer-readable recording medium.

[0055] 3-2. Driving environment information The driving environment information 200 indicates the driving environment of the autonomously driven vehicle 1. The driving environment information 200 is stored in the storage device 120.

[0056] 11 is a block diagram showing an example of driving environment information 200. The driving environment information 200 includes map information 210, specific position information 220, evacuation area information 230, vehicle state information 240, surrounding situation information 250, vehicle position information 260, and delivery information 270.

[0057] The map information 210 includes a general navigation map. The map information 210 may indicate lane arrangements, road shapes, etc. The map information 210 may include location information of traffic lights, signs, etc. The processor 110 acquires map information of a required area from a map database. The map database may be stored in a predetermined storage device mounted on the autonomously driven vehicle 1, or may be stored in an external management server. In the latter case, the processor 110 communicates with the management server to acquire the required map information.

[0058] The specific location information 220 indicates a specific location PS where remote assistance for the autonomous vehicle 1 may be required. For example, the specific location information 220 is created in advance. The specific location information 220 may be included in the map information 210. As described below, the specific location information 220 may be added in real time.

[0059] The evacuation area information 230 indicates the locations of the stop candidate areas AC and the stop prohibition areas AX (see FIG. 8). The evacuation area information 230 may indicate the priority of the stop candidate areas AC (see FIG. 9). The evacuation area information 230 is created in advance. The evacuation area information 230 may be included in the map information 210.

[0060] The vehicle state information 240 is information that indicates the state of the autonomously driven vehicle 1. The processor 110 acquires the vehicle state information 240 from a vehicle state sensor.

[0061] The surrounding situation information 250 is information that indicates the situation around the autonomous vehicle 1. The processor 110 acquires the surrounding situation information 250 using a recognition sensor. For example, the surrounding situation information 250 includes image information IMG captured by a camera. The surrounding situation information 250 further includes object information related to objects around the autonomous vehicle 1. Examples of objects include pedestrians, bicycles, other vehicles (preceding vehicles, parked vehicles, etc.), road configurations (white lines, curbs, guardrails, walls, median strips, roadside structures, etc.), signs, obstacles, etc. The object information indicates the relative position and relative speed of the object with respect to the autonomous vehicle 1.

[0062] The vehicle position information 260 is information indicating the position of the autonomous driving vehicle 1. The processor 110 acquires the vehicle position information 260 from a detection result by a position sensor. The processor 110 may also acquire highly accurate vehicle position information 260 by a well-known self-position estimation process (Localization) using object information and map information 210.

[0063] The distributed information 270 includes road traffic information, construction section information, traffic regulation information, etc. The processor 110 receives the distributed information 270 via the communication device 40 from an information providing server or roadside infrastructure.

[0064] The processor 110 can grasp the construction section, the congested section, the location of the accident, and the like based on the distributed information 270. In this case, the processor 110 may add the construction section, the congested section, the location of the accident, and the like to the specific location information 220.

[0065] 3-3. Vehicle driving control, automatic driving control The processor 110 executes "vehicle driving control" that controls the driving of the autonomously driven vehicle 1. The vehicle driving control includes steering control, acceleration control, and deceleration control. The processor 110 executes vehicle driving control by controlling the driving device 30 (steering device, drive device, braking device). Specifically, the processor 110 executes steering control by controlling the steering device. The processor 110 also executes acceleration control by controlling the drive device. The processor 110 also executes deceleration control by controlling the braking device.

[0066] The processor 110 also 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 the map information 210, etc. Then, the processor 110 performs vehicle travel control based on the driving environment information 200 so that the autonomous vehicle 1 heads toward the destination DST along the target route RT.

[0067] More specifically, the processor 110 generates a driving plan for the autonomous vehicle 1 based on the driving environment information 200. The driving plan includes maintaining the current driving lane, changing lanes, avoiding obstacles, and the like. Furthermore, the processor 110 generates a target trajectory TR required for the autonomous vehicle 1 to drive according to the driving plan. The target trajectory TR includes a target position and a target speed. Then, the processor 110 executes vehicle driving control so that the autonomous vehicle 1 follows the target route RT and the target trajectory TR.

[0068] 3-4. Processing related to remote support During the autonomous driving, the processor 110 judges whether remote assistance by a remote operator is necessary. Typically, a situation in which remote assistance by a remote operator is necessary is a situation in which autonomous driving is difficult. For example, when at least one of the above-mentioned recognition process, action determination process, and timing determination process is difficult, the processor 110 judges that remote assistance by a remote operator is necessary.

[0069] When determining that remote assistance is necessary, the processor 110 transmits a remote assistance request REQ to the remote assistance device 2 via the communication device 40. The remote assistance request REQ requests remote assistance of the autonomously driven vehicle 1 from the remote operator.

[0070] Moreover, the processor 110 transmits the vehicle information VCL to the remote assistance device 2 via the communication device 40. The vehicle information VCL includes at least a part 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 include vehicle state information 240 and vehicle position information 260. The vehicle information VCL may include results of a recognition process, an action determination process, and a timing determination process.

[0071] Furthermore, the processor 110 receives an operator instruction INS from the remote assistance device 2 via the communication device 40. The operator instruction INS is an instruction for the autonomously driven vehicle 1 input by a remote operator. When the processor 110 receives the operator instruction INS, the processor 110 performs vehicle driving control in accordance with the received operator instruction INS.

[0072] 4. Processing flow when an abnormality occurs in the remote support system Fig. 12 is a flowchart showing an example of processing by the autonomous driving system 10 according to this embodiment. In particular, Fig. 12 shows a processing flow related to when an abnormality occurs in the remote assistance system 4.

[0073] 4-1. Step S100 In step S100, the processor 110 determines whether or not there is an abnormality in the remote assistance system 4 that provides remote assistance to the autonomous driving vehicle 1. For example, the remote assistance system 4 includes the remote assistance device 2, the communication network 3, and the communication device 40 of the autonomous driving system 10.

[0074] An abnormality in the remote support system 4 includes a "functional failure" in which the function of the remote support system 4 is lost. 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., communication ECU) of the autonomous driving system 10 has a self-diagnosis function. The self-diagnosis function enables the processor 110 to detect a functional failure of the communication device 40.

[0075] The abnormality of the remote support system 4 may include a performance degradation in which the function of the remote support system 4 is degraded. For example, the processor 110 monitors the communication status with the remote support device 2 (e.g., throughput, communication speed, communication delay). If the throughput or communication speed falls below a threshold, the processor 110 determines that a performance degradation of the remote support system 4 has occurred. As another example, if the communication delay exceeds a threshold, the processor 110 determines that a performance degradation of the remote support system 4 has occurred.

[0076] If no abnormality is detected in the remote support system 4 (step S100; No), the process in the current cycle 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.

[0077] 4-2. Step S200 In step S200, the processor 110 determines whether or not a specific position PS exists on a first target route RT1 from the current position P1 to the destination DST. The first target route RT1 is set and grasped by the processor 110. The specific position PS is obtained from the specific position information 220. Therefore, the processor 110 can determine whether or not a specific position PS exists on the first target route RT1 based on the specific position information 220.

[0078] If the specific position PS exists on the first target route RT1 (step S200; 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; No), the process in this cycle ends.

[0079] 4-3. Step S300 In step S300, the processor 110 searches for an alternative route RT2 different from the first target route RT1 as a target route RT to the destination DST. In particular, the processor 110 searches for an alternative route RT2 that has a smaller number of specific positions PS through which the autonomously driven vehicle 1 passes 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 position information 220.

[0080] 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. Below, some examples of step S300 will be described.

[0081] 4-3-1. First example FIG. 13 is a flowchart showing a first example of step S300.

[0082] In step S320, the processor 110 searches for an alternative route RT2 that reaches the destination DST from the current position P1 without passing through the specific position PS. If such an alternative route RT2 is found (step S320; Yes), the process proceeds to step S400. On the other hand, if such an alternative route RT2 is not found (step S320; No), the process proceeds to step S600.

[0083] According to the first example, it is possible to search for an alternative route RT2 that is not affected by an abnormality in the remote support system 4.

[0084] 4-3-2. Second example 14 is a flowchart showing a second example of step S300. Step S320 is similar to the first example. If an alternative route RT2 that does not pass through the specific position PS is not found (step S320; No), the process proceeds to step S330.

[0085] In step S330, processor 110 searches for an alternative route RT2 that has fewer specific positions PS passed by autonomous vehicle 1 than first target route RT1. If such an alternative route RT2 is found (step S330; Yes), processing proceeds to step S400. On the other hand, if such an alternative route RT2 is not found (step S330; No), processing proceeds to step S600.

[0086] According to the second example, it is possible to widen the selection range of the alternative route RT2, that is, it is possible to ease the conditions imposed on the alternative route RT2.

[0087] 4-3-3.Third example FIG. 15 is a flowchart showing a third example of step S300.

[0088] In step S310, the processor 110 determines whether the abnormality in the remote support system 4 is a malfunction or a deterioration in performance.

[0089] If the abnormality in the remote support system 4 is a malfunction (step S310; Yes), the process proceeds to step S320. Step S320 and subsequent steps are the same as in the first example described above.

[0090] On the other hand, if the abnormality of the remote support system 4 is a performance degradation (step S320; No), the process proceeds to step S330. Step S330 and subsequent steps are the same as in the second example. Note that the alternative route RT2 here also includes an alternative route RT2 that does not pass through the specific position PS.

[0091] According to the third example, when the abnormality of the remote support system 4 is a performance degradation, it is possible to widen the selection range of the alternative route RT2. In other words, when the abnormality of the remote support system 4 is a performance degradation, it is possible to relax the conditions imposed on the alternative route RT2.

[0092] 4-4. Step S400 In step S400, the processor 110 performs a route change process. Specifically, the processor 110 changes the target route RT to the destination DST from the first target route RT1 to an alternative route RT2. After that, the process proceeds to step S500.

[0093] 4-5. Step S500 In step S500, the processor 110 performs vehicle driving control based on the driving environment information 200 so that the autonomously driven vehicle 1 heads toward the destination DST along the alternative route RT2.

[0094] 4-6. Step S600 In step S600, processor 110 executes evacuation processing to safely evacuate autonomous vehicle 1.

[0095] Specifically, the processor 110 sets the target evacuation position PE on the first target route RT1. At this time, the processor 110 sets the target evacuation position PE so that the autonomous vehicle 1 can realistically stop based on the current position P1, vehicle speed, driving performance, and the like of the autonomous vehicle 1. The processor 110 may further refer to the evacuation area information 230. The evacuation area information 230 indicates the positions of the stop candidate areas AC and the stop prohibition areas AX. The processor 110 sets the target evacuation position PE in the stop candidate areas AC included in the evacuation margin section XE, avoiding the stop prohibition areas AX. The evacuation area information 230 may indicate the priority of the stop candidate areas AC. In that case, the processor 110 sets the target evacuation position PE so as to be included in the stop candidate areas AC with the highest possible priority.

[0096] Then, the processor 110 performs vehicle driving control so that the autonomously driven vehicle 1 travels toward the target evacuation position PE and stops at the target evacuation position PE. For example, the processor 110 generates a target trajectory TR such that the autonomously driven vehicle 1 travels from the current position P1 toward the target evacuation position PE and stops at the target evacuation position PE. Then, the autonomous driving system 10 performs vehicle driving control so that the autonomously driven vehicle 1 follows the target trajectory TR (see FIG. 7). [Explanation of symbols]

[0097] 1. Self-driving vehicles 2. Remote Support Devices 3. Communication Network 4. Remote Support 10 Autonomous Driving Systems 20 Sensor Group 30 Running gear 40 Communication Equipment 100 Control device 110 Processor 120 Storage device 200 Driving Environment Information 210 Map Information 220 Specific location information 230 Evacuation Area Information 240 Vehicle status information 250 Surrounding Area Information 260 Vehicle location information 270 Distribution Information DST destination P1 Current position PE target evacuation position PS specific position RT Target Route RT1 First target route RT2 Alternative Route PROG Automatic driving control program

Claims

1. An autonomous driving system for controlling an autonomous vehicle that is a target of remote assistance, one or more processors; one or more storage devices for storing specific location information indicating specific locations where the remote assistance may be required; Equipped with The one or more processors: A first target route is set as a target route to a destination, determining whether or not there is an abnormality in a remote assistance system that provides the remote assistance to the autonomous vehicle; When the abnormality in the remote assistance system is detected before the remote assistance is required, searching for an alternative route through which the autonomous vehicle passes through fewer specific positions than the first target route based on the specific position information; When the alternative route is found, the target route is changed from the first target route to the alternative route. Autonomous driving system.

2. The automated driving system according to claim 1, The one or more processors search for the alternative route to reach the destination without passing through the specific location based on the specific location information. Autonomous driving system.

3. The automated driving system according to claim 1, When the abnormality of the remote support system is a malfunction, the one or more processors search for the alternative route to reach the destination without passing through the specific location based on the specific location information. Autonomous driving system.

4. The automated driving system according to claim 1, When the abnormality of the remote assistance system is a performance degradation, the one or more processors search for the alternative route in which the autonomous vehicle passes through a smaller number of specific positions than the first target route, based on the specific position information. Autonomous driving system.

5. The automatic driving system according to any one of claims 1 to 4, If the alternative route is not found, the one or more processors set a target evacuation position on the first target route and control the autonomous vehicle to stop at the target evacuation position. Autonomous driving system.

6. An autonomous driving control method for controlling an autonomous driving vehicle that is a target of remote assistance, the specific location information indicating a specific location where the remote assistance may be required; The automatic driving control method includes: A process of setting a first target route as a target route to a destination; A process of determining whether or not there is an abnormality in a remote assistance system that provides the remote assistance to the autonomous driving vehicle; When the abnormality in the remote assistance system is detected before the remote assistance is required, a process of searching for an alternative route through which the autonomous vehicle passes, the alternative route including fewer specific positions than the first target route, based on the specific position information; When the alternative route is found, a process of changing the target route from the first target route to the alternative route; Includes Autonomous driving control method.

7. An autonomous driving control program that is executed by a computer and controls an autonomous driving vehicle that is a target of remote assistance, the specific location information indicating a specific location where the remote assistance may be required; The automatic driving control program includes: A process of setting a first target route as a target route to a destination; A process of determining whether or not there is an abnormality in a remote assistance system that provides the remote assistance to the autonomous driving vehicle; When the abnormality in the remote assistance system is detected before the remote assistance is required, a process of searching for an alternative route through which the autonomous vehicle passes, the alternative route including fewer specific positions than the first target route, based on the specific position information; When the alternative route is found, a process of changing the target route from the first target route to the alternative route; causing the computer to execute Autonomous driving control program.

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