Vehicle control system and vehicle control method

Abstract

The present invention relates to a vehicle control system and a vehicle control method. A processor of a vehicle is configured to determine whether remote assistance from a remote facility is required during an autonomous driving control. The processor is configured to: in a case where it is determined that remote assistance is required, generate a target trajectory of a vehicle waiting at a predetermined position. The waiting predetermined position represents a predetermined position waiting for reception of an assistance signal from the remote facility. The processor is configured to calculate a driving efficiency level indicating a degree of driving efficiency required for the vehicle, and is configured to calculate a request timing for sending a request signal for remote assistance to the remote facility based on the driving efficiency level. The processor is configured to: in the calculation of the request timing, output a late timing in a case where the driving efficiency level is low.

Description

Technical Field

[0001] The present invention relates to a vehicle control system and a vehicle control method for a vehicle that receives remote assistance from a remote facility during the process of autonomous driving control. Background Art

[0002] Japanese Patent Application Laid-Open No. 2018-77649 discloses a system for remotely driving a vehicle that performs autonomous driving. The system includes a management facility where an operator who performs remote driving (manual driving) is stationed. The management facility receives a remote operation request from the vehicle. The remote operation request is sent, for example, when it becomes difficult to execute the system-based autonomous driving. At the start of remote driving, the management facility determines driving suitability conditions such as the driving proficiency and wakefulness of the operator. When it is determined that the driving suitability conditions are satisfied, the system-based autonomous driving is temporarily stopped, and the operation subject of the vehicle is switched from the system to the operator.

[0003] In a vehicle performing autonomous driving control, it is expected that there is no driver of the vehicle or the driving skill of the driver is low. Therefore, if the vehicle can be remotely operated, it is expected that remote operation requests will be frequently issued during the process of autonomous driving control. However, the human resources of the operator are also limited. Therefore, if remote operation requests are frequently issued at the same time, it becomes difficult to handle all of these requests. In this way, the vehicle will continuously stop on the road waiting for remote operation, which will obstruct traffic, so it is not ideal. Therefore, there is a need to develop a technology for preventing such a situation from occurring. Summary of the Invention

[0004] The present invention provides a technology capable of suppressing the frequency of sending remote operation requests from a vehicle performing autonomous driving control.

[0005] A first aspect of the present invention is a vehicle control system for a vehicle configured to receive remote assistance from a remote facility during autonomous driving control. The vehicle control system includes a memory and a processor. Driving environment data of the vehicle is stored in the memory. The processor is configured to generate a target trajectory of the vehicle based on the driving environment data. The processor is configured to perform the autonomous driving control based on the target trajectory. The processor is configured to perform the following operations as the autonomous driving control: determine whether remote assistance is required based on at least one of the driving environment data and the target trajectory; in a case where it is determined that remote assistance is required, generate a target trajectory including a waiting predetermined position, where the waiting predetermined position represents a predetermined position for waiting for reception of an assistance signal from the remote facility; calculate a driving efficiency level representing a degree of driving efficiency required for the vehicle based on the driving environment data; calculate a request timing for sending a request signal for the remote assistance to the remote facility based on the driving efficiency level; and send the request signal to the remote facility when the request timing arrives. The processor is configured to: in the calculation of the request timing, output a later timing in a case where the driving efficiency level is low. The later timing is later than an earlier timing, and the earlier timing is a timing in a case where the driving efficiency level is high.

[0006] According to the above first aspect, in a case where it is determined that remote assistance is required, the request timing is calculated based on the driving efficiency level. In the calculation of the request timing, a later timing is output in a case where the driving efficiency level is low than in a case where the driving efficiency level is high. Therefore, in a case where the driving efficiency level is low, the request timing can be delayed. If the request timing is delayed, it is expected that: during the period before the request timing arrives, the driving environment of the vehicle changes and the determination result that remote assistance is required changes. Then, if the determination result changes, the request signal is not sent either. Therefore, the transmission frequency of the request signal can be suppressed.

[0007] In the first aspect, it may be that the vehicle control system further includes a database. It may be that map data is stored in the database. It may be that the processor is configured to perform the following operations in the autonomous driving control: calculate a waiting time for waiting for an assistance signal from the remote facility at the waiting predetermined position based on the driving efficiency level; determine whether the waiting time exceeds a permissible time; in a case where it is determined that the waiting time exceeds the permissible time, determine whether the waiting predetermined position is suitable as a temporary stop position based on at least one of the driving environment data and the map data; and generate a target trajectory in which the waiting predetermined position is corrected in a case where it is determined that the waiting predetermined position is not suitable as the temporary stop position.

[0008] According to the above configuration, when it is determined that the waiting time calculated based on the driving efficiency level exceeds the allowable time, it is determined whether the waiting predetermined position is suitable as a temporary stop position. Then, when it is determined that the waiting predetermined position is not suitable as a temporary stop position, a target trajectory in which the waiting predetermined position is corrected is generated. Therefore, a target trajectory including a waiting predetermined position suitable as a temporary stop position can be generated. The waiting time is the time for waiting for an auxiliary signal from a remote facility at the waiting predetermined position. Therefore, the longer the waiting time, the more the temporary stop of the vehicle will obstruct traffic. When the waiting time exceeds the allowable time, a target trajectory including a suitable waiting predetermined position is generated, so that such an adverse situation can be prevented from occurring.

[0009] In the first aspect, it may also be that the driving environment data has the external condition data of the vehicle. It may also be that the processor is configured to: in the calculation of the driving efficiency level, when the external condition data includes the identification data of the following vehicle of the vehicle, output a high level. It may also be that the high level is higher than the low level, and it may also be that the low level is the level when the external condition data does not include the identification data of the following vehicle of the vehicle.

[0010] In the first aspect, it may also be that the driving environment data has the internal condition data of the vehicle. It may also be that the processor is configured to: in the calculation of the driving efficiency level, when the internal condition data includes the boarding data indicating that there is a passenger in the vehicle, output a high level. It may also be that the high level is higher than the low level, and it may also be that the low level is the level when the internal condition data does not include the boarding data indicating that there is a passenger in the vehicle.

[0011] In the first aspect, it may also be that the driving environment data has the internal condition data of the vehicle. It may also be that the internal condition data has the data of the remaining driving range of the vehicle. It may also be that the processor is configured to: in the calculation of the driving efficiency level, the shorter the remaining driving range, the higher the level output.

[0012] In the first aspect, it may also be that the driving environment data has the working condition data of the passenger transportation service provided by the vehicle. It may also be that the working condition data has the data of the delay time of the transportation service relative to the scheduled operation time. It may also be that the processor is configured to: in the calculation of the driving efficiency level, the longer the delay time, the higher the level output.

[0013] In the first solution, alternatively, the driving environment data may include the operating condition data of the passenger transportation service provided by the vehicle. Alternatively, the operating condition data may include the data of the remuneration paid by the passenger for the transportation service. Alternatively, the processor is configured to: in the calculation of the driving efficiency level, the higher the remuneration, the higher the level output.

[0014] In the first solution, alternatively, the driving environment data may include the traffic condition data in the route from the current location of the vehicle to the destination. Alternatively, the processor is configured to: in the calculation of the driving efficiency level, when the traffic condition data includes the data of congestion occurring on the route, output a high level. Alternatively, the high level is higher than the low level, and the low level is the level when the traffic condition data does not include the data of congestion occurring on the route.

[0015] According to the above configuration, the driving efficiency level can be calculated based on various data included in the driving environment data.

[0016] The second solution of the present invention is a vehicle control method for a vehicle configured to receive remote assistance from a remote facility during the process of autonomous driving control. The vehicle control method is executed by a processor of the vehicle. The processor is configured to generate a target trajectory of the vehicle based on the driving environment data of the vehicle, and is configured to perform the autonomous driving control based on the target trajectory. The vehicle control method includes: determining whether remote assistance is required based on at least one of the driving environment data and the target trajectory; when it is determined that remote assistance is required, generating a target trajectory including a waiting predetermined position, where the waiting predetermined position represents a predetermined position for waiting for the reception of an assistance signal from the remote facility; calculating a driving efficiency level representing the degree of driving efficiency required for the vehicle based on the driving environment data; calculating a request timing for sending a request signal for the remote assistance to the remote facility based on the driving efficiency level; when the request timing arrives, sending the request signal to the remote facility; and in the calculation of the request timing, when the driving efficiency level is low, outputting a late timing, where the late timing is later than an early timing, and the early timing is the timing when the driving efficiency level is high.

[0017] According to the second solution described above, when it is determined that remote assistance is required, the request timing is calculated based on the driving efficiency level. In the calculation of the request timing, when the driving efficiency level is low, a timing later than the case where the driving efficiency level is high is output. Therefore, when the driving efficiency level is low, the request timing can be delayed. If the request timing is delayed, it is expected that during the period before the arrival of this request timing, the driving environment of the vehicle changes and the determination result that remote assistance is required changes. Then, if the determination result changes, the request signal is not sent either. Therefore, the transmission frequency of the request signal can be suppressed.

[0018] In the second solution, it may also be that the vehicle control method includes the following operations performed by the processor: calculating, based on the driving efficiency level, the waiting time for waiting for an assistance signal from the remote facility at the waiting predetermined position; determining whether the waiting time exceeds the allowable time; when it is determined that the waiting time exceeds the allowable time, determining whether the waiting predetermined position is suitable as a temporary stop position based on at least one of the driving environment data and the map data stored in the database; and when it is determined that the waiting predetermined position is not suitable as the temporary stop position, generating a target trajectory in which the waiting predetermined position is corrected.

[0019] According to the above configuration, when it is determined that the waiting time calculated based on the driving efficiency level exceeds the allowable time, it is determined whether the waiting predetermined position is suitable as a temporary stop position. Then, when it is determined that the waiting predetermined position is not suitable as the temporary stop position, a target trajectory in which the waiting predetermined position is corrected is generated. Therefore, a target trajectory including a waiting predetermined position suitable as a temporary stop position can be generated. The waiting time is the time for waiting for an assistance signal from the remote facility at the waiting predetermined position. Therefore, the longer the waiting time, the more the temporary stop of the vehicle will obstruct traffic. When the waiting time exceeds the allowable time, a target trajectory including a suitable waiting predetermined position is generated, so that such an adverse situation can be avoided preventively. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] 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 represent the same elements, and:

[0021] Figure 1 FIG. is a diagram showing a configuration example of a remote assistance system to which the vehicle control system of the first embodiment is applied.

[0022] Figure 2 FIG. is a diagram showing a first transmission example of a request signal for remote assistance transmitted from a vehicle during the process of autonomous driving control.

[0023] Figure 3 It is a diagram showing a second example of the transmission of a request signal sent from a vehicle during autonomous driving control.

[0024] Figure 4 It is for Figure 2 a diagram explaining the disadvantages in the case where the transmission timing of the request signal is delayed in the first transmission example shown.

[0025] Figure 5 It is for Figure 3 a diagram explaining the advantages in the case where the transmission timing of the request signal is delayed in the second transmission example shown.

[0026] Figure 6 It is a diagram showing an example of the relationship between the driving efficiency level and the time of waiting for the reception of an assistance signal at a waiting predetermined position.

[0027] Figure 7 It is showing Figure 1 a block diagram of a configuration example of the vehicle shown.

[0028] Figure 8 It is a diagram showing an example of driving environment data.

[0029] Figure 9 It is showing Figure 1 a block diagram of a configuration example of the remote facility shown.

[0030] Figure 10 It is showing Figure 7 a block diagram of a functional configuration example of the vehicle control device shown.

[0031] Figure 11 It is a flowchart showing an example of the processing performed by the vehicle control device (processor) during autonomous driving control in the first embodiment.

[0032] Figure 12 It is a diagram explaining the outline of the second embodiment.

[0033] Figure 13 It is a block diagram showing a functional configuration example of the control device included in the vehicle control system of the second embodiment.

[0034] Figure 14 It is a flowchart showing an example of the processing performed by the vehicle control device (processor) during autonomous driving control in the second embodiment. Detailed Embodiments

[0035] Hereinafter, with reference to the accompanying drawings, a vehicle control system according to an embodiment of the present invention will be described. It should be noted that the vehicle control method according to the embodiment is implemented by computer processing performed in the vehicle control system according to the embodiment. In addition, in the respective drawings, the same or corresponding parts are denoted by the same reference numerals, and the description thereof is simplified or omitted.

[0036] 1. First Embodiment

[0037] First, with reference to Figures 1 to 11 a first embodiment of the present invention will be described.

[0038] 1-1. Outline of the First Embodiment

[0039] 1-1-1. Remote Assistance

[0040] Figure 1 FIG. is a diagram showing a configuration example of a remote assistance system to which the vehicle control system according to the first embodiment is applied. Figure 1 The remote assistance system 1 shown includes a vehicle 2 and a remote facility 3 that communicates with the vehicle 2. Communication between the vehicle 2 and the remote facility 3 is performed via a network 4. In this communication, communication data COM2 is transmitted from the vehicle 2 to the remote facility 3. On the other hand, communication data COM3 is transmitted from the remote facility 3 to the vehicle 2.

[0041] The vehicle 2 is, for example, an automobile powered by an internal combustion engine such as a diesel engine or a gasoline engine, an electric vehicle powered by an electric motor, or a hybrid vehicle equipped with an internal combustion engine and an electric motor. The electric motor is driven by a battery such as a secondary battery, a hydrogen fuel cell, a metal fuel cell, or an alcohol fuel cell.

[0042] The driving of the vehicle 2 is performed by the vehicle control system according to the first embodiment. The vehicle control system performs, for example, vehicle control for assisting manual driving performed by the driver of the vehicle 2 or vehicle control for performing autonomous driving of the vehicle 2. The former is collectively referred to as driving assistance control, and the latter is collectively referred to as autonomous driving control. As driving assistance control, collision avoidance control and lane departure suppression control can be exemplified. The collision avoidance control assists in avoiding collisions between the vehicle 2 and surrounding objects. The lane departure suppression control suppresses the vehicle 2 from deviating from the driving lane.

[0043] In the first embodiment, a case where autonomous driving control based on the target trajectory of the vehicle 2 is considered is taken into account. The target trajectory is configured as a set of target positions of the vehicle 2 at respective future reference timings set at a prescribed time interval. The target trajectory may also include the target speed of the vehicle 2 at each target position. In the autonomous driving control, the deviation between the vehicle 2 and the target trajectory (for example, lateral deviation, yaw angle deviation, and speed deviation) is calculated, and the vehicle 2 is controlled so as to reduce this deviation.

[0044] During the process of autonomous driving control, the vehicle control system determines whether remote assistance by an operator is required. When it is determined that remote assistance is required, the vehicle control system sends a request signal RS for remote assistance to the remote facility 3. The request signal RS is included in the communication data COM2.

[0045] The vehicle 2 is at least equipped with a camera 21. The camera 21 captures an image (moving image) of the external condition of the vehicle 2. The camera 21 is set to capture an image of the periphery of the vehicle 2 (for example, front and rear images). The image data IMG obtained by the camera 21 is typically moving image data. However, the image data IMG can also be still image data. When it is determined that remote assistance is required, the vehicle control system sends the image data IMG to the remote facility 3. The image data IMG is also included in the communication data COM2.

[0046] When the remote facility 3 receives the request signal RS from the vehicle control system, it remotely assists the driving of the vehicle 2 based on the operator's operation. The remote facility 3 is at least provided with a display 31. As the display 31, a liquid crystal display (LCD: Liquid Crystal Display) and an organic EL (OLED: Organic Light Emitting Diode) display can be exemplified.

[0047] During the remote assistance by the operator, the remote facility 3 displays the image data IMG received from the vehicle 2 on the display 31. The operator grasps the external condition of the vehicle 2 based on the image data IMG displayed on the display 31 and inputs an assistance instruction for the vehicle 2. The remote facility 3 generates an assistance signal AS based on this assistance instruction and sends it to the vehicle 2. The assistance signal AS is included in the communication data COM3.

[0048] Examples of the remote assistance by the operator include recognition assistance and judgment assistance. In the case of performing autonomous driving control, for example, when sunlight shines on a traffic signal existing in front of the vehicle 2, the recognition accuracy of the lighting state of the light-emitting part (for example, green, yellow, and red light-emitting parts) of the traffic signal decreases. When the lighting state cannot be recognized, it also becomes difficult to judge at which timing what kind of action should be performed. In such a case, recognition assistance for the lighting state and / or judgment assistance for the actions of the vehicle 2 based on the lighting state recognized by the operator are performed.

[0049] Remote assistance performed by an operator also includes remote driving. In remote driving, the operator performs driving operations of the vehicle 2 including at least one of steering, acceleration, and deceleration with reference to the image data IMG displayed on the display 31. In this case, the assistance instruction performed by the operator indicates the content of the driving operation of the vehicle 2. The remote facility 3 generates an assistance signal AS corresponding to the content of the driving operation and transmits it to the vehicle 2. The vehicle control system performs driving operations of the vehicle 2 including at least one of steering, acceleration, and deceleration in accordance with the assistance signal AS.

[0050] It should be noted that the required time from the transmission of the communication data COM2 including the request signal RS to the reception of the communication data COM3 including the assistance signal AS transmitted in response to the signal varies depending on communication speed factors such as communication standards and used frequency bands. This required time is set separately considering the communication speed factors.

[0051] 1-1-2. Transmission timing of the request signal

[0052] Figure 2 is a diagram showing a first example of the transmission of the request signal RS sent from the vehicle 2 during the process of autonomous driving control. In Figure 2 the vehicle 2 traveling on the lane L1 is depicted. The lane L2 adjacent to the lane L1 is, for example, a lane for a vehicle (oncoming vehicle) traveling in the direction opposite to the traveling direction of the vehicle 2. In front of the vehicle 2, a stopped vehicle 5 stopped on the lane L1 is depicted. The stopped vehicle 5 is an obstacle that obstructs the travel of the vehicle 2 along the lane L1 and conforms to an object (avoidance target) that needs to avoid a collision with the vehicle 2.

[0053] Figure 2 The target tracks TR21 and TR22 shown are an example of the target tracks generated by the vehicle control system. In this first example, the vehicle control system identifies the stopped vehicle 5 as an avoidance target. The target track TR21 is a target track for the vehicle 2 to temporarily stop near the stopped vehicle 5. The stop position SP1 is a target position corresponding to the front end of the target track TR21. The target track TR22 is a target track for the vehicle 2 to pass by the side of the stopped vehicle 5. The target track TR22 can be generated either simultaneously with the generation of the target track TR21 or during the travel along the target track TR21.

[0054] When it is determined that remote assistance is required, the vehicle control system sends a request signal RS for remote assistance. For example, when the recognition accuracy of the stopped vehicle 5 or the recognition accuracy around the stopped vehicle 5 is low, it is determined that remote assistance is required. In another example, when the safety of the target track TR22 cannot be ensured, it is determined that remote assistance is required. When sending the request signal RS, the vehicle control system selects the target track TR21 and performs autonomous driving control along the target track TR21.

[0055] In this case, the request signal RS is sent at an arbitrary timing during the travel along the target track TR21 or at the timing when the vehicle 2 reaches the stop position SP1. Moreover, the request signal RS can also be sent after the vehicle 2 reaches the stop position SP1.

[0056] Figure 3 It is a diagram showing a second transmission example of the request signal RS sent from the vehicle 2 during the autonomous driving control. In Figure 3 the vehicle 2 traveling in the lane L1 is depicted. The vehicle 2 is scheduled to enter the intersection PI. An oncoming vehicle 6 is depicted on the opposite side of the intersection PI with respect to the vehicle 2. Similar to the vehicle 2, the oncoming vehicle 6 is scheduled to enter the intersection PI.

[0057] Figure 3 The target tracks TR23 and TR24 shown are an example of the target tracks generated by the vehicle control system. The target track TR23 is a target track for the vehicle 2 to temporarily stop at the intersection PI. The stop position SP2 is the target position corresponding to the front end of the target track TR23. The target track TR24 is a target track for the vehicle 2 to perform a right-turn operation at the intersection PI. The target track TR24 can be generated simultaneously with the generation of the target track TR23 or can be generated during the travel along the target track TR23.

[0058] In the second example, the vehicle control system recognizes the oncoming vehicle 6. The predicted track TR61 is an example of the future track of the oncoming vehicle 6. The predicted track TR61 is predicted by the vehicle control system when the target track TR23 is generated. The prediction of the predicted track TR61 is performed, for example, based on the behavior models of various moving bodies such as four-wheel vehicles, two-wheel vehicles, and pedestrians. This behavior model is preset according to the behavior patterns of various moving bodies.

[0059] Similarly to the first example, in the second example, it is also determined whether remote assistance is required. For example, when the collision condition is satisfied, it is determined that remote assistance is required. The collision condition includes, for example, a crossing condition and a proximity condition. The crossing condition is satisfied when the target orbit TR24 crosses the predicted orbit TR61. The proximity condition is satisfied when the difference between the timing at which the vehicle 2 reaches the crossing position and the timing at which the oncoming vehicle 6 reaches the crossing position is within a specified time. When the request signal RS is sent, the vehicle control system selects the target orbit TR23 and performs autonomous driving control along the target orbit TR23.

[0060] In this case, the request signal RS is sent at an arbitrary timing during the travel along the target orbit TR23 or at the timing when the vehicle 2 reaches the stop position SP2. Moreover, the request signal RS may also be sent after the vehicle 2 reaches the stop position SP2.

[0061] 1-1-3. Driving efficiency level

[0062] As described in Figure 2 and Figure 3 , the timing at which the request signal RS is sent (hereinafter, also referred to as "request timing RT".) can be set to any timing after the timing when it is determined that remote assistance is required. The fact that the request timing RT is arbitrary has both advantages and disadvantages. For example, in the case of performing remote driving by an operator, by advancing the request timing RT, a smooth transition from autonomous driving control to remote driving can be achieved. In the case of performing recognition assistance or judgment assistance, the operator has a surplus in grasping the surrounding environment. On the other hand, if the request timing RT is advanced, the time for which the operator is engaged in a single remote assistance becomes longer. Therefore, when a plurality of request signals RS are received, it is difficult for the operator to handle all of these request signals RS.

[0063] Refer to Figure 4 and Figure 5 to describe the advantages and disadvantages in the case where the request timing RT is delayed. Figure 4 is a diagram for explaining the disadvantages in the case where the request timing RT is delayed in the first transmission example shown in Figure 2 . Comparing Figure 4 with Figure 2 , it can be seen that Figure 4 the position of the vehicle 2 shown is closer to the stop position SP1 than Figure 2 the position of the vehicle 2 shown. In the case where the request timing RT is delayed, the time for waiting for the assistance signal AS at the stop position SP1 becomes longer. If this time becomes longer, the vehicle 2 will obstruct traffic. In addition, the driver and passengers of the vehicle 2 may feel uncomfortable with this waiting situation.

[0064] Figure 5 This is a diagram for explaining the advantages in the case where the request timing RT is delayed in the second transmission example described in Figure 3 . By comparing Figure 5 with Figure 3 , it can be seen that the position of the vehicle 2 shown in Figure 5 is closer to the stop position SP2 than the position of the vehicle 2 shown in Figure 3 . In addition, the oncoming vehicle 6 passes through the middle position of the intersection PI and is about to enter the lane L2.

[0065] In the case where the request timing RT is delayed, the determination result that remote assistance is required may change. In the case where the determination result changes, the execution of the automatic driving control can be continued without relying on remote assistance. Figure 5 The target tracks TR25 and TR26 depicted in

[0066] are target tracks for allowing the vehicle 2 that has entered the intersection PI to perform a right turn without temporarily stopping. The predicted track TR62 is an example of the future track of the oncoming vehicle 6 predicted by the vehicle control system when generating the target track TR25. In view of such advantages and disadvantages, in the first embodiment, the request timing RT is calculated based on the "driving efficiency level EL". The driving efficiency level EL represents the degree of driving efficiency required for the vehicle 2. "Driving efficiency" is defined as the ratio of the driving distance of the vehicle 2 during the waiting time (hereinafter, also referred to as "waiting time") WT for receiving the assistance signal AS at the waiting predetermined position WP to the waiting time WT. The waiting predetermined position WP represents a predetermined position for waiting to receive the assistance signal AS. As the waiting predetermined position WP, the temporary stop position of the vehicle 2 included in the target track can be exemplified. That is, the stop positions SP1 and SP2 described in Figure 2 and Figure 3 are specific examples corresponding to the waiting predetermined position WP.

[0067] Figure 6 This is a diagram showing an example of the relationship between the driving efficiency level EL and the waiting time WT (WT@WP). As shown in Figure 6 , the higher the driving efficiency level EL, the shorter the waiting time WT. When the driving efficiency level EL is equal to "EL1", the waiting time WT represents "0". The waiting time WT being "0" means receiving the assistance signal AS at the timing when the vehicle 2 reaches the waiting predetermined position WP. When the driving efficiency level EL is higher than "EL1", the waiting time WT represents a value lower than "0". The waiting time WT being lower than "0" means receiving the assistance signal AS at a timing before the vehicle 2 reaches the waiting predetermined position WP.

[0068] In Figure 6The left side also shows the relationship between the position where the request signal RS is transmitted and the driving efficiency level EL. As already described, when the driving efficiency level EL is high, there is a high possibility of receiving the auxiliary signal AS at a timing before the vehicle 2 reaches the waiting predetermined position WP. Therefore, the higher the driving efficiency level EL, the farther the position where the request signal RS is transmitted (hereinafter, also referred to as "request position RP") is from the waiting predetermined position WP. Conversely, the lower the driving efficiency level EL, the closer the request position RP is to the waiting predetermined position WP.

[0069] Thus, according to the first embodiment, the request signal RS is transmitted at a timing calculated based on the driving efficiency level EL. Therefore, it is possible to transmit the request signal RS to the remote facility 3 at the optimal timing considering the driving environment such as the external condition of the vehicle 2 and the internal condition of the vehicle 2, and thus receive the auxiliary signal AS. Therefore, it is possible to maximize the advantages based on setting the request timing RT to an arbitrary timing or minimize the disadvantages based on setting the request timing RT to an arbitrary timing. It should be noted that examples of the driving environment will be described later.

[0070] Hereinafter, the vehicle control system of the first embodiment and the remote assistance system including the vehicle control system will be described in detail.

[0071] 1 - 2. Remote Assistance System

[0072] 1 - 2 - 1. Example of Vehicle Configuration

[0073] Figure 7 It represents Figure 1 a block diagram of the configuration example of the vehicle 2 shown. As Figure 7 shown, the vehicle 2 includes a camera 21, a sensor group 22, a map database (map DB) 23, a driving device 24, a communication device 25, and a control device 26. These elements constitute the vehicle control system of the first embodiment. The camera 21, the sensor group 22, the map database 23, the driving device 24, and the communication device 25 are connected to the control device 26 through an in-vehicle network (for example, CAN (Car Area Network)). It should be noted that the description of the camera 21 has been described as in Figure 1 the description.

[0074] The sensor group 22 includes state sensors that detect the state of the vehicle 2. As state sensors, a speed sensor, an acceleration sensor, a yaw rate sensor, and a steering angle sensor can be exemplified. The sensor group 22 also includes position sensors that detect the position and orientation of the vehicle 2. As position sensors, a GNSS (Global Navigation Satellite System) sensor can be exemplified. The sensor group 22 may also include identification sensors other than the camera 21. The identification sensors identify (detect) the external condition of the vehicle 2 using radio waves or light. As identification sensors, a millimeter-wave radar and a LIDAR (Laser Imaging Detection and Ranging) can be exemplified.

[0075] Map data MAP is stored in a map database (map DB) 23. As map data MAP, position data of roads, data on road shapes (e.g., types of curves and straight lines), and position data of intersections and structures can be exemplified. The map data MAP also includes traffic control data. The map database 23 is formed in an in-vehicle storage device (e.g., a hard disk drive, a flash memory). The map database 23 may also be formed in a computer of a facility (e.g., the remote facility 3) that can communicate with the vehicle 2.

[0076] The traveling device 24 includes a steering device, a driving device, and a braking device. The steering device steers the tires of the vehicle 2. The steering device includes, for example, an electric power steering (EPS) device. The driving device is a power source that generates a driving force. As the driving device, an electric motor and an internal combustion engine can be exemplified. The braking device generates a braking force.

[0077] The communication device 25 performs wireless communication with a base station (not shown) of the network 4. As communication standards for this wireless communication, communication standards for mobile communications such as 4G, LTE, or 5G can be exemplified. Among the connection targets of the communication device 25 is the remote facility 3. In communication with the remote facility 3, the communication device 25 transmits communication data COM2 received from the control device 26 to the remote facility 3.

[0078] The control device 26 is composed of a microcomputer having at least one processor 26a, at least one memory 26b, and an interface 26c. The processor 26a includes a CPU (Central Processing Unit). The memory 26b is a volatile memory such as a DDR (Double Data Rate) memory, and expands the programs used by the processor 26a and temporarily stores various data. Various data acquired by the vehicle 2 is stored in the memory 26b. The various data includes driving environment data ENV of the vehicle 2. The interface 26c is an interface with external devices such as the camera 21 and the sensor group 22.

[0079] Here, with reference to Figure 8 , examples of the driving environment data ENV will be described. As Figure 8 shown, the driving environment data ENV includes external condition data EXT, internal condition data INT, position and orientation data POS, working condition data SER, and traffic condition data TRA.

[0080] As the external condition data EXT, image data IMG acquired by the camera 21 and recognition data acquired by the above-described recognition sensor can be exemplified.

[0081] As the internal condition data INT, state data of the vehicle 2 acquired by the above-described state sensor can be exemplified. The internal condition data INT may also include boarding data indicating that a passenger is on board the vehicle 2. The internal condition data INT may also include data indicating the remaining travel distance of the vehicle 2. When the power source of the vehicle 2 is an electric motor, the remaining travel distance is calculated based on the remaining battery level. When the power source of the vehicle 2 is an internal combustion engine, the remaining travel distance is calculated based on the remaining fuel level.

[0082] The position and orientation data POS is data on the position and orientation of the vehicle 2 acquired by the above-described position sensor.

[0083] The working condition data SER is data on the working condition of the transportation service when the vehicle 2 provides a transportation service for passengers. As the vehicle 2 providing the transportation service, a shared bus traveling on a prescribed route according to a prescribed schedule and a demand bus traveling on a route from the departure place of the user to the destination according to a request from the user can be exemplified. As the working condition data SER in the former case, data on the delay time of the transportation service with respect to the scheduled operation time can be exemplified. As the working condition data SER in the latter case, data on the remuneration paid by the user for the transportation service can be exemplified. It should be noted that the working condition data SER is obtained, for example, from a server that manages the transportation service.

[0084] Traffic condition data TRA is data representing the traffic condition in the route from the current location of vehicle 2 to the destination. As the traffic condition data TRA, for example, data on the congestion occurring on the route from the current location of vehicle 2 to the destination can be cited. Among the congestion data, for example, data on the length from the start point to the end point of the congestion (congestion length) and data on the estimated time for the congestion to be eliminated can be cited. It should be noted that the traffic condition data TRA is obtained, for example, from a center that collects and edits traffic information and provides the traffic information to the outside.

[0085] 1-2-2. Configuration example of remote facility

[0086] Figure 9 represents Figure 1 a block diagram showing a configuration example of the remote facility 3 shown. As Figure 9 shown, the remote facility 3 includes a display 31, an input device 32, a communication device 33, and a data processing device 34. The display 31, the input device 32, and the communication device 33 are connected to the data processing device 34 through a dedicated network. It should be noted that the description of the display 31 is as already described in the description of Figure 1 .

[0087] The input device 32 is a device operated by an operator of the remote facility 3. The input device 32 includes, for example: an input unit that receives an input by the operator; and a control circuit that generates and outputs an auxiliary signal AS based on the input. As the input unit, for example, a touch panel, a mouse, a keyboard, a button, and a switch can be cited. As the input by the operator, for example, a movement operation of a cursor displayed on the display 31 and a selection operation of a button displayed on the display 31 can be cited.

[0088] In the case where the operator remotely drives vehicle 2, the input device 32 may also include an input device for driving. As the input device for driving, for example, a steering wheel, a shift lever, an accelerator pedal, and a brake pedal can be cited.

[0089] The communication device 33 performs wireless communication with a base station of the network 4. As the communication standard for the wireless communication, for example, communication standards for mobile communications such as 4G, LTE, or 5G can be cited. The communication targets of the communication device 33 include vehicle 2. In the communication with vehicle 2, the communication device 33 transmits communication data COM3 received from the data processing device 34 to vehicle 2.

[0090] The data processing device 34 is a computer for processing various data. The data processing device 34 includes at least one processor 34a, at least one memory 34b, and an interface 34c. The processor 34a includes a CPU. The memory 34b expands the programs used by the processor 34a and temporarily stores various data. The input signals from the input device 32 and various data acquired by the remote facility 3 are stored in the memory 34b. The various data includes the image data IMG included in the communication data COM2. The interface 34c is an interface with external devices such as the input device 32.

[0091] 1-2-3. Functional configuration example of the control device

[0092] Figure 10 represents Figure 7 The block diagram showing the functional configuration example of the control device 26 shown. As Figure 10 shown, the control device 26 includes a data acquisition unit 261, a data processing unit 262, a target trajectory generation unit 263, a vehicle control unit 264, a request determination unit 265, a communication processing unit 266, a horizontal calculation unit 267, and a timing calculation unit 268. These functions are realized by the processor 26a processing a prescribed program stored in the memory 26b.

[0093] The data acquisition unit 261 acquires the driving environment data ENV. Examples of the driving environment data ENV are as described in Figure 8 above. The data acquisition unit 261 also acquires the communication data COM3. As already described, the communication data COM3 is data sent from the remote facility 3 to the vehicle 2. The data acquisition unit 261 also acquires the map data MAP from the map database 23.

[0094] The data processing unit 262 processes the various data acquired by the data acquisition unit 261. As the processing of the various data, the recognition processing of objects based on the external condition data EXT can be exemplified. According to this recognition processing, objects such as moving bodies and lane dividing lines (white lines) existing around the vehicle 2 are recognized. The processing of the various data includes the calculation processing of the future trajectory of the moving body based on the moving body recognized by the recognition processing and the above-mentioned behavior model.

[0095] The processing of various data includes the encoding processing of image data IMG and request signal RS. The encoded image data IMG and request signal RS are included in communication data COM2. The processing of various data includes the decoding processing of auxiliary signal AS included in communication data COM3. The processing of various data may also include the calculation processing of the cruising range based on internal condition data INT. The processing of various data may also include the calculation processing of the delay time relative to the operation preset time based on operation condition data SER.

[0096] The target orbit generation unit 263 generates a target orbit. The target orbit is generated, for example, based on the target identified by the identification processing of the data processing unit 262 and various data (state data of vehicle 2, position and orientation data) acquired by the data acquisition unit 261. The target orbit is output to the vehicle control unit 264 and the request determination unit 265.

[0097] The vehicle control unit 264 performs the autonomous driving control of vehicle 2 based on the target orbit. In the autonomous driving control, the steering, acceleration, and deceleration of vehicle 2 are controlled so that vehicle 2 follows the target orbit TR2. In order to make vehicle 2 follow the target orbit, the vehicle control unit 264 calculates the deviation between vehicle 2 and the target orbit (for example, lateral deviation, yaw angle deviation, and speed deviation). Then, the vehicle control unit 264 controls the steering, acceleration, and deceleration of vehicle 2 to reduce the deviation. The vehicle control unit 264 also controls the steering, acceleration, and deceleration of vehicle 2 based on the auxiliary signal AS.

[0098] The request determination unit 265 determines whether remote assistance is required. This determination is made, for example, based on the likelihood of the avoidance object (hereinafter, also referred to as "recognition likelihood") identified by the identification processing of the data processing unit 262. Alternatively, this determination is made based on the recognition likelihood of the objects around the avoidance object. The recognition likelihood is a numerical value indicating the certainty of the output in the object recognition using deep learning. As a specific example of the recognition likelihood, an index of the classification result output together with the classification result of the object of deep learning using the YOLO (You Only Look Once) network can be cited. It should be noted that the method for calculating the recognition likelihood applicable to the first embodiment is not particularly limited. When the recognition likelihood is lower than the threshold TH1, it is determined that remote assistance is required.

[0099] In another example, it is determined whether remote assistance is required based on the target orbit. For example, when the distance from the target orbit to the lane dividing line where vehicle 2 is traveling is lower than the threshold TH2, it is determined that the safety of the target orbit cannot be guaranteed. Regarding the target orbit, when the above-mentioned collision conditions are satisfied (refer to Figure 3In the case of (description of), it is also determined that the safety of the target track cannot be guaranteed. In such a case, it is determined that remote assistance is required.

[0100] The communication processing unit 266 transmits the image data IMG encoded by the data processing unit 262 and the request signal RS to the remote facility 3 via the communication device 25.

[0101] The horizontal calculation unit 267 calculates the driving efficiency level EL. The driving efficiency level EL is calculated, for example, using the following formula (1) in which the driving environment data ENV is a variable.

[0102] EL = ΣWk × fk(ENV) ……(1)

[0103] Wk (k≥1) shown in formula (1) is a weighting coefficient assigned according to the type of driving environment data ENV used in the calculation of the driving efficiency level EL.

[0104] As a first example of the driving environment data ENV used in the calculation of the driving efficiency level EL, the identification data of the following vehicle included in the external condition data EXT can be cited. The following vehicle is a vehicle traveling in the same direction as the traveling direction of vehicle 2 in the rear direction of vehicle 2. The identification data of the following vehicle can be obtained either by the above-mentioned identification sensor or by the processing of the image data behind vehicle 2.

[0105] For example, when the identification data of the following vehicle is not included in the external condition data EXT, the value of the function fk(ENV) is set to "V1", and when it is not the case, the value is set to a value greater than V1. In this way, the value of the driving efficiency level EL calculated when the identification data of the following vehicle is included in the external condition data EXT becomes higher.

[0106] The temporary stop at the predetermined position WP may obstruct the passage of the following vehicle. In this regard, if the value of the driving efficiency level EL becomes higher, such an adverse situation can be avoided preventively. On the other hand, when the identification data of the following vehicle is not included in the external condition data EXT, the value of the driving efficiency level EL can also be lowered to allow a temporary stop.

[0107] As a second example of the driving environment data ENV used in the calculation of the driving efficiency level EL, the occupancy data included in the internal condition data INT can be cited. For example, when the occupancy data is not included in the internal condition data INT, the value of the function fk(ENV) is set to "V2", and when it is not the case, the value is set to a value greater than V2. In this way, the value of the driving efficiency level EL calculated when the occupancy data is included in the internal condition data INT becomes higher.

[0108] The temporary stop while waiting for the predetermined position WP may give a sense of discomfort to the occupants of the vehicle 2. In this regard, if the value of the driving efficiency level EL becomes higher, the comfort of the occupants can be maintained. On the other hand, when the interior condition data INT does not include boarding data, the value of the driving efficiency level EL can also be decreased to permit the temporary stop.

[0109] As a third example of the driving environment data ENV used in the calculation of the driving efficiency level EL, the data of the remaining cruising range included in the interior condition data INT can be cited. For example, when the remaining cruising range exceeds the threshold TH3, the value of the function fk(ENV) is set to "V3", and when it is not the case, the value is set to a value greater than V3. In this way, the value of the driving efficiency level EL calculated when the remaining cruising range is lower than the threshold TH3 becomes higher.

[0110] The temporary stop while waiting for the predetermined position WP may cause the remaining cruising range to decrease. In this regard, if the value of the driving efficiency level EL becomes higher, the decrease in the remaining cruising range associated with the temporary stop can be suppressed. On the other hand, if there is a surplus in the remaining cruising range, the value of the driving efficiency level EL can also be decreased to permit the temporary stop. It should be noted that in this third example, the value of the function fk(ENV) can also be changed in such a way that the shorter the remaining cruising range, the more the value of the function fk(ENV) increases.

[0111] As a fourth example of the driving environment data ENV used in the calculation of the driving efficiency level EL, the data of the delay time included in the working condition data SER can be cited. For example, when the delay time is lower than the threshold TH4, the value of the function fk(ENV) is set to "V4", and when it is not the case, the value is set to a value greater than V4. In this way, the value of the driving efficiency level EL calculated when the delay time exceeds the threshold TH4 becomes higher.

[0112] The temporary stop while waiting for the predetermined position WP may cause the delay time to lengthen. In this regard, if the value of the driving efficiency level EL becomes higher, the lengthening of the delay time associated with the temporary stop can be suppressed. On the other hand, when the delay time exceeds the threshold TH4, the value of the driving efficiency level EL can also be decreased to permit the temporary stop. It should be noted that in this example, the value of the function fk(ENV) can also be changed in such a way that the longer the delay time, the more the value of the function fk(ENV) increases.

[0113] As a fifth example of the driving environment data ENV used in the calculation of the driving efficiency level EL, the data on remuneration included in the working condition data SER can be cited. For example, when the remuneration is lower than the threshold TH5, the value of the function fk(ENV) is set to "V5", and when this is not the case, the value is set to a value greater than V5. In this way, the value of the driving efficiency level EL calculated when more remuneration is paid becomes higher.

[0114] The temporary stop at the waiting predetermined position WP may give a sense of discomfort to users who expect efficient transportation. In this regard, if the value of the driving efficiency level EL becomes higher, the comfort of the users can be maintained. On the other hand, when the remuneration is lower than the threshold TH5, the value of the driving efficiency level EL can also be lowered to allow the temporary stop. It should be noted that in this example, the value of the function fk(ENV) can also be changed in such a way that the higher the remuneration, the greater the value of the function fk(ENV).

[0115] As a sixth example of the driving environment data ENV used in the calculation of the driving efficiency level EL, the data on congestion included in the traffic condition data TRA can be cited. For example, when the data on congestion is not included in the traffic condition data TRA, the value of the function fk(ENV) is set to "V6", and when this is not the case, the value is set to a value greater than V6. In this way, the value of the driving efficiency level EL calculated when congestion is occurring on the route from the current location of the vehicle 2 to the destination becomes higher.

[0116] The temporary stop at the waiting predetermined position WP may be combined with congestion to delay the arrival time at the destination. In this regard, if the value of the driving efficiency level EL becomes higher, the delay in the arrival time can be minimized. On the other hand, when the traffic condition data TRA does not include the data on congestion, the value of the driving efficiency level EL can also be lowered to allow the temporary stop.

[0117] As a seventh example of the driving environment data ENV used in the calculation of the driving efficiency level EL, the data on the estimated time included in the traffic condition data TRA can be cited. For example, when the estimated time is lower than the threshold TH6, the value of the function fk(ENV) is set to "V7", and when this is not the case, the value is set to a value greater than V7. In this way, the value of the driving efficiency level EL calculated when the estimated time exceeds the threshold TH6 becomes higher. The advantages in the seventh example are basically the same as those in the sixth example.

[0118] The first to seventh examples of the above driving environment data ENV can be appropriately combined.

[0119] The timing calculation unit 268 calculates the timing of the transmission request signal RS (that is, the request timing RT). The request timing RT is expressed as "X seconds after the current timing". The request timing RT is calculated, for example, by the following equation (2).

[0120] X = Y - TC + WT...(2)

[0121] Y shown in the above equation (2) is the timing when the vehicle 2 reaches the waiting predetermined position WP, and is expressed as "Y seconds after the current timing". "Y" representing the arrival timing can be calculated based on the target track TR. In addition, TC shown in the above equation (2) is the time required from the transmission of the request signal RS to the reception of the auxiliary signal AS transmitted in response to the signal. The required time TC is set separately based on communication speed factors such as communication standards and used frequency bands.

[0122] The waiting time WT is calculated based on the relationship between the driving efficiency level EL and the waiting time WT described in Figure 6 The calculation of the waiting time WT is performed by applying the driving efficiency level EL calculated by the level calculation unit 267 to the relationship described in Figure 6 .

[0123] When the waiting time WT is longer than the required time TC (WT > TC), the request timing RT is calculated as the timing that is late by the amount of the difference between these times. When the waiting time WT is equal to the required time TC, the request timing RT coincides with the arrival timing. When the waiting time WT is shorter than the required time TC (WT < TC), the request timing RT is calculated as the timing that is early by the amount of the difference between these times.

[0124] Upper and lower limits can also be set for "X" representing the request timing RT. The upper limit is set to avoid the request timing RT from being overly delayed. On the other hand, the lower limit is set to avoid the request timing RT from being overly advanced. The upper limit of the preferred "X" is Y + 10 seconds. This means that when the request timing RT violates the upper limit constraint, the transmission request signal RS is sent 10 seconds after the arrival timing. The lower limit of the preferred "X" is 1 second. This means that when the request timing RT violates the lower limit constraint, the transmission request signal RS is sent 1 second after the current timing.

[0125] 1 - 2 - 4. Processing example

[0126] Figure 11 is a flowchart showing an example of the processing performed by the control device 26 (processor 26a) during the automatic driving control in the first embodiment. Figure 11 The shown routine is repeatedly executed at a prescribed control cycle.

[0127] In Figure 11In the illustrated routine, first, it is determined whether remote assistance is required (step S11). The determination of whether remote assistance is required is made based on the external condition data EXT or the target trajectory. In the determination based on the external condition data EXT, the recognition likelihood of the avoidance object or the recognition likelihood of the objects around the avoidance object is compared with the threshold value TH1. If any of the recognition likelihoods is lower than the threshold value TH1, it is determined that remote assistance is required. In the determination based on the target trajectory, it is determined whether the collision condition regarding the target trajectory is satisfied. If it is determined that the collision condition is satisfied, it is determined that remote assistance is required.

[0128] If the determination result in step S11 is negative, the processing of this routine is ended. On the other hand, if the determination result is positive, the driving efficiency level EL is calculated (step S12). The driving efficiency level EL is calculated using, for example, the driving environment data ENV and the above formula (1). Examples of the driving environment data ENV used in this calculation have been described as above.

[0129] Following the processing of step S12, the request timing RT is calculated (step S13). The calculation of the request timing RT is performed using, for example, the above formula (2). Here, the variables of the above formula (2) are "Y" representing the arrival timing and the waiting time WT. The former is calculated based on the target trajectory TR. The latter is calculated using the driving efficiency level EL calculated in the processing of step S12. For example, by referring to the mapping diagram showing the relationship between the driving efficiency level EL and the waiting time WT described in Figure 6 or by calculating using the model formula representing this relationship to calculate the waiting time WT. It should be noted that the mapping diagram and the model formula can be the pre-set or constructed mapping diagram and model formula.

[0130] Following the processing of step S13, it is determined whether the request timing RT has arrived (step S14). The timing of the request timing RT starts immediately after the calculation of the request timing RT. The processing of step S14 is repeated until the request timing RT arrives.

[0131] In the processing of step S14, it can also be determined whether the vehicle 2 has reached the request position RP. If the request timing RT is calculated in the processing of step S13, the request position RP can also be determined. Therefore, by determining whether the vehicle 2 has reached the request position RP, it is substantially determined whether the request timing RT has arrived. It should be noted that the determination of whether the vehicle 2 has reached the request position RP is made based on, for example, the position and orientation data POS of the vehicle 2 and the request position RP.

[0132] When the determination result in step S14 is affirmative, the request signal RS is output (step S15). When the request signal RS is output, an encoding process of the request signal RS is performed. The encoded request signal RS is transmitted to the remote facility 3 via the communication device 25.

[0133] 1-3. Effects

[0134] According to the first embodiment, when it is determined that remote assistance is required, the driving efficiency level EL is calculated based on the driving environment data ENV. Then, based on the driving efficiency level EL, the timing for transmitting the request signal RS (that is, the request timing RT) is calculated. Then, after the request timing RT arrives, the request signal RS is transmitted to the remote facility 3. Therefore, the request signal RS can be transmitted at the optimal request timing RT considering the driving environment, and thus the assistance signal AS can be received. Therefore, both the operator who performs the remote assistance and the vehicle 2 (or the occupants of the vehicle 2) that receives the remote assistance can enjoy the advantages corresponding to the driving efficiency level EL.

[0135] 2. Second Embodiment

[0136] Next, refer to Figures 12 to 14 The second embodiment of the present invention will be described. It should be noted that the descriptions that are repeated with those in the description of the first embodiment are appropriately omitted.

[0137] 2-1. Outline of the Second Embodiment

[0138] Figure 12 It is a diagram for explaining the outline of the second embodiment. In Figure 12 the same situation as that described in Figure 2 is depicted. Figure 2 The difference from Figure 12 lies in the target track TR27. The target track TR27 is a target track for the vehicle 2 to temporarily stop at a position closer to the front than the stop position SP1. The stop position SP3 is the target position corresponding to the front end of the target track TR27.

[0139] In the example of Figure 2 the stop position SP1 is set as the waiting predetermined position WP. And based on this waiting predetermined position WP, the waiting time WT is calculated. Figure 12 The relationship shown on the right side of Figure 2 is the same as an example of the relationship between the driving efficiency level EL and the waiting time WT described in

[0140] According to the first embodiment, the lower the driving efficiency level EL is, the longer the waiting time WT is set. Therefore, if the waiting time WT becomes longer, the possibility that the vehicle 2 temporarily stops at the waiting predetermined position WP becomes higher. In this way, since the time of this temporary stop becomes longer, the waiting predetermined position WP may not be suitable as the temporary stop position. In Figure 12 this situation is depicted.

[0141] In Figure 12 the example shown, a parking facility PK adjacent to the lane L1 is depicted. The stop position SP1 is in front of the entrance / exit EN of the parking facility PK. When the stop position SP1 is in front of the entrance / exit EN, it will obstruct the passage of vehicles exiting from or entering the parking facility PK. Therefore, depending on the time of the temporary stop at the waiting predetermined position WP, the stop position SP1 as the waiting predetermined position WP may not be suitable as the temporary stop position.

[0142] In view of such a problem, in the second embodiment, it is determined whether the waiting time WT exceeds the threshold value THW. The threshold value THW can be set to the allowable time (for example, 5 seconds) of the temporary stop at the waiting predetermined position WP. When the waiting time WT exceeds the threshold value THW, it is determined whether the waiting predetermined position WP is suitable as the temporary stop position. The determination of whether the waiting predetermined position WP is suitable as the temporary stop position can be made based on at least one of the external condition data EXT (specifically, the image data IMG) and the map data MAP.

[0143] Then, when it is determined that the waiting predetermined position WP is not suitable as the temporary stop position, the target trajectory is generated again. Figure 12 The target trajectory TR27 shown is the target trajectory generated again. The target trajectory TR27 includes the stop position SP3 that is suitable as the temporary stop position.

[0144] In this way, according to the second embodiment, a target trajectory including the waiting predetermined position WP that is suitable as the temporary stop position can be generated. Therefore, even if the waiting time WT calculated according to the driving efficiency level EL becomes longer, it is possible to prevent in advance the occurrence of traffic obstruction caused by the temporary stop of the vehicle 2 at the waiting predetermined position WP.

[0145] Hereinafter, the vehicle control system of the second embodiment will be described in detail.

[0146] 2-2. Vehicle control system

[0147] 2-2-1. Example of the functional configuration of the control device

[0148] Figure 13This is a block diagram showing a functional configuration example of a control device included in the vehicle control system of the second embodiment. As Figure 13 shown, the control device 26 includes a data acquisition unit 261, a data processing unit 262, a target trajectory generation unit 263, a vehicle control unit 264, a request determination unit 265, a communication processing unit 266, a horizontal calculation unit 267, a timing calculation unit 268, and a position determination unit 269. These functions are realized by a processor 26a processing a prescribed program stored in a memory 26b.

[0149] Function blocks other than the position determination unit 269 are the same as the functional configuration example described in Figure 10 . Therefore, the following description will focus on the position determination unit 269. The position determination unit 269 determines whether the waiting predetermined position WP is suitable as a temporary stop position. In this determination, first, the waiting time WT is calculated. The calculation of the waiting time WT is performed by applying the driving efficiency level EL calculated by the horizontal calculation unit 267 to the relationship described in Figure 6 .

[0150] The position determination unit 269 then determines whether the waiting time WT exceeds the threshold THW. Then, when it is determined that the waiting time WT exceeds the threshold THW, the position determination unit 269 identifies landmarks around the waiting predetermined position WP and / or acquires position data of intersections and structures around the waiting predetermined position WP based on at least one of the external condition data EXT (specifically, image data IMG) and the map data MAP.

[0151] Based on the landmark recognition process using the image data IMG, landmarks around the waiting predetermined position WP are recognized. Based on the map data MAP, position data of intersections and structures around the waiting predetermined position WP are acquired. The position determination unit 269 determines the suitability of the waiting predetermined position WP based on the recognized landmarks and the acquired position data.

[0152] As unsuitable positions, in addition to the entrance / exit EN described in Figure 12 , examples also include the intersection PI and the crosswalk described in Figure 3 . When it is determined that the waiting predetermined position WP is unsuitable, the position determination unit 269 outputs a determination signal JS including an instruction to correct the target trajectory to the target trajectory generation unit 263. When it is determined that the waiting predetermined position WP is suitable, the position determination unit 269 outputs a determination signal JS including an instruction to output the target trajectory to the target trajectory generation unit 263.

[0153] When the target orbit generation unit 263 receives a determination signal IS including a correction instruction, it regenerates the target orbit. The regeneration of the target orbit is performed, for example, by setting a new stop position at a position closer to the vehicle than the stop position included in the previous target orbit. The regeneration of the target orbit is repeated until a determination signal JS including an output instruction is received. When a determination signal JS including an output instruction is received, the target orbit generation unit 263 outputs the target orbit that is the object of the output instruction to the vehicle control unit 264 and the request determination unit 265.

[0154] 2-2-2. Processing example

[0155] Figure 14 It is a flowchart showing a processing example performed by the control device 26 (processor 26a) during the automatic driving control in the second embodiment. Figure 14 The shown routine is Figure 11 repeatedly executed at a prescribed control cycle in the same manner as the shown routine.

[0156] In Figure 14 the shown routine, the processes of steps S21 and S22 are performed. The contents of the processes of steps S21 and S22 are the same as the contents of the processes of steps S11 and S12 described in Figure 11 .

[0157] Subsequent to the process of step S22, the waiting time WT is calculated (step S23). The calculation of the waiting time WT is performed using the driving efficiency level EL calculated in step S22. For example, the waiting time WT is calculated by referring to the mapping diagram showing the relationship between the driving efficiency level EL and the waiting time WT described in Figure 6 or by performing a calculation using a model formula representing the relationship. Note that the mapping diagram and the model formula can be the pre-set or pre-constructed mapping diagram and model formula.

[0158] Subsequent to the process of step S23, it is determined whether the waiting time WT exceeds the threshold value THW (step S24). In the process of step S24, the waiting time WT calculated in the process of step S23 is compared with the threshold value THW. Note that, as already described, the threshold value THW is set to the allowable time for temporarily stopping at the waiting predetermined position WP.

[0159] In the case where the determination result in step S24 is negative, the processing of the present routine is terminated. On the other hand, in the case where the determination result is positive, it is determined whether the waiting predetermined position WP conforms to an appropriate position (step S25). In the processing of step S25, first, the waiting predetermined position WP is determined based on the target track TR. Next, the landmarks around the waiting predetermined position WP are identified based on the image data IMG. Alternatively, the position data of the intersections and structures around the waiting predetermined position WP are obtained based on the map data MAP.

[0160] Then, the suitability of the waiting predetermined position WP is determined based on the identified landmarks and the obtained position data. In the case where it is determined that the waiting predetermined position WP is suitable, the target track is output (step S26). In the case where it is determined that the waiting predetermined position WP is not suitable, the target track is regenerated (step S27). The regeneration of the target track is performed, for example, by setting a new stop position at a position closer to the front than the stop position included in the target track determined to be unsuitable. The processing of steps S25 and S27 is repeatedly executed until a positive determination result is obtained in the processing of step S25.

[0161] 2-3. Effects

[0162] According to the second embodiment, a target track including the waiting predetermined position WP suitable as a temporary stop position can be generated. Therefore, it is possible to prevent in advance the occurrence of traffic obstruction caused by the temporary stop of the vehicle 2 at the waiting predetermined position WP.

Claims

1. A vehicle control system for a vehicle configured to receive remote assistance from a remote facility during an autonomous driving control, wherein the vehicle control system is characterized by comprising: a memory storing driving environment data of the vehicle; a processor configured to generate a target trajectory of the vehicle based on the driving environment data and configured to perform the autonomous driving control based on the target trajectory; and a database storing map data, wherein the processor is configured to perform the following operations as the autonomous driving control: determine whether remote assistance is required based on at least one of the driving environment data and the target trajectory; generate the target trajectory including a waiting predetermined position in a case where it is determined that remote assistance is required, wherein the waiting predetermined position represents a predetermined position for waiting for reception of an assistance signal from the remote facility; calculate a driving efficiency level representing a degree of driving efficiency required for the vehicle based on the driving environment data; calculate a request timing for sending a request signal for the remote assistance to the remote facility, the request timing being a timing for sending the request signal; send the request signal to the remote facility when the request timing arrives; and in the calculation of the request timing, output a later timing in a case where the driving efficiency level is low, wherein the later timing is later than an earlier timing, and the earlier timing is a timing in a case where the driving efficiency level is high, the higher the driving efficiency level is, the farther the position for sending the request signal is from the waiting predetermined position, and the lower the driving efficiency level is, the closer the position for sending the request signal is to the waiting predetermined position, the processor is further configured to perform the following operations as the autonomous driving control: calculate a waiting time for waiting for an assistance signal from the remote facility at the waiting predetermined position based on the driving efficiency level; determine whether the waiting time exceeds a permissible time; in a case where it is determined that the waiting time exceeds the permissible time, determine whether the waiting predetermined position is suitable as a temporary stop position based on at least one of the driving environment data and the map data; and generate a target trajectory in which the waiting predetermined position is corrected in a case where it is determined that the waiting predetermined position is not suitable as the temporary stop position.

2. The vehicle control system according to claim 1, wherein the driving environment data has external condition data of the vehicle, the processor is configured to: output a high level in the calculation of the driving efficiency level in a case where the external condition data includes identification data of a following vehicle of the vehicle, the high level is higher than a low level, and the low level is a level in a case where the external condition data does not include identification data of a following vehicle of the vehicle.

3. The vehicle control system according to claim 1 or 2, wherein the driving environment data has internal condition data of the vehicle, The processor is configured to: in the calculation of the driving efficiency level, when the internal condition data includes occupancy data indicating that there is an occupant in the vehicle, output a high level, The high level is higher than the low level, The low level is the level when the internal condition data does not include occupancy data indicating that there is an occupant in the vehicle.

4. The vehicle control system according to claim 1 or 2, characterized in that, The driving environment data has the internal condition data of the vehicle, The internal condition data has data on the remaining driving range of the vehicle, The processor is configured to: in the calculation of the driving efficiency level, the shorter the remaining driving range, the higher the level output.

5. The vehicle control system according to claim 1 or 2, characterized in that, The driving environment data has the working condition data of the passenger transportation service provided by the vehicle, The working condition data has data on the delay time of the transportation service relative to the scheduled operation time, The processor is configured to: in the calculation of the driving efficiency level, the longer the delay time, the higher the level output.

6. The vehicle control system according to claim 1 or 2, characterized in that, The driving environment data has the working condition data of the passenger transportation service provided by the vehicle, The working condition data has data on the remuneration paid by the passenger for the transportation service, The processor is configured to: in the calculation of the driving efficiency level, the higher the remuneration, the higher the level output.

7. The vehicle control system according to claim 1 or 2, characterized in that, The driving environment data has traffic condition data on the route from the current location of the vehicle to the destination, The processor is configured to: in the calculation of the driving efficiency level, when the traffic condition data includes data on congestion occurring on the route, output a high level, The high level is higher than the low level, The low level is the level when the traffic condition data does not include data on congestion occurring on the route.

8. A vehicle control method for a vehicle configured to receive remote assistance from a remote facility during the process of autonomous driving control, the vehicle control method is characterized by including: The processor of the vehicle, which is configured to generate a target trajectory of the vehicle based on the driving environment data of the vehicle and is configured to perform the autonomous driving control based on the target trajectory, performs the following operations: Determine whether remote assistance is required based on at least one of the driving environment data and the target trajectory; When it is determined that remote assistance is required, generate the target trajectory including a waiting predetermined position, where the waiting predetermined position represents a predetermined position for waiting to receive an assistance signal from the remote facility; Calculate a driving efficiency level representing the degree of driving efficiency required for the vehicle based on the driving environment data; Calculate a request timing for sending the request signal for the remote assistance to the remote facility based on the driving efficiency level, where the request timing is the timing for sending the request signal; When the request timing arrives, send the request signal to the remote facility; and In the calculation of the request timing, when the driving efficiency level is low, output a late timing, where the late timing is later than an early timing, and the early timing is the timing when the driving efficiency level is high; The higher the driving efficiency level, the farther the position for sending the request signal is from the waiting predetermined position, and the lower the driving efficiency level, the closer the position for sending the request signal is to the waiting predetermined position; Through the processor, the following operations are also performed: Calculate a waiting time for waiting for an assistance signal from the remote facility at the waiting predetermined position based on the driving efficiency level; Determine whether the waiting time exceeds a tolerance time; When it is determined that the waiting time exceeds the tolerance time, determine whether the waiting predetermined position is suitable as a temporary stop position based on at least one of the driving environment data and the map data stored in the database; and When it is determined that the waiting predetermined position is not suitable as the temporary stop position, generate a target track for correcting the waiting predetermined position.

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