Vehicle control device and vehicle control system

Abstract

To achieve efficiency of a physical distribution by preventing deterioration of a congestion state due to an invasion of an automatic operation vehicle to a congestion area and utilizing and managing the automatic operation vehicle.SOLUTION: A vehicle control device includes: a communication section; an obstacle identification section for acquiring obstacle information from an outer side via the communication section so as to respectively identify an automatic operation vehicle and other obstacles; a congestion degree determination section for determining a congestion degree for each area; and an operation instruction section for transmitting an instruction to avoid an invasion to an area where a congestion is determined to the automatic operation vehicle when the automatic operation vehicle intending to approach the area exists. The vehicle control system also includes a vehicle control device, an automatic operation control device, and a road side monitoring device.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present application relates to a vehicle control device and a vehicle control system. [Background technology]

[0002] In recent years, there has been a demand for the introduction of autonomous driving technology to transportation vehicles. Due to the shortage of drivers in transportation work and the need to save on labor costs, many autonomous guided vehicles that utilize autonomous driving vehicles have been proposed for use within factory premises and large commercial facilities. Demonstration experiments and commercial operation of autonomous guided vehicles have also begun.

[0003] A yard truck (YardTruck) has been proposed that can automatically travel within a factory, move cargo between factory buildings, and automatically connect and disconnect the trailer it tows. By controlling multiple yard trucks in parallel, it is possible to realize logistics within a factory with a small number of people (for example, Patent Document 1). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] International Publication No. 2019 / 165147 Summary of the Invention [Problem to be solved by the invention]

[0005] The automatic driving technology of the yard towing vehicle described in Patent Document 1 does not take into consideration the case where there are many vehicles traveling in the same area as the yard towing vehicle that is being driven automatically. A situation may occur where the premises are congested with vehicles, causing a traffic jam and preventing the vehicles from moving freely. In such a congested situation, an operator who manages the logistics of the premises needs to instruct the yard towing vehicles to move at an appropriate time. However, such instructions by the operator require a high level of judgment. The results are largely influenced by the personal characteristics of the operator, such as the experience and ability of the operator. The judgment and operation of an inexperienced operator may lead to a worsening of the congestion situation and a delay in the arrival completion time of the cargo towed by the yard towing vehicle.

[0006] The present disclosure aims to provide a vehicle control device and vehicle control system that prevents the worsening of congestion due to autonomous vehicles entering congested areas and achieves more efficient logistics by utilizing autonomous vehicles. [Means for solving the problem]

[0007] A vehicle control device according to the present disclosure includes: A communication unit that communicates with the outside world; an obstacle identification unit that acquires obstacle information generated by a plurality of obstacle detection units provided externally via a communication unit and identifies the autonomous vehicle and other obstacles; a congestion level determination unit that determines a congestion level for each zone based on the information identified by the obstacle identification unit; and The system is equipped with a driving instruction unit that determines whether there is an autonomous vehicle planning to enter an area that has been determined to be congested by the congestion degree determination unit, and if there is an autonomous vehicle planning to enter, transmits instructions to the autonomous vehicle via the communication unit to avoid entering the area.

[0008] In addition, the vehicle control system according to the present disclosure includes: A vehicle control device; An autonomous driving control device that is mounted on an autonomous driving vehicle, has an obstacle detection unit, and communicates with a vehicle control device via an on-board communication unit; The roadside monitoring device has an obstacle detection unit and communicates with the vehicle control device via a roadside communication unit. Effect of the Invention

[0009] The vehicle control device and vehicle control system disclosed herein can prevent the worsening of congestion due to autonomous vehicles entering congested areas, and can achieve more efficient logistics by utilizing autonomous vehicles. [Brief description of the drawings]

[0010] [Figure 1] 1 is a configuration diagram of a vehicle control system according to a first embodiment. [Diagram 2] 1 is a configuration diagram of a vehicle control device according to a first embodiment. [Diagram 3] 1 is a configuration diagram of an automatic driving control device according to a first embodiment. [Figure 4] 1 is a configuration diagram of a driving assistance control device according to a first embodiment. [Diagram 5] 1 is a configuration diagram of a roadside monitoring device according to a first embodiment. [Figure 6] FIG. 2 is a hardware configuration diagram of a control device according to the first embodiment. [Figure 7] 3 is a block diagram showing a flow of obstacle information to a vehicle control device according to the first embodiment. FIG. [Figure 8] 3 is a diagram showing an obstacle time-series map of the vehicle control device according to the first embodiment. FIG. [Figure 9] 4 is a flowchart showing a process of the vehicle control device according to the first embodiment. [Figure 10] FIG. 11 is a configuration diagram of a vehicle control device according to a second embodiment. [Figure 11] 10 is a first flowchart showing the process of a vehicle control device according to the second embodiment. [Figure 12] 10 is a second flowchart showing the process of the vehicle control device according to the second embodiment. [Figure 13] FIG. 11 is a configuration diagram of a vehicle control device according to a third embodiment. [Figure 14] 11 is a first flowchart showing the process of a vehicle control device according to the third embodiment. [Figure 15] 11 is a time chart showing the processing of a vehicle control device according to the third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, the embodiments will be described in detail with reference to the drawings. The drawings are shown in a schematic manner, and for the convenience of explanation, configurations are omitted or simplified as appropriate. Furthermore, the size and positional relationship of the configurations shown in different drawings are not necessarily described accurately, and may be changed as appropriate. Furthermore, in the following explanation, similar components are illustrated with the same reference numerals, and their names and functions are also assumed to be similar. Therefore, detailed explanations of them may be omitted to avoid duplication.

[0012] 1. First embodiment <Vehicle control system configuration> FIG. 1 is a configuration diagram of a vehicle control system 900 according to the first embodiment. The vehicle control system 900 is configured by connecting a vehicle control device 100, an automatic driving control device 200 that controls an automatic driving vehicle 20, and a roadside monitoring device 400 through communication. Communication between the devices can be wireless communication. Wired communication may be used between the vehicle control device 100 and the roadside monitoring device 400. The vehicle control system 900 is generally configured to include automatic driving control devices 200 of multiple automatic driving vehicles 20, and multiple roadside monitoring devices 400. In addition, the system may be configured to include a driving assistance control device 300 that controls a manually driven vehicle 30 equipped with a communication function.

[0013] The vehicle control system 900 may be considered as a system including the vehicle control device 100, the autonomous vehicle 20, and the manually driven vehicle 30. The vehicle control system 900 is a system for preventing the congestion situation from worsening due to the intrusion of an autonomous vehicle into a congested area. In Fig. 1, the configuration of each device is shown in outline with only the parts mentioned here being described.

[0014] The vehicle control device 100 communicates with the automatic driving control device 200, the driving assistance control device 300, and the roadside monitoring device 400 in the area it controls to collect obstacle information related to obstacles on the road. The obstacle information is generated by the obstacle detection unit 203 included in the automatic driving control device 200, the obstacle detection unit 303 included in the driving assistance control device 300, and the obstacle detection unit 403 included in the roadside monitoring device 400. The obstacle information is then transmitted to the communication unit 101 included in the vehicle control device 100 by the in-vehicle communication unit 201 included in the automatic driving control device 200, the in-vehicle communication unit 301 included in the driving assistance control device 300, and the roadside communication unit 401 included in the roadside monitoring device 400.

[0015] The vehicle control device 100 uses the obstacle identification unit 103 to identify autonomous vehicles and other obstacles from the obstacle information collected via the communication unit 101. Then, based on the information identified by the obstacle identification unit 103, the congestion level determination unit 104 determines the congestion level for each zone obtained by dividing the area under control.

[0016] The driving instruction unit 110 of the vehicle control device 100 determines whether there is an autonomous vehicle 20 that is scheduled to enter an area that has been determined to be congested by the congestion degree determination unit. If there is an autonomous vehicle 20 that is scheduled to enter a congested area, the driving instruction unit 110 transmits an instruction to the autonomous vehicle 20 via the communication unit 101 to avoid entering the area.

[0017] Possible instructions to prevent the autonomous vehicle 20 from entering the area include an instruction to reduce the driving speed to delay the entry into the area. Also, an instruction to stop and wait the autonomous vehicle 20 in a place that does not obstruct traffic is possible. When the congestion situation in the area improves, the autonomous vehicle 20 can start entering the area. Furthermore, an instruction to bypass the area and proceed to the destination or intermediate destination is possible. If the area is not a necessary intermediate destination, the autonomous vehicle 20 can continue traveling by bypassing the area.

[0018] The vehicle control device 100 can obtain information such as the current position, current driving direction, and current driving speed of the autonomous vehicle 20 from the autonomous driving control device 200, and estimate the planned driving route of the autonomous vehicle 20. The vehicle control device 100 can also obtain an action plan held by the autonomous vehicle 20, and recognize the planned driving route of the autonomous vehicle 20. The action plan is a plan for searching for an optimal route for the autonomous vehicle 20 to travel from a departure point to a destination, and for traveling within constraints such as traffic rules. The action plan held by the autonomous vehicle 20 is updated in response to changes in the surrounding environment.

[0019] <Vehicle control device> 2 is a configuration diagram of the vehicle control device 100 according to the embodiment 1. The vehicle control device 100 receives obstacle information from the automatic driving control device 200, the driving assistance control device 300, and the roadside monitoring device 400 via the communication unit 101. Then, the vehicle control device 100 receives an action plan from the automatic driving control device 200 via the communication unit 101.

[0020] The obstacle location statistical database 109 of the vehicle control device 100 stores the received obstacle information. By statistically analyzing the data in the obstacle location statistical database 109, it is possible to predict the movement status of each object. The future occupancy time of an obstacle may be estimated from statistical information on the past occupancy area and past occupancy time of the obstacle.

[0021] In addition, by checking the position, size, shape, moving direction, and moving speed of the object detected by the obstacle detection unit based on the data from the sensors equipped in each device, it is possible to estimate the detection error of the object and the future position of the object. Furthermore, it is also possible to identify the same obstacle from obstacle information from multiple obstacle detection units.

[0022] The behavior plan storage unit 105 of the vehicle control device 100 stores the behavior plan of the autonomously driven vehicle 20 received via the communication unit 101. The behavior plan storage unit 105 provides the behavior plans of all autonomously driven vehicles that are subject to control so that they can be referenced.

[0023] The obstacle identification unit 103 identifies the current positions of the autonomous vehicle 20 and other obstacles and their estimated positions at each future time from the obstacle information, information in the obstacle position statistics database 109, and the behavior plan of the autonomous vehicle 20 stored in the behavior plan storage unit 105. The obstacle identification unit 103 divides the area it controls into arbitrary zones and creates an obstacle time series map that lists the congestion level of each zone by time.

[0024] The congestion level determination unit 104 determines the congestion level for each zone by time, which is clarified by the obstacle time series map. The congestion level may be expressed by the number of obstacles or the number of vehicles in each zone. The congestion level for any zone (n, m) (n is the X coordinate and m is the Y coordinate) may be specified as Dnm. If the congestion level Dnm of zone (n, m) is equal to or greater than a predetermined determination value DK, the zone (n, m) may be determined to be congested. If the determination value DK=1, the zone is determined to be congested if there is at least one obstacle.

[0025] The driving instruction unit 110 determines whether there is an autonomous vehicle 20 entering an area determined to be congested by the congestion degree determination unit 104. If there is no area determined to be congested, or if there is no autonomous vehicle 20 entering an area determined to be congested, there is no problem, and no instruction is issued from the driving instruction unit 110.

[0026] When an autonomous vehicle 20 is entering an area determined to be congested, the entry of the autonomous vehicle 20 into the congested area may increase the degree of congestion and make it difficult to pass through. In order to avoid such a situation, the driving instruction unit 110 identifies the autonomous vehicle 20 that is about to enter the congested area and instructs the vehicle to avoid entering the congested area. The instruction to avoid by the driving instruction unit 110 is transmitted to the vehicle via the communication unit 101.

[0027] <Automatic driving control device> 3 is a configuration diagram of an automatic driving control device 200 according to the first embodiment. The automatic driving control device 200 is mounted on an automatic driving vehicle 20, and an actuator 220 is driven by an operation control unit 213 of an automatic driving control unit 210 to perform automatic driving. The actuator 220 indicates a group of actuators, and can operate the acceleration, deceleration, turning, and stopping of the automatic driving vehicle 20. Specifically, automatic driving can be realized by operating a propulsion device such as an internal combustion engine or an electric motor, a transmission, a braking device, and a steering device.

[0028] In order for the autonomous vehicle 20 to perform autonomous driving, an action plan must be generated by instructions from the passenger or from outside. The action plan is a plan for searching for an optimal route for the autonomous vehicle 20 to travel from a departure point to a destination, and for traveling within constraints such as traffic rules. The action plan purpose, which determines the departure point, intermediate points, destination, loading and unloading of luggage, and time constraints thereof, which are the basis for generating the action plan, is indicated by the passenger or from outside, and the action plan generation unit 211 of the autonomous driving control device 200 generates the action plan.

[0029] The automatic driving control device 200 drives the actuator 220 in accordance with the action plan generated by the action plan generation unit 211 to operate the automatic driving vehicle 20. In response to the appearance of an unexpected obstacle, the automatic driving control device 200 can continue traveling of the automatic driving vehicle 20 while correcting the action plan by the action plan correction unit 212. The action plan is not fixed but is updated as it is used. The automatic driving control device 200 transmits the generated action plan and the corrected action plan to the vehicle control device 100 via the in-vehicle communication unit 201 to share them.

[0030] The autonomous driving control device 200 includes a position detection unit 204 that detects position information of the autonomous vehicle 20. The position detection unit 204 can calculate the vehicle position using positioning information from a Global Navigation Satellite System (GNSS) that detects the vehicle position, a travel distance sensor that detects the number of rotations of the wheels of the autonomous vehicle 20, a gyro sensor that detects the acceleration, speed, angular acceleration, and angular velocity of the autonomous vehicle 20, and the like. The vehicle position may also be identified using information from a tag or the like embedded in the roadside using a short-range wireless communication technology such as Near Field Communication (NFC). Furthermore, the vehicle position may be obtained by identifying landmark buildings and signs using the on-board sensor 202.

[0031] The vehicle position information of the autonomously driven vehicle 20 detected by the position detection unit 204 is transmitted to the autonomous driving control unit 210 and used for autonomous driving. The vehicle position information is then transmitted to the vehicle control device 100 via the in-vehicle communication unit 201 and shared.

[0032] The external environment in which the autonomous vehicle 20 travels is constantly changing. Therefore, the autonomous driving control device 200 detects objects around the vehicle using the on-board sensor 202, and detects obstacles using the obstacle detection unit 203. The on-board sensor 202 indicates a group of sensors for grasping the external environment, and can be configured by combining image sensors, radio wave sensors, optical sensors, ultrasonic sensors, etc. Possible obstacles to be detected include vehicles with three or more wheels, motorcycles, bicycles, pedestrians, and other obstacles.

[0033] Image sensors, such as surveillance cameras, capture images of objects and calculate the distance to the object from the image data captured within a certain viewing angle range. The size, direction of movement, speed, and type of the object can also be obtained from the image data. Visible light cameras, infrared cameras, etc. can be used as image sensors.

[0034] The radio wave sensor may be a millimeter wave radar (MMWR) that uses a frequency band of 24 to 79 GHz, etc. The radio wave sensor can detect the position of an object and can also detect the moving speed of the object by the Doppler effect.

[0035] Examples of optical sensors that can be used include laser radar, LiDAR (Light Detection and Ranging), etc. Laser light is irradiated within a certain field of view, and point cloud data obtained by the reflection of the laser light from an object is detected, allowing the position and shape of the object to be grasped.

[0036] The obstacle detection unit 203 receives information from the image sensor, radio wave sensor, optical sensor, and ultrasonic sensor, which are sensors for grasping the external environment. As the in-vehicle sensor 202, all of the image sensor, radio wave sensor, optical sensor, and ultrasonic sensor may be used, or only some of the sensors may be used. Also, sensors other than those mentioned above may be used to grasp the external environment.

[0037] The obstacle detection unit 203 can use a sensor fusion technique that combines these pieces of information to detect objects. Combining multiple types of sensor information can remove noise information and enable highly reliable object distance measurement, speed detection, and attribute identification. Furthermore, obstacles may be identified based on reinforcement learning such as deep learning.

[0038] All of the information from these sensors may be processed by the obstacle detection unit 203, but information processing may be performed for each sensor, data acquired by each sensor may be processed, and only information on the position, outer shape, speed, and type of the identified object may be transmitted to the obstacle detection unit 203. In this way, the processing of the sensor information can be distributed and executed, thereby reducing the amount of information processed by the obstacle detection unit 203 alone.

[0039] The obstacle detection unit 203 transmits obstacle information, which is information related to an obstacle, to the autonomous driving control unit 210. The autonomous driving control unit 210 corrects the action plan by the action plan correction unit 212 as necessary. In addition, the obstacle detection unit 203 transmits the obstacle information to the vehicle control device 100 via the in-vehicle communication unit 201.

[0040] <Driver assistance control device> 4 is a configuration diagram of a driving assistance control device 300 according to embodiment 1. The driving assistance control device 300 is assumed to be a control device for a manually driven vehicle 30 incorporating technologies such as an autonomous emergency braking (AEB) system that detects obstacles in front, behind, and to the sides and brings the vehicle to an emergency stop, an active constant speed control system that drives the vehicle by following the vehicle in front, and a lane keeping system that steers the vehicle while maintaining the vehicle in its lane.

[0041] Like the autonomous vehicle 20, the manually driven vehicle 30 includes an on-board sensor 302. An obstacle detection unit 303 generates obstacle information from a signal from the on-board sensor 302 and transmits it to a driving assistance control unit 310. The driving assistance control unit 310 drives an actuator 320 to provide control for AEB and the like. The obstacle detection unit 303 transmits the obstacle information to the vehicle control device 100 via the on-board communication unit 301 for sharing.

[0042] Unlike the automatic driving control device 200 of the automatic driving vehicle 20, the driving assistance control device 300 of the manually driven vehicle 30 does not have an action plan. Therefore, the action plan cannot be transmitted to the vehicle control device 100 to share the vehicle's future driving route. However, the vehicle position information of the manually driven vehicle 30 detected by the position detection unit 304 is transmitted to the vehicle control device 100 via the on-board communication unit 301 and shared. Note that a description of a manually driven vehicle that does not have a communication function is omitted here.

[0043] <Roadside monitoring device> FIG. 5 is a configuration diagram of a roadside monitoring device 400 according to the first embodiment. The roadside monitoring device 400 may also be referred to as an RSU (Road Side Unit). The roadside monitoring device 400 is installed on the roadside in a plurality of locations and includes roadside sensors 402 for detecting surrounding obstacles. The plurality of roadside monitoring devices 400 may be arranged in a cluster in the same location to share the responsibility of monitoring in all directions. The plurality of roadside monitoring devices 400 may also be arranged separately to monitor roads, intersections, etc. from different directions. Since it is not realistic to detect obstacles on all roads from the viewpoint of cost, etc., the roadside monitoring device 400 is often installed at intersections with particularly high traffic volumes, corners, roads with poor visibility, etc.

[0044] Roadside monitoring device 400 grasps the external environment within a specified viewing angle, and detects obstacles around intersections and roads using roadside sensor 402. As sensors for grasping the external environment, image sensors, radio wave sensors, optical sensors, ultrasonic sensors, etc. may be provided, similar to in-vehicle sensors 202 and 302. As obstacles to be detected, similar to in-vehicle sensors 202 and 302, possible obstacles include vehicles with three or more wheels, motorcycles, bicycles, pedestrians, and other obstacles.

[0045] The roadside monitoring device 400 may use all of the image sensor, radio wave sensor, optical sensor, and ultrasonic sensor, or may use only some of the sensors. In addition, sensors other than those mentioned above may be used to grasp the external environment.

[0046] The obstacle detection unit 403 can use a sensor fusion technique that combines these pieces of information to detect objects. All of the information from these sensors may be processed by the obstacle detection unit 403. However, information processing may be performed for each sensor, data acquired by each sensor may be processed, and only information on the position, outer shape, speed, and type of the identified object may be transmitted to the obstacle detection unit 403.

[0047] In this way, the processing of sensor information can be distributed and executed, thereby reducing the amount of information processed by a single obstacle detection unit 403. Obstacle information around the roadside monitoring device 400 generated by the obstacle detection unit 403 from signals of the roadside sensor 402 is transmitted to the vehicle control device 100 via the roadside communication unit 401 and shared.

[0048] <Control device hardware configuration> FIG. 6 is a hardware configuration diagram of the control device. The hardware configuration shown in FIG. 6 can be applied individually to the vehicle control device 100, the automatic driving control device 200, the driving assistance control device 300, and the roadside monitoring device 400. Here, a case where the hardware configuration is applied to the vehicle control device 100 will be described as a representative. In this embodiment, the vehicle control device 100 is an electronic control device installed to control the automatic driving vehicle 20. Each function of the vehicle control device 100 is realized by a processing circuit provided in the vehicle control device 100. Specifically, the vehicle control device 100 includes, as processing circuits, an arithmetic processing device 90 (computer) such as a CPU (Central Processing Unit), a storage device 91 that exchanges data with the arithmetic processing device 90, an input circuit 92 that inputs an external signal to the arithmetic processing device 90, and an output circuit 93 that outputs a signal from the arithmetic processing device 90 to the outside. Each piece of hardware such as the arithmetic processing device 90, the storage device 91, the input circuit 92, and the output circuit 93 are connected to each other by a wired network such as a bus or a wireless network.

[0049] The arithmetic processing device 90 may be an application specific integrated circuit (ASIC), an integrated circuit (IC), a digital signal processor (DSP), a graphics processing unit (GPU), a field programmable gate array (FPGA), various logic circuits, various signal processing circuits, etc. Also, the arithmetic processing device 90 may be a plurality of devices of the same type or different types, and each process may be shared and executed. The storage device 91 may be a random access memory (RAM) configured to be able to read and write data from the arithmetic processing device 90, a read only memory (ROM) configured to be able to read data from the arithmetic processing device 90, etc. As the storage device 91, a non-volatile or volatile semiconductor memory such as a flash memory, a solid state drive (SSD), an EPROM, an EEPROM, etc., a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, a DVD, etc. may be used. The input circuit 92 is connected to various sensors, switches, and communication lines, and includes an A / D converter, a communication circuit, and the like that inputs output signals and communication information of these sensors and switches to the arithmetic processing device 90. The output circuit 93 includes a drive circuit that outputs control signals from the arithmetic processing device 90, a communication circuit, and the like. The interfaces of the input circuit 92 and the output circuit 93 may be based on specifications such as CAN (Control Area Network) (registered trademark), Ethernet (registered trademark), USB (Universal Serial Bus) (registered trademark), DVI (Digital Visual Interface) (registered trademark), and HDMI (High-Definition Multimedia Interface) (registered trademark). In addition to the input circuit 92 and the output circuit 93, the arithmetic processing device 90 may be directly connected to a communication device 94 for communication.

[0050] Each function of the vehicle control device 100 is realized by the arithmetic processing device 90 executing software (programs) stored in a storage device 91 such as a ROM, and cooperating with other hardware of the vehicle control device 100 such as the storage device 91, an input circuit 92, and an output circuit 93. Setting data such as thresholds and judgment values ​​used by the vehicle control device 100 is stored in the storage device 91 such as a ROM as part of the software (programs). Each function of the vehicle control device 100 may be configured as a software module, or may be configured as a combination of software and hardware.

[0051] <Obstacle information flow> Fig. 7 is a block diagram showing a flow of obstacle information to the vehicle control device 100 according to the embodiment 1. Fig. 8 is a diagram showing an obstacle time-series map of the vehicle control device 100 according to the embodiment 1.

[0052] 7 illustrates how the obstacle information generated by the obstacle detection unit 203 of the automatic driving control device 200, the obstacle detection unit 303 of the driving assistance control device 300, and the obstacle detection unit 403 of the roadside monitoring device 400 is transmitted to the vehicle control device 100 via the communication unit of each device. Then, each obstacle information is transmitted to the obstacle identification unit 103 and the obstacle position statistics database 109 via the communication unit 101 of the vehicle control device 100.

[0053] Data stored in the obstacle position statistics database 109 is statistically processed, and information predicting the future positions of obstacles other than the autonomous vehicle 20 is transmitted to the obstacle identification unit 103. In addition, the autonomous driving control device 200 transmits an action plan for the autonomous vehicle 20 to the obstacle identification unit 103. From this information, the obstacle identification unit 103 can create an obstacle time-series map that indicates the occupied area of ​​each obstacle at each time.

[0054] As shown in Fig. 8, the obstacle time series map shows the occupancy of each obstacle in a given area over time. In Fig. 8, the times (t1 to t16) that the obstacle occupies each area are listed. Here, the presence or absence of the time of the obstacle's occupation is listed for each area. Additionally, static obstacles (fixed obstacles) such as buildings are shown by filling the area with a crosshatched line. Additionally, obstacles whose occupancy time is unknown are shown by filling the area with a horizontal striped line.

[0055] By generating an obstacle time-series map, the congestion degree determination unit 104 can determine a congested area. In Fig. 8, an area that is scheduled to be occupied by an obstacle is determined as a congested area for each hour of the day. Whether or not the autonomous vehicle 20 will enter this congested area is confirmed from the action plan.

[0056] An instruction to avoid intrusion is transmitted from the vehicle control device 100 to the autonomous vehicle 20 that is entering the area at the time when an obstacle is present. Upon receiving the instruction to avoid entry, the autonomous driving control device 200 stops and waits the vehicle, or drives around the area, thereby preventing the congestion from worsening. By avoiding traffic congestion, the efficiency of the overall logistics can be improved.

[0057] Also, an obstacle time series map different from the obstacle time series map exemplified in FIG. 8 may be used. For example, an obstacle time series map showing the occupancy of multiple obstacles by recording the name (identification ID) of the obstacle for each area and the occupancy time may be used. The congestion degree may be expressed by the number of obstacles or the number of vehicles at the same time for each area. The congestion degree for any area (n, m) at any time (n is the X coordinate and m is the Y coordinate) may be specified as Dnm. When the congestion degree Dnm of the area (n, m) is equal to or greater than a predetermined judgment value DK, the area (n, m) may be determined to be congested.

[0058] <Vehicle control system processing> Fig. 9 is a flowchart showing the processing of the vehicle control device 100 according to the first embodiment. The processing shown in Fig. 9 is executed by the arithmetic processing device of the vehicle control device 100. This processing may be executed at predetermined time intervals (for example, every 1 ms). Instead of at predetermined time intervals, the processing may be executed in response to an event such as the communication unit 101 of the vehicle control device 100 receiving obstacle information generated by an obstacle detection unit of the automatic driving control device 200, the driving assistance control device 300, or the roadside monitoring device 400, or receiving an action plan from the automatic driving control device 200.

[0059] 9 starts, and in step S107, the vehicle control device 100 acquires obstacle information generated by the obstacle detection units of the automatic driving control device 200, the driving assistance control device 300, and the roadside monitoring device 400. Then, in step S108, the vehicle control device 100 acquires the driving plan of the automatic driving control device 200.

[0060] In step S109, obstacle identification is performed. Specifically, the obstacle identification unit 103 of the vehicle control device 100 creates an obstacle time-series map showing the occupied area of ​​each obstacle at each time from the above information. Then, in step S110, the congestion degree determination unit 104 determines the congestion degree from the obstacle time-series map. Here, it is assumed that the congestion degree for each area is calculated by Dnm.

[0061] In step S111, an area where the congestion level Dnm is equal to or greater than the judgment value DK (a congested area) is extracted, and an autonomously driven vehicle 20 entering that area at the same time is searched for. In step S112, it is determined whether or not there is an autonomously driven vehicle 20 entering. If there is an autonomously driven vehicle 20 entering (determination is YES), the process proceeds to step S120. If it is determined that there is no autonomously driven vehicle 20 entering (determination is NO), the process ends.

[0062] In step S120, an entry avoidance instruction is transmitted to the automatic driving control device 200 of the corresponding automatically driven vehicle 20. Then, the process ends.

[0063] In this way, the vehicle control device 100 and vehicle control system 900 of embodiment 1 can prevent the congestion situation from worsening due to the autonomous vehicle 20 entering a congested area, and can achieve efficient logistics by utilizing the autonomous vehicle 20.

[0064] 2. Second embodiment <Vehicle control device> Fig. 10 is a configuration diagram of a vehicle control device 100 according to the embodiment 2. The only difference between Fig. 10 and Fig. 2 according to the embodiment 1 is that a driving instruction unit 110 includes an action plan revision planning unit 111 and a selection unit 112. Here, only the difference from the embodiment 1 will be described.

[0065] Vehicle control device 100 according to the second embodiment creates an obstacle time-series map indicating the occupied area of ​​each obstacle at each time, extracts an area where the congestion degree Dnm is equal to or greater than the judgment value DK (a congested area), and searches for an autonomously driven vehicle 20 entering that area at the same time. If an autonomously driven vehicle 20 is entering the congested area, action plan revision unit 111 proposes a revision to the action plan for that autonomously driven vehicle 20.

[0066] The execution of each strategy included in a collection of predefined action plans that the autonomous vehicle 20 can take (also referred to as a strategy group) is simulated, and the results of the execution of the action are predicted. The strategy is a policy for proposing a proposed revision of the action plan, such as making the autonomous vehicle 20 wait for a certain time in a specific non-congested area, making the autonomous vehicle 20 proceed to a congested area without waiting and continue the action plan, and making the autonomous vehicle 20 detour around the congested area. The information included in the obtained results may be, for example, an evaluation result (score) based on the time it takes for each autonomous vehicle 20 to complete the action plan, the area to be occupied and the time for which it is occupied, the worst value of the congestion degree of the number of congested areas, etc.

[0067] The selection unit 112 selects an optimal revision proposal for the proposed revision of the action plan proposed by the revision proposal of the action plan proposal 111. Then, an optimal instruction for revision of the action plan for avoiding simultaneous entry into a congested area is transmitted to the autonomous driving control device 200 of the autonomous driving vehicle 20 via the communication unit 101. Here, for the index evaluated as optimal by the selection unit 112, a revision proposal that results in the earliest completion time of the action plan of the autonomous driving vehicle 20 may be selected as the optimal revision proposal of the action plan. That is, a revision proposal of the action plan that results in the earliest time for the autonomous driving vehicle to complete the action plan that satisfies the action plan purpose is selected. The selection unit 112 may also select a revision proposal that results in the smallest maximum value of the congestion degree in the controlled area as the optimal revision proposal of the action plan. That is, the congestion degree of all areas in the revision proposals is confirmed, and a revision proposal that results in the smallest maximum value of the congestion degree is selected as the optimal revision proposal of the action plan.

[0068] <Vehicle control system processing> Fig. 11 is a first flowchart showing the processing of the vehicle control device 100 according to the embodiment 2. Fig. 12 is a second flowchart showing the processing of the vehicle control device 100. The flowchart in Fig. 12 shows a continuation of the flowchart in Fig. 11.

[0069] The flowcharts of Figures 11 and 12 according to the second embodiment differ from the flowchart of Figure 9 according to the first embodiment only in that the process of step S120 in Figure 9 is replaced by step S113 to step S118 in Figure 12. Here, only the parts that differ from the first embodiment will be described.

[0070] 11 and 12 are executed by the arithmetic processing device of the vehicle control device 100. This process may be executed at predetermined time intervals (for example, every 1 ms). Instead of at predetermined time intervals, the process may be executed in response to an event such as the communication unit 101 of the vehicle control device 100 receiving obstacle information generated by the obstacle detection unit of the automatic driving control device 200, the driving assistance control device 300, or the roadside monitoring device 400, or receiving an action plan from the automatic driving control device 200.

[0071] 12, an area where the congestion level Dnm is equal to or greater than the judgment value DK (a congested area) is extracted, and it is determined whether or not there is an autonomously driven vehicle 20 entering that area at the same time. If there is an autonomously driven vehicle 20 entering (determination is YES), the process proceeds to step S113. If it is determined that there is no autonomously driven vehicle 20 entering (determination is NO), the process ends.

[0072] In step S113, the behavior plan revision unit 111 formulates a waiting plan among the behavior plan revision proposals for the corresponding autonomous vehicle 20. The waiting plan is a behavior plan revision proposal in which the autonomous vehicle 20 waits at an arbitrary location until the congestion situation improves and an additional behavior plan revision instruction is sent to the autonomous vehicle 20. The behavior plan revision unit 111 proposes multiple behavior plan revision proposals worth considering.

[0073] In step S114, the route points, arrival time at the destination, impact on congestion level, etc. of each proposed plan are evaluated as evaluation indexes. Then, in step S115, the behavior plan revision planning unit 111 formulates a congested area detouring plan from among the behavior plan revision plans for the corresponding autonomous driving vehicle 20. The congested area detouring plan is an behavior plan for detouring the congested area and proceeding to the destination or a route. If the area is not a route that does not need to be visited, there is an advantage in that travel can be continued by detouring the area.

[0074] In step S116, the route points, arrival time at the destination, impact on congestion level, etc. of each proposed plan are evaluated as evaluation indices. In step S117, the action plan amendment proposed by the action plan amendment unit 111 is selected based on the selected indices.

[0075] Then, in step S118, the selected proposed revision of the action plan is transmitted to the autonomous driving control device 200 of the corresponding autonomous driving vehicle 20 via the communication unit 101. The process then ends. The corresponding autonomous driving vehicle 20 receives the proposed revision, and thereafter continues autonomous driving control based on this revised action plan.

[0076] By configuring in this way, the vehicle control device 100 and vehicle control system 900 according to the second embodiment can prevent the congestion situation from worsening due to the autonomously driven vehicle 20 entering a congested area, and can give specific instructions to the autonomous driving control device 200 by transmitting the selected action plan amendment proposal to the autonomously driven vehicle 20. This makes it possible to realize optimal instructions for improving the efficiency of logistics.

[0077] 3. Third embodiment <Vehicle control device> Fig. 13 is a configuration diagram of a vehicle control device 100 according to the embodiment 3. What differs from Fig. 10 according to the embodiment 2 in Fig. 13 is that an action plan goal storage unit 113 is added to the driving instruction unit 110, and an operator console 114 having an action plan goal indication unit 115 and a selection index indication unit 116 is provided in the driving instruction unit 110. Here, only the parts that differ from the embodiment 2 will be described.

[0078] In the vehicle control device 100 according to the third embodiment, an action plan objective specified for each autonomous vehicle 20 is stored in the action plan objective storage unit 113 each time the action plan objective is specified. This makes it possible to grasp the latest status of the action plan objective specified for each autonomous vehicle 20, and also makes it possible to refer to the action plan when making a proposed revision.

[0079] Furthermore, in the vehicle control device 100 according to the third embodiment, the operator can issue an instruction to update an action plan objective to the autonomous driving control device 200 of a specific autonomous driving vehicle 20 from the operator console 114. Then, the operator can issue an instruction to update an index for selecting an optimal revision plan from the action plan revision plans from the operator console 114.

[0080] The action plan objectives are matters that determine the departure point, intermediate points, destination, loading and unloading of luggage, and time constraints thereof, which are the basis for generating an action plan for the autonomous vehicle 20. The action plan generation unit 211 of the autonomous vehicle 20 generates an action plan based on the action plan objectives. When the operator issues an instruction to update the action plan objectives of a specific autonomous driving control device 200 from the operator console 114 of the vehicle control device 100, the action plan objectives to be updated are transmitted from the vehicle control device 100 to the relevant autonomous driving control device 200.

[0081] The selection index is an index used when the selection unit 112 selects a revision proposal for the action plan of the autonomously driven vehicle 20. For example, it is possible to select, from among the proposed revision proposals for the action plan, a revision proposal that brings the completion time of the action plan of the autonomously driven vehicle 20 to the earliest as the optimal revision proposal for the action plan. It is also possible to select, from among the proposed revision proposals for the action plan, a revision proposal that brings the maximum value of the congestion degree to a minimum as the optimal revision proposal for the action plan.

[0082] <Vehicle control system processing> Fig. 14 is a first flowchart showing the processing of the vehicle control device 100 according to the embodiment 3. The rest of Fig. 14 is the same as the flowchart shown in Fig. 12. Therefore, the flowchart shown in Fig. 12 is used as a second flowchart showing the processing of the vehicle control device 100 according to the embodiment 3.

[0083] The flowchart in Fig. 14 according to the third embodiment differs from the flowchart in Fig. 11 according to the second embodiment only in that the processes from step S101 to step S106 in Fig. 14 are added before step S107 in Fig. 11. Here, only the parts that differ from the second embodiment will be described.

[0084] The process shown in Fig. 14 and the subsequent process shown in Fig. 12 are executed by the arithmetic processing device of the vehicle control device 100. This process may be executed at predetermined time intervals (for example, every 1 ms). Instead of at predetermined time intervals, the process may be executed in response to an event such as the communication unit 101 of the vehicle control device 100 receiving obstacle information generated by the obstacle detection unit of the automatic driving control device 200, the driving assistance control device 300, or the roadside monitoring device 400, or receiving an action plan from the automatic driving control device 200.

[0085] In step S101 of Fig. 14, it is confirmed whether the operator console has been operated. In step S102, it is determined whether an instruction to update the action plan goal has been given from the operator console. If an instruction to update the action plan goal has been given (determination is YES), the process proceeds to step S103. If an instruction to update the action plan goal has not been given from the operator console (determination is NO), the process proceeds to step S105.

[0086] In step S103, the updated action plan objective is transmitted to the autonomous driving control device 200 of the specified autonomous vehicle 20. In step S104, the updated action plan objective is stored in the action plan objective storage unit 113 of the vehicle control device 100 together with the name (or number) of the corresponding autonomous vehicle 20.

[0087] In step S105, it is determined whether or not an instruction to update the selection index has been issued from the operator console. If an instruction to update the selection index has been issued (determination is YES), the process proceeds to step S106. If an instruction to update the selection index has not been issued from the operator console (determination is NO), the process proceeds to step S107.

[0088] In step S106, the selection index is updated. Specifically, the index used when the selection unit 112 of the vehicle control device 100 selects the most appropriate revision plan from the revision plans proposed by the action plan revision unit 111 is updated.

[0089] The process from step S107 onwards is the same as the process in Fig. 11 according to embodiment 2. In this way, in Fig. 14, the action plan objective and the selection index are updated depending on whether or not the operator console is operated.

[0090] <Time chart showing the processing of the vehicle control device> Fig. 15 is a time chart showing the processing of the vehicle control device 100 according to the third embodiment. In Fig. 15, operations executed by each device or functional block of the vehicle control device 100 are shown on horizontal lines. The flow of time is shown from left to right in Fig. 15. The vertical arrows indicate the flow of data. The manually-driven vehicle 30 is omitted from Fig. 15.

[0091] First, obstacle information generated by the obstacle detection unit 403 of the roadside monitoring device 400 and the obstacle detection unit 203 of the autonomous vehicle 20 is transmitted to the obstacle identification unit 103 of the vehicle control device 100. Information on each obstacle identified by the obstacle identification unit 103 is transmitted to the congestion degree determination unit 104 as an obstacle time-series map.

[0092] Next, the operator console 114 of the vehicle control device 100 is operated to instruct updating of the action plan objective of the specific autonomous vehicle 20. Inside the vehicle control device 100, the update of the action plan objective of the specific autonomous vehicle 20 is stored in the action plan objective storage unit 113 and is referred to when the action plan revision planning unit 111 proposes a revision proposal.

[0093] At the same time, an instruction to update the action plan objective is transmitted to the corresponding autonomous vehicle 20. In the autonomous vehicle 20, a new action plan is generated by the action plan generation unit 211 based on the updated action plan objective. The generated action plan is then transmitted from the autonomous vehicle 20 to the vehicle control device 100 and stored in the action plan storage unit 105.

[0094] Within the vehicle control device 100, updates to the behavior plan objectives of a particular autonomous vehicle 20 are stored in the behavior plan objective storage unit 113, forwarded to the behavior plan revision planning unit 111, and referenced when the behavior plan revision planning unit 111 proposes revision proposals.

[0095] Furthermore, an instruction to update the selection index is issued by operating the operator console 114 of the vehicle traffic control device 100. The updated selection index is transmitted to the selection unit 112 and is used when selecting a revised action plan.

[0096] The congestion level determination unit 104 determines whether a congested area is present from the obstacle information (obstacle time series map) transmitted from the obstacle identification unit 103, and determines whether there is an autonomous vehicle 20 that is scheduled to enter the congested area from the action plans of all autonomous vehicles 20 transmitted from the action plan storage unit 105.

[0097] When an autonomous vehicle 20 is scheduled to enter a congested area, the action plan revision planning unit 111 is caused to prepare multiple revisions to the action plan of the autonomous vehicle 20 in question, and to present them to the selection unit 112. The selection unit 112 selects the most appropriate revision from the proposed revisions to the action plan using the updated selection index. Then, the selected revision to the action plan is sent to the autonomous vehicle 20 in question. The autonomous vehicle 20 in question receives the revision to the action plan and automatically travels based on the revision, and is therefore able to avoid entering the congested area.

[0098] In this way, the vehicle control device 100 and vehicle control system 900 according to the third embodiment can prevent a worsening of the congestion situation caused by the intrusion of the autonomously driven vehicle 20 into a congested area, and can realize efficient logistics using the autonomously driven vehicle 20. Furthermore, it is possible to update the action plan objectives and selection indexes of a specific autonomously driven vehicle 20 by operating the operator console 114. This makes it possible to smoothly update the action plan objectives and selection indexes of the autonomously driven vehicle 20 under control, and realizes highly flexible vehicle control.

[0099] In the above description, the action plan for each autonomous vehicle 20 is generated by the autonomous driving control device 200 of each autonomous vehicle 20, but the action plan for each autonomous vehicle 20 may be generated in the vehicle control device 100, and autonomous driving may be performed while modifying the action plan received by each autonomous vehicle 20. In that case, each time the autonomous vehicle 20 modifies its action plan, it may transmit the modified action plan to the vehicle control device 100, and the vehicle control device 100 may always store the latest action plan for the autonomous vehicle 20 in the action plan storage unit 105.

[0100] Although various exemplary embodiments and examples are described in this application, various features, aspects, and functions described in one or more embodiments are not limited to the application of a specific embodiment, but can be applied to the embodiments alone or in various combinations. Therefore, countless modifications not illustrated are expected within the scope of the technology disclosed in this specification. For example, the following are included: when at least one component is modified, added, or omitted, and further, when at least one component is extracted and combined with a component of another embodiment.

[0101] Various aspects of the present disclosure are summarized below as appendices.

[0102] (Appendix 1) A communication unit that communicates with the outside world; an obstacle identification unit that acquires obstacle information generated by a plurality of obstacle detection units provided externally via the communication unit and identifies the autonomous vehicle and other obstacles; a congestion level determination unit that determines a congestion level for each zone based on the information identified by the obstacle identification unit; and A vehicle control device comprising: a driving instruction unit that determines whether there is an autonomous vehicle planning to enter an area determined to be congested by the congestion degree determination unit, and, if there is an autonomous vehicle planning to enter, transmits an instruction to the autonomous vehicle via the communication unit to avoid entering the area. (Appendix 2) The vehicle control device described in Appendix 1, wherein the obstacle identification unit acquires, via the communication unit, obstacle information transmitted from a vehicle equipped with the obstacle detection unit that generates surrounding obstacle information based on the output of an on-board sensor, and obstacle information transmitted from a roadside monitoring device equipped with the obstacle detection unit that generates surrounding obstacle information based on the output of a roadside sensor. (Appendix 3) An action plan storage unit that acquires and stores an action plan including information on a route along which the autonomous driving vehicle will travel and a scheduled time of passage via the communication unit, The vehicle control device according to claim 1 or 2, wherein the congestion level determination unit determines the congestion level at each time point for each area based on the information identified by the obstacle identification unit and the behavior plan of the autonomously driving vehicle stored in the behavior plan storage unit. (Appendix 4) The vehicle control device described in Appendix 3, wherein the driving instruction unit determines whether or not there is an autonomous vehicle scheduled to enter an area at the same time as the area where the time-specific congestion degree determined by the congestion degree determination unit is equal to or greater than a predetermined determination value, based on the action plan stored in the action plan storage unit. (Appendix 5) The vehicle control device described in Appendix 4, wherein, when there is an autonomous vehicle scheduled to enter an area at the same time as the autonomous vehicle, the congestion level determined by the congestion level determination unit is equal to or higher than the determination value, the driving instruction unit transmits an instruction to the autonomous vehicle to modify the action plan via the communication unit to avoid entering the area at the same time. (Appendix 6) The vehicle control device described in Appendix 5, wherein the driving instruction unit has an action plan revision planning unit that drafts a revision proposal for the action plan of the autonomous vehicle, and a selection unit that selects an optimal revision proposal from the proposed revision proposals for the action plan, and transmits an optimal action plan revision instruction to the autonomous vehicle via the communication unit to avoid simultaneous entry into the area. (Appendix 7) 7. The vehicle control device according to claim 6, wherein the selection unit of the driving instruction unit selects the revision plan that results in the earliest completion time of the action plan for the autonomous vehicle as the optimal revision plan for the action plan. (Appendix 8) The vehicle control device according to claim 6, wherein the selection unit of the driving instruction unit selects, as an optimal revision plan for the action plan, a revision plan that has the smallest maximum value of the congestion degree among the revision plans. (Appendix 9) The driving instruction unit has a behavior plan objective instruction unit that instructs behavior plan objectives that determine a starting point, a waypoint, a destination, loading and unloading of luggage, and time constraints therefor, which are the basis for generating a behavior plan for the autonomous driving vehicle; The vehicle control device according to any one of appendix 6 to 8, wherein the action plan revision planning unit drafts a revision proposal for the action plan of the autonomous vehicle based on the action plan objective instructed by the action plan objective instructing unit. (Appendix 10) The driving instruction unit has a selection indicator indication unit that indicates a selection indicator for selecting a correction proposal for an action plan of the autonomous driving vehicle, 10. The vehicle control device according to any one of claims 6 to 9, wherein the selection unit selects an optimal proposed revision to the action plan from the proposed revisions to the action plan based on the index indicated by the selection index indication unit. (Appendix 11) A vehicle control device according to any one of appendix 1 to 10; an automatic driving control device that is mounted on the automatic driving vehicle, has the obstacle detection unit, and communicates with the vehicle control device via an in-vehicle communication unit; a roadside monitoring device having the obstacle detection unit and communicating with the vehicle control device via a roadside communication unit. (Appendix 12) 12. The vehicle control system according to claim 11, further comprising a driving assistance control device that is mounted on a manually driven vehicle, has the obstacle detection unit, and communicates with the vehicle control device via an on-board communication unit. [Explanation of symbols]

[0103] 20 Automatic driving vehicle, 30 Manual driving vehicle, 100 Vehicle control device, 101 Communication unit, 103 Obstacle identification unit, 104 Congestion degree determination unit, 105 Action plan storage unit, 110 Driving instruction unit, 111 Action plan correction planning unit, 112 Selection unit, 115 Action plan purpose instruction unit, 116 Selection index instruction unit, 200 Automatic driving control device, 201, 301 In-vehicle communication unit, 203, 303, 403 Obstacle detection unit, 400 Roadside monitoring device, 401 Roadside communication unit, 900 Vehicle control system

Claims

1. A communication unit that communicates with the outside world; an obstacle identification unit that acquires obstacle information generated by a plurality of obstacle detection units provided externally via the communication unit and identifies the autonomous vehicle and other obstacles; a congestion level determination unit that determines a congestion level for each zone based on the information identified by the obstacle identification unit; and A vehicle control device comprising: a driving instruction unit that determines whether there is an autonomous vehicle planning to enter an area determined to be congested by the congestion degree determination unit, and, if there is an autonomous vehicle planning to enter, transmits an instruction to the autonomous vehicle via the communication unit to avoid entering the area.

2. 2. The vehicle control device according to claim 1, wherein the obstacle identification unit acquires, via the communication unit, obstacle information transmitted from a vehicle equipped with the obstacle detection unit that generates surrounding obstacle information based on output from an on-board sensor, and obstacle information transmitted from a roadside monitoring device equipped with the obstacle detection unit that generates surrounding obstacle information based on output from a roadside sensor.

3. An action plan storage unit that acquires and stores an action plan including information on a route along which the autonomous driving vehicle will travel and a scheduled time of passage via the communication unit, The vehicle control device according to claim 1 , wherein the congestion degree determination unit determines the congestion degree for each area at each time based on the information identified by the obstacle identification unit and the behavior plan of the autonomously driven vehicle stored in the behavior plan storage unit.

4. The vehicle control device according to claim 3, wherein the driving instruction unit determines whether or not there is an autonomous vehicle scheduled to enter an area at the same time as the area where the time-specific congestion degree determined by the congestion degree determination unit is equal to or greater than a predetermined determination value, based on the action plan stored in the action plan storage unit.

5. 5. The vehicle control device of claim 4, wherein when there is an autonomous vehicle scheduled to enter an area at the same time as the autonomous vehicle, the autonomous vehicle transmits an instruction to modify an action plan to avoid entering the area at the same time via the communication unit, the instruction being transmitted to the autonomous vehicle when the autonomous vehicle is scheduled to enter the area at the same time as the autonomous vehicle ... via the communication unit.

6. The vehicle control device of claim 5, wherein the driving instruction unit has an action plan revision planning unit that drafts a revision proposal for the action plan of the autonomous vehicle, and a selection unit that selects an optimal revision proposal from the proposed revision proposals for the action plan, and transmits an optimal action plan revision instruction to the autonomous vehicle via the communication unit to avoid simultaneous entry into the area.

7. The vehicle control device according to claim 6 , wherein the selection unit of the driving instruction unit selects, as the optimal revision plan to the action plan, a revision plan that results in the earliest completion time of the action plan for the autonomous vehicle.

8. The vehicle control device according to claim 6 , wherein the selection unit of the driving instruction unit selects, as an optimal revision plan for the action plan, a revision plan that minimizes the maximum value of the congestion degree among the revision plans.

9. The driving instruction unit has a behavior plan objective instruction unit that instructs behavior plan objectives that determine a starting point, a waypoint, a destination, loading and unloading of luggage, and time constraints therefor, which are the basis for generating a behavior plan for the autonomous driving vehicle; The vehicle control device according to claim 6 , wherein the action plan revision planning unit plans a revision of the action plan of the autonomous vehicle based on the action plan objective specified by the action plan objective specifying unit.

10. The driving instruction unit has a selection indicator indication unit that indicates a selection indicator for selecting a correction proposal for an action plan of the autonomous driving vehicle, 7. The vehicle control device according to claim 6, wherein the selection unit selects an optimal revised action plan from the revised action plans based on the index indicated by the selection index indication unit.

11. A vehicle control device according to any one of claims 1 to 10; an automatic driving control device that is mounted on the automatic driving vehicle, has the obstacle detection unit, and communicates with the vehicle control device via an in-vehicle communication unit; a roadside monitoring device having the obstacle detection unit and communicating with the vehicle control device via a roadside communication unit.

12. The vehicle control system according to claim 11 , further comprising a driving assistance control device that is mounted on a manually-driven vehicle, has the obstacle detection unit, and communicates with the vehicle control device via an on-board communication unit.

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