Autonomous driving system

Abstract

A control device constituting an autonomous travel system calculates a predicted arrival time, which is the time for a transport vehicle to arrive at the position of an obstacle, on the basis of the position of the obstacle and the position and travel speed of the transport vehicle, and calculates a predicted arrival time, on the basis of the position and travel speed of another vehicle and the predicted arrival time. A predicted position of the other vehicle after the predicted arrival time has elapsed is calculated, and if it is determined that the other vehicle is present in the vicinity of the obstacle after the predicted arrival time has elapsed, the travel lane is set as an avoidance region. When it is determined that the other vehicle does not exist in the vicinity of the obstacle after the predicted arrival time has elapsed, both the travel lane and the lane adjacent to the travel lane are set as an avoidance region, and the position of the transport vehicle, the position of the obstacle, and the avoidance region are determined based on the position of the transport vehicle, the position of the obstacle, and the avoidance region. An evasion path for causing the transport vehicle to evade the obstacle is generated within the evasion area.

Description

Technical Field

[0001] The invention relates to an autonomous driving system. Background Art

[0002] In open-pit mines and the like, dump trucks (hereinafter referred to as "unmanned vehicles") are known to travel autonomously without an operator (hereinafter sometimes referred to as "driver") on board. In order to increase the amount of soil, sand and minerals transported that is equivalent to the mine's production volume, the unmanned vehicles responsible for transportation need to increase the distance they travel within the operating time. However, there are obstacles such as mining machinery for road maintenance and rocks dropped from unmanned vehicles in transportation in the mine. When the unmanned vehicle detects an obstacle in the direction of travel, it stops in front of the obstacle to prevent contact with the obstacle. However, if the unmanned vehicle is stopped, production will decrease. Therefore, in order to improve production, it is preferable to avoid obstacles without stopping the unmanned vehicle.

[0003] In the past, a vehicle control device having a function of generating a path to avoid contact between a vehicle and an obstacle is known (see Patent Document 1). The vehicle control device described in Patent Document 1 includes: an obstacle determination unit that calculates the distance and relative speed between the vehicle and the obstacle; a driving path determination unit that selects the driving path of the vehicle based on the distance and relative speed; and a driving path generation unit that generates a target driving path based on the selected driving path. The driving path determination unit selects one of the following first path, second path, and third path when an obstacle in the first lane is detected while driving in the second lane, wherein the first path is to drive in the second lane and drive to the center of the first lane after passing the obstacle, the second path is to drive from the second lane to the center of the first lane, and after driving in the center of the first lane, drive to the second lane and avoid the obstacle, and the third path is to drive from the second lane to a driving path that is closer to the obstacle avoidance direction than the center of the first lane, and after driving on the driving path that is closer to the obstacle avoidance direction, drive to the second lane and avoid the obstacle.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: Japanese Patent Application Publication No. 2021-70379 Summary of the invention

[0007] In the technology described in Patent Document 1, when there is an obstacle on the boundary line of the host vehicle's driving lane on the opposite side of the oncoming lane, the obstacle can be avoided by using the vicinity of the boundary line between the host vehicle's driving lane and the oncoming lane. However, in a mine or the like, when there is an obstacle such as a rock dropped from an unmanned vehicle near the boundary line between the host vehicle's driving lane and the oncoming lane, the technology described in Patent Document 1 cannot be used.

[0008] An object of the present invention is to provide an autonomous driving system that can avoid the obstacle and continue the driving of the transport vehicle even when the obstacle exists near a boundary line between the transport vehicle's driving lane and a lane adjacent to the driving lane.

[0009] An autonomous driving system according to one embodiment of the present invention includes a control device that controls a transport vehicle capable of autonomous driving along a driving path. The control device is configured to calculate, when an obstacle is located in a driving lane of the transport vehicle, a predicted arrival time, which is a time until the transport vehicle reaches the position of the obstacle, based on the position of the obstacle, the position and the driving speed of the transport vehicle, calculate a predicted position of other vehicles existing around the transport vehicle after the predicted arrival time has passed, based on the position of the obstacle and the predicted position of the other vehicles, determine whether the other vehicles are located near the obstacle after the predicted arrival time has passed, if it is determined that the other vehicles are located near the obstacle after the predicted arrival time has passed, set the driving lane as an avoidance area, and do not set a lane adjacent to the driving lane as an avoidance area, if it is determined that the other vehicles are not located near the obstacle after the predicted arrival time has passed, set both the driving lane and the lane adjacent to the driving lane as avoidance areas, and generate an avoidance path as the driving path for the transport vehicle to avoid the obstacle within the avoidance area based on the position of the transport vehicle, the position of the obstacle, and the avoidance area.

[0010] Effects of the Invention

[0011] According to the present invention, it is possible to provide an autonomous driving system that can continue driving a transport vehicle while avoiding the obstacle even when the obstacle exists near a boundary line between a driving lane of the transport vehicle and a lane adjacent to the driving lane. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 The diagram schematically shows a work site of an open-pit mine, and shows an unmanned vehicle having an autonomous driving system according to a first embodiment.

[0013] Figure 2 This is a diagram showing the structure of an unmanned vehicle.

[0014] Figure 3 This is a diagram showing the travel path of an unmanned vehicle traveling on a haulage road.

[0015] Figure 4A This is a diagram showing an example of the first table of map information.

[0016] Figure 4B It is a diagram showing an example of the second table of map information.

[0017] Figure 5 This is a flowchart showing an example of the flow of obstacle information calculation processing executed by the obstacle information calculation unit.

[0018] Figure 6 It is a schematic plan view showing the host vehicle traveling in the driving lane and other vehicles (oncoming vehicles) traveling in the oncoming lane.

[0019] Figure 7 This is a flowchart showing an example of the flow (main flow) of main calculation processing of the vehicle control device.

[0020] Figure 8 This is a flowchart showing an example of the flow of the avoidance area determination process executed by the avoidance path generation unit.

[0021] Fig. 9 This is a flowchart showing an example of the flow of the avoidance route generation process executed by the avoidance route generation unit.

[0022] Fig. 10A It is a diagram showing spatial distances corresponding to avoidance areas, and shows a case where a driving lane and an oncoming lane are set as avoidance areas.

[0023] Fig. 10B 1 is a diagram showing spatial distances corresponding to avoidance areas, and shows a case where only the driving lane is set as the avoidance area.

[0024] Fig.11A It is a diagram showing movement limit distances corresponding to avoidance areas, and shows a case where a driving lane and an oncoming lane are set as avoidance areas.

[0025] Fig. 11B It is a diagram showing movement limit distances corresponding to avoidance areas, and shows a case where only the driving lane is set as the avoidance area.

[0026] Fig.12 It is a schematic diagram showing a work site of an open-pit mine, showing a control station having an autonomous driving system according to a second embodiment.

[0027] Fig.13 This diagram shows the configuration of unmanned vehicles, mining machinery, and a control station.

[0028] Fig.14 This is a flowchart showing an example of the flow of the avoidance area determination process executed by the control server according to the second embodiment. DETAILED DESCRIPTION

[0029] The embodiments of the present invention are described with reference to the accompanying drawings. The following description shows specific examples of the contents of the present invention, and the present invention is not limited to these descriptions. Those skilled in the art can make various changes and modifications within the scope of the technical ideas disclosed in this specification. In addition, in all the drawings used to illustrate the present invention, parts with the same function are marked with the same reference numerals, and their repeated descriptions are sometimes omitted.

[0030] <First embodiment>

[0031] Reference Figures 1 to 11B , an autonomous driving system according to a first embodiment of the present invention is described. Figure 1 1 is a schematic diagram showing an operation site of an open-pit mine, showing an unmanned vehicle 20 having an autonomous driving system according to a first embodiment. Figure 1 As shown, at the work site of an open-pit mine, one or more mining machines 30 for excavating soil, sand, ore, etc., loading the excavated material onto an unmanned vehicle 20, and maintaining a transportation road 50, and one or more unmanned vehicles 20 for transporting the soil, sand, ore, etc. loaded from the mining machines 30 work in cooperation. In addition, in the figure, each unmanned vehicle 20 capable of autonomous driving is represented as 20-1, 20-2, ...

[0032] The unmanned vehicle 20 travels on a transport road 50 set according to the shape of the work site. The unmanned vehicle 20 is a transport vehicle that can travel autonomously without an operator on board. The unmanned vehicle 20 is, for example, a dump truck having a body 21 with a cargo box (cargo bucket) for loading goods and four wheels 22 provided on the body 21. In addition, in this first embodiment, the case where all the unmanned vehicles (dump trucks) 20 present at the work site have the same specifications (for example, the same maximum cargo capacity) and have the same functions is explained as an example. The mining machinery 30 is, for example, a hydraulic excavator having an operating device including a boom, a dipper arm and a bucket, a body on which the operating device is installed, and tracks provided on the body.

[0033] The unmanned vehicles 20 and the mining machine 30 are configured to be able to communicate with each other via a wireless communication line 40. Specifically, a plurality of wireless base stations 41 are provided at the work site, and the unmanned vehicles 20 and the mining machine 30 transmit and receive information to each other via these wireless base stations 41.

[0034] Figure 2 2 is a diagram showing the structure of the unmanned vehicle 20. Figure 2 As shown, the unmanned vehicle 20 has a vehicle control device 100, an external sensor 101, a load sensor 102, a position sensor 103, an orientation sensor 104, a speed sensor 105, a steering angle sensor 106, a travel drive device 107, a storage device 108, and a wireless communication device 109 as a hardware configuration. The autonomous driving system of the first embodiment includes the vehicle control device 100 and the storage device 108. Hereinafter, the unmanned vehicle 20 having these hardware and being a control target of the vehicle control device 100 is defined as the host vehicle 20A.

[0035] The wireless communication device 109 is a communication device capable of wirelessly communicating with the wireless base station 41 constituting a part of the wireless communication line 40, and has a communication interface including a communication antenna having a band region such as the 2.1 GHz band as an induction band region.

[0036] The travel drive device 107 steers the wheels 22 or rotates the wheels 22 based on the travel control command from the vehicle control device 100, thereby driving the vehicle body 21. The travel drive device 107 includes, for example, an engine, a generator driven by the engine, a travel motor (electric motor) that drives the wheels 22 with the power generated by the generator, a steering device that steers the wheels 22, and a braking device that applies braking force to the wheels 22.

[0037] The travel motor accelerates the vehicle body 21 by applying driving force to the wheel 22. The steering device has a steering motor (electric motor) for changing the steering angle. The braking device includes an electric braking device and a mechanical braking device. The electric braking device is a regenerative braking device that uses the regenerative torque generated based on the power generation of the travel motor as a braking force to reduce the travel speed. The mechanical braking device is a friction-type mechanical braking device that can generate a greater braking force than the electric braking device. The mechanical braking device is, for example, a disc brake device provided in the wheel hub of the wheel 22, which uses the friction force as a braking force to reduce the travel speed.

[0038] The vehicle control device 100 is composed of a computer having a processing device such as a CPU (Central Processing Unit), a volatile memory called a so-called RAM (Random Access Memory), a non-volatile memory such as a ROM (Read Only Memory), an input / output interface, and other peripheral circuits. These hardware cooperate to run the software and realize multiple functions. In addition, the vehicle control device 100 can be composed of one computer or multiple computers.

[0039] The non-volatile memory stores programs that can perform various operations and data necessary for various operations (thresholds for judging processing, and the width of the unmanned vehicle 20A, the lowest ground clearance, the space distance between the wheels 22, etc.). In other words, the non-volatile memory is a storage medium (storage device) that can read the program that realizes the functions of this embodiment. The volatile memory is a storage medium (storage device) that temporarily stores the calculation results based on the processing device and the signals input from the input and output interface. The processing device is a device that expands the program stored in the non-volatile memory in the volatile memory and performs calculations, and performs prescribed calculations on the data obtained from the input and output interface, the non-volatile memory and the volatile memory according to the program. The input unit of the input and output interface converts the signals input from various sensors 101 to 106 and the wireless communication device 109 into data that can be calculated by the processing device. In addition, the output unit of the input and output interface generates an output signal corresponding to the calculation results based on the processing device, and outputs the signal to the travel drive device 107 and the wireless communication device 109.

[0040] The external sensor 101 is a sensor for identifying objects around the unmanned vehicle 20. The external sensor 101 measures the relative three-dimensional position between the vehicle 20A and objects (such as obstacles, mining machinery 30 and other unmanned vehicles 20) around the vehicle 20A. In addition, the external sensor 101 may also have a function of measuring the distance between the vehicle 20A and the object based on the measured relative position. The external sensor 101 is, for example, a LIDAR (Light Detection And Ranging) that can use a laser to measure the relative three-dimensional position of the external sensor 101 and the object. In addition, millimeter wave radar, stereo camera, etc. can also be used for the external sensor 101.

[0041] The cargo sensor 102 is used to obtain the cargo amount of the host vehicle 20A. The cargo sensor 102 detects, for example, the load acting on the suspension of the host vehicle 20A or the pressure of the hydraulic oil in the hydraulic cylinder (suspension cylinder), and calculates the cargo amount of the host vehicle 20A based on the detection result.

[0042] The position sensor 103 is used to obtain the position of the host vehicle 20A (the position of the vehicle body 21), and the azimuth sensor 104 is used to obtain the azimuth of the host vehicle 20A (the direction of the vehicle body 21). The position sensor 103 and the azimuth sensor 104 have, for example, multiple antennas for GNSS (Global Navigation Satellite System) (hereinafter referred to as GNSS antennas), and a positioning calculation device that calculates the position of the vehicle body 21 represented by real coordinates in three-dimensional space and the angle from the reference azimuth, i.e., the azimuth, based on satellite signals (GNSS radio waves) from multiple positioning satellites received by the GNSS antennas. The position of the vehicle body 21 is represented by the position coordinates of the vehicle body 21 in the geographic coordinate system (global coordinate system), for example.

[0043] In addition, the position sensor 103 and the azimuth sensor 104 may also be composed of a GNSS antenna and a positioning operation device. In this case, the azimuth sensor 104 calculates the azimuth angle from the trajectory of the position of the vehicle body 21. In addition, the azimuth sensor 104 may have, for example, an IMU (Inertial Measurement Unit) and an operation device that calculates the azimuth angle from the time change of the angular acceleration information detected by the IMU.

[0044] The speed sensor 105 is used to obtain the running speed V of the host vehicle 20A (moving speed of the vehicle body 21). The speed sensor 105 is, for example, a wheel speed sensor that detects the rotation speed of the wheel 22. Alternatively, the speed sensor 105 may be a device that calculates the speed from the temporal change in the position of the vehicle body 21 calculated by the position sensor 103.

[0045] The steering angle sensor 106 is used to obtain the steering angle of the host vehicle 20A. The steering angle sensor 106 is, for example, an angle detection device such as an encoder attached to a steering device.

[0046] The vehicle control device 100 controls the operation of the host vehicle 20A. Figure 3 1 is a diagram showing a travel path 11 of an unmanned vehicle 20 traveling on a haul road 50 . Figure 3 The example in which the haul road 50 is composed of only the driving lane 51 on which the unmanned vehicle 20 is traveling is shown. However, the haul road 50 may also be composed of the driving lane 51 and the oncoming lane 52 adjacent to the driving lane 51 (see Figure 6 ) Figure 3 As shown, the vehicle control device 100 outputs a travel control command to the travel drive device 107 in order to make the host vehicle 20A autonomously travel along the travel path 11. The travel control command includes a brake operation amount, an accelerator operation amount, and a steering angle operation amount.

[0047] The driving path 11 is determined by a plurality of nodes 12. Information related to the plurality of nodes 12 (hereinafter also referred to as map information) is stored in the storage device 108 as described later. The driving path 11 is data representing a curve within the driving lane 10, and the nodes 12 are data representing coordinates on the driving path 11. The vehicle control device 100 may be configured to cause the vehicle 20A to autonomously drive in a manner that minimizes the deviation from the driving path 11, or may be configured to cause the vehicle 20A to autonomously drive in a manner that passes through the nodes 12. In the illustrated example, the driving path 11 is set as a curve passing through the center of the driving lane 10, but the driving path 11 may also be set at a position offset to either the left or right side from the center of the driving lane 10. In addition, in the illustrated example, the nodes 12 are arranged at equal intervals on the driving path 11, but may also be arranged at unequal intervals.

[0048] Figure 2 The storage device 108 shown is a non-volatile storage medium capable of reading data, and stores an OS (Operating System), various control programs, application programs, databases, etc. The storage device 108 includes a map information storage unit 181. The map information storage unit 181 stores the map information in a table format. Figure 4A as well as Figure 4B Map information shown.

[0049] Figure 4A is a diagram showing an example of the first table of map information. Figure 4B 2 is a diagram showing an example of the second table of map information. Figure 4A as well as Figure 4B As shown, the map information includes information such as the positions of nodes defining the travel route 11 , the slope, the speed limit, and the width of the lane. Figure 4A is map information about the route from the loading location to the unloading location, Figure 4B It is map information about the route from the unloading point to the loading point. In addition, although it is recorded separately in the first table and the second table, it can also be set as a data table that makes the first table and the second table continuous.

[0050] The vehicle 20A follows the first table (see Figure 4A ) is traveling on the driving path 11 specified by the node position, the first table becomes the map information about the driving lane 51, and the second table (refer to Figure 4B) becomes the map information about the oncoming lane 52. Hereinafter, another unmanned vehicle 20 traveling in the oncoming lane 52 adjacent to the lane in which the host vehicle 20A is traveling is defined as an oncoming vehicle 20B. In addition, in this specification, the control and operation when the host vehicle 20A is traveling along the driving path 11 specified by the node position of the first table are representatively described. In addition, when the host vehicle 20A is traveling along the driving path 11 specified by the node position of the second table (refer to Figure 4B ) is traveling on the driving path 11 specified by the node position, the second table becomes the map information about the driving lane, and the first table (refer to Figure 4A ) becomes map information about the oncoming lane.

[0051] In the first table, a node ID, a node position, a speed limit, a slope, and driving lane information are defined for each node. In the second table, a node ID, a node position, a speed limit, a slope, and oncoming lane information are defined for each node.

[0052] The node ID is information for identifying a node, and the node position is information for defining the path shape of the driving path 11. The node position is determined, for example, by the coordinates of a site coordinate system in which the coordinate origin is set at the work site. The site coordinate system is a two-dimensional orthogonal coordinate system consisting of X and Y coordinates. In addition, the node position can also be determined by the coordinates of a geographic coordinate system. The coordinates of the site coordinate system and the coordinates of the geographic coordinate system can be converted.

[0053] The speed limit of the travel path 11 is determined by considering at least one of the curvature and the slope of the travel path 11. In addition, the curvature of the travel path 11 can be obtained as the reciprocal of the radius of a circle having a predetermined number of nodes 12 on the circumference. In addition, the curvature of the travel path 11 can be obtained in advance by a manned driving test or the like as the reciprocal of the turning radius of the travel trajectory calculated from the azimuth angle of the vehicle body 21 or the time change of the position of the vehicle body 21 when the unmanned vehicle 20 is driven along the travel path 11.

[0054] The slope of the driving path 11 is the inclination of the driving path 11 relative to the horizontal direction. The lane information (driving lane information and oncoming lane information) is data that specifies the area where the unmanned vehicle 20 can travel, that is, the lane. In the work site of an open-pit mine, in most cases, there is no physical lane forming line (lane boundary line, center line, etc.) for forming a lane, which is a strip area for lane traffic. Therefore, in this specification, the area where the unmanned vehicle 20 can travel specified by the lane information stored in the storage device 108 is defined as a lane. In addition, the lane includes a driving lane 51 in which the host vehicle 20A travels, and an oncoming lane 52 in which the oncoming vehicle 20B travels.

[0055] In the present embodiment, when the unmanned vehicle 20 is located at the node 12 , the distances DL and DR from the node 12 in the left-right direction orthogonal to the traveling direction of the unmanned vehicle 20 are stored in the map information storage unit 181 as lane information.

[0056] Reference Figure 3 , an example of a driving lane 51 is described. In the present embodiment, a virtual lane-forming line 51L on the left side of the driving lane (driving area) is defined by the distance DL to the left from the node 12. Similarly, a virtual lane-forming line 51R on the right side of the driving lane (driving area) is defined by the distance DR to the right from the node 12. In other words, the lane-forming line 51L is equivalent to a virtual line connecting points that are separated from each other by the distance DL to the left from the plurality of nodes 12 of the driving path 11 constituting the driving lane 51. Similarly, the lane-forming line 51R is equivalent to a virtual line connecting points that are separated from each other by the distance DR to the right from the plurality of nodes 12 of the driving path 11 constituting the driving lane 51. In addition, in the present embodiment, the lane-forming line 51R on the right side functions as a center line that divides the driving lane 51 of the vehicle and the oncoming lane 52 (refer to Figure 6 ). In addition, for Figure 6 The same is true for the illustrated oncoming lane 52. That is, the lane formation lines 52L and 52R of the oncoming lane 52 are defined by the distances DL and DR as oncoming lane information.

[0057] Reference Figure 2 , the functions of the vehicle control device 100 are described in detail. Figure 2 1 is a functional block diagram of the vehicle control device 100. Figure 2 As shown, the vehicle control device 100 functions as an obstacle information calculation unit 111, an avoidance path generation unit 112, a control target generation unit 113, and an autonomous driving control unit 114 by the processing device executing a program stored in a nonvolatile memory.

[0058] The obstacle information calculation unit 111 detects the presence of the obstacle 90 in the traveling direction of the host vehicle 20A based on the detection result of the external sensor 101. The obstacle information calculation unit 111 calculates the position of the obstacle, the height of the obstacle, and the lateral width of the obstacle as information of the obstacle in the traveling direction of the host vehicle 20A based on the detection result of the external sensor 101. The position of the obstacle includes the position of the center of the obstacle and the positions of the upper, lower, left, and right ends of the obstacle. The height of the obstacle is calculated based on the positions of the upper and lower ends of the obstacle. The lateral width of the obstacle is calculated based on the positions of the left and right ends of the obstacle.

[0059] The avoidance path generation unit 112 generates an avoidance path as a new driving path for avoiding obstacles based on information about obstacles. In addition, "generating an avoidance path" means setting a plurality of nodes constituting the avoidance path. The control target generation unit 113 generates a control target including a target value of a driving speed, i.e., a target speed Vt, and a target value of a steering angle, i.e., a target steering angle, based on map information stored in the map information storage unit 181. In addition, when an avoidance path is generated, the control target generation unit 113 generates a control target for causing the vehicle 20A to travel along the avoidance path. That is, the control target generation unit 113 generates a control target based on the positions of the nodes constituting the avoidance path, ignoring the positions of the nodes of the map information within the range from the starting node to the end node of the avoidance path.

[0060] The autonomous driving control unit 114 generates a driving control command based on the control target generated by the control target generation unit 113, the driving speed V acquired by the speed sensor 105, and the steering angle acquired by the steering angle sensor 106. The autonomous driving control unit 114 outputs the generated driving control command to the driving drive device 107. As a result, each part of the driving drive device 107 is controlled, and the vehicle body 21 travels along the driving path 11 specified by the map information. In addition, when an avoidance path is generated, the vehicle body 21 travels along the avoidance path as a new driving path.

[0061] Reference Figure 5 as well as Figure 6 , detailing the computational processing of obstacle information. Figure 5 2 is a flowchart showing an example of the flow of obstacle information calculation processing executed by the obstacle information calculation unit 271 . Figure 5 The process shown in the flowchart is started, for example, when the ignition switch of the host vehicle 20A is turned on and the vehicle control device 100 is started, and is repeatedly executed in a predetermined control cycle (calculation cycle).

[0062] like Figure 5 As shown, in step S10 , the obstacle information calculation unit 111 acquires map information and sensor information indicating the detection result of the external sensor 101 from the map information storage unit 181 of the storage device 108 , and proceeds with the process to step S13 .

[0063] In step S13, the obstacle information calculation unit 111 detects obstacles existing in the traveling direction (in front) of the host vehicle 20A based on the sensor information of the external sensor 101 acquired in step S10. In step S15, the obstacle information calculation unit 111 calculates the information of the detected obstacle, that is, the position of the obstacle, and the parameters indicating the size of the obstacle, namely, the height and the width.

[0064] Reference Figure 6 , the calculation and processing of obstacle information performed by the obstacle information calculation unit 111 is described in detail. Figure 6 2 is a top view schematically showing the host vehicle 20A traveling in the driving lane 51 and another vehicle (oncoming vehicle) 20B traveling in the oncoming lane 52. The obstacle information calculation unit 111 calculates, for example, Figure 6 As shown, a rectangular parallelepiped 91 surrounds the obstacle 90. The obstacle information calculation unit 111 calculates the center of the lower bottom surface of the rectangular parallelepiped 91 as the position Po of the obstacle, calculates the height of the rectangular parallelepiped 91 from the ground (the height from the lower bottom surface to the upper bottom surface of the rectangular parallelepiped 91) as the height Ho of the obstacle, and calculates the length of the rectangular parallelepiped 91 in the horizontal direction (left-right direction) perpendicular to the driving path 11 as the lateral width Wo of the obstacle. Figure 5 In step S13 shown in the figure, when the calculation processing of the information (position, size) of the obstacle 90 is completed, the processing proceeds to step S15.

[0065] In step S15, the obstacle information calculation unit 111 determines whether the obstacle 90 exists in the driving lane (travelable area) 10 based on the information of the obstacle 90 calculated in step S13. When at least a part of the rectangular parallelepiped 91 exists in the driving lane 10 when viewed from above, the obstacle information calculation unit 111 determines that the obstacle 90 exists in the driving lane 10. When the entire rectangular parallelepiped 91 does not exist in the driving lane 10 when viewed from above, the obstacle information calculation unit 111 determines that the obstacle 90 does not exist in the driving lane 10. In step S15, when it is determined that the obstacle 90 exists in the driving lane 10, the processing proceeds to step S17. In step S15, when it is determined that the obstacle 90 does not exist in the driving lane 10, the processing proceeds to step S19.

[0066] In step S17, the obstacle information calculation unit 111 calculates the obstacle information based on the position Po of the obstacle 90 and the first table of map information (see Figure 4A ), and determines the node position closest to the position Po of the obstacle 90 in the driving lane 10. The obstacle information calculation unit 111 sets the node ID of the determined node position as the driving lane obstacle IDdx. The obstacle information calculation unit 111 calculates the node ID of the determined node position based on the position Po of the obstacle 90 and the second table of the map information (refer to Figure 4B ), and determines the node position closest to the obstacle position Po in the oncoming lane 52. The obstacle information calculation unit 111 sets the node ID of the determined node position as the oncoming lane obstacle IDox.

[0067] In step S19 , when the driving lane obstacle IDdx and the oncoming lane obstacle IDox are set, the obstacle information calculation unit 111 cancels these settings.

[0068] If the setting process of the driving lane obstacle IDdx and the oncoming lane obstacle IDox (step S17) or the setting cancellation process of the driving lane obstacle IDdx and the oncoming lane obstacle IDox (step S19) is completed, then the control cycle in this control cycle is completed. Figure 5 The processing shown in the flowchart is completed.

[0069] Reference Figures 7 to 11B , detailing the generation process of the avoidance path and the generation process of the control target. Figure 7 This is a flowchart showing an example of the flow (main flow) of the main calculation processing of the vehicle control device 100 . Figure 7 The process shown in the flowchart is started, for example, when the ignition switch of the host vehicle 20A is turned on and the vehicle control device 100 is activated, and is repeatedly executed in a predetermined control cycle (calculation cycle).

[0070] like Figure 7 As shown, in step S20, the avoidance path generation unit 112 determines whether the driving lane obstacle IDdx and the oncoming lane obstacle IDox are set by the obstacle information calculation unit 111. The processing of step S20 is equivalent to the processing of detecting the obstacle 90 in front of the host vehicle 20A and determining whether the detected obstacle 90 exists in the driving lane 10. In the case where it is determined that the obstacle IDdx and IDox are set, that is, in the case where the obstacle 90 is detected in front of the host vehicle 20A and it is determined that the detected obstacle 90 exists in the driving lane 10, the processing proceeds to step S23. In step S20, if it is determined that the obstacle IDdx and IDox are not set, the control cycle in this control cycle is Figure 7 That is, when no obstacle 90 is detected in front of the vehicle 20A, or when it is determined that the detected obstacle 90 does not exist in the driving lane 10, there is no obstacle that may collide with the vehicle 20A, and thus, the vehicle 20A travels along the driving path 11 based on the map information.

[0071] In step S23 , the avoidance path generation unit 112 acquires the position of the host vehicle 20A from the position sensor 103 , acquires the travel speed V of the host vehicle 20A from the speed sensor 105 , and proceeds to step S26 .

[0072] In step S26, the avoidance path generation unit 112 obtains the node position (coordinates) of the driving lane obstacle IDdx set in step S17. The avoidance path generation unit 112 calculates the distance along the driving path 11 from the position of the host vehicle 20A to the node position of the driving lane obstacle IDdx based on the node position of the driving lane obstacle IDdx and the position of the host vehicle 20A obtained in step S23. The avoidance path generation unit 112 calculates the time until the host vehicle 20A reaches the node position of the driving lane obstacle IDdx, that is, the predicted arrival time Ta, based on the calculated distance and the driving speed V of the host vehicle 20A obtained in step S23.

[0073] In step S30, the avoidance path generation unit 112 determines an avoidance area (avoidance area) in the haul road 50 based on the predicted arrival time Ta, the positional relationship between the other vehicle 20B and the obstacle 90, the cargo volume of the own vehicle 20A and the other vehicle 20B, and the slope of the travel path 11, and proceeds to step S60. Figure 8 , the avoidance area determination process (step S30) is described in detail.

[0074] Figure 8 1 is a flowchart showing an example of the process of determining the avoidance area performed by the avoidance path generation unit 112. The avoidance area determination process (step S30) is first performed in step S131. The avoidance path generation unit 112 sets the variable k to 1 and advances the process to step S133. In addition, the variable k is a unique number assigned to each unmanned vehicle 20 existing at the work site. The variable k is a natural number that is incremented by one each time in step S139 described later. Hereinafter, the unmanned vehicle 20 assigned with the variable k is also referred to as the kth unmanned vehicle 20.

[0075] The unmanned vehicle 20 at the work site obtains the detection information of the position sensor 103 and the speed sensor 105 of the unmanned vehicle 20 according to the prescribed control cycle, and transmits it to other unmanned vehicles 20 via the wireless communication line 40. In step S133, the avoidance path generation unit 112 obtains the position Pk and the travel speed Vk of the unmanned vehicle 20 from the kth unmanned vehicle 20, and proceeds to step S135.

[0076] In step S135, the avoidance path generation unit 112 calculates the travel distance Dk (Dk=Vk·Ta) of the kth unmanned vehicle based on the travel speed Vk obtained in step S133 and the predicted arrival time Ta calculated in step S26. The avoidance path generation unit 112 calculates the predicted position Pka of the kth unmanned vehicle 20 at the time point of the predicted arrival time Ta based on the position Pk of the unmanned vehicle 20 obtained in step S133, the travel path 11 of the unmanned vehicle 20 included in the map information, and the travel distance Dk. The avoidance path generation unit 112 determines the node position closest to the predicted position Pka, and sets the node ID of the determined node position as the predicted position IDk of the other vehicle.

[0077] In the next step S137, the avoidance path generation unit 112 determines whether the k-th unmanned vehicle 20 is present in the vicinity of the obstacle 90 after the predicted arrival time Ta has passed (at the passing time point) based on the oncoming lane obstacle IDox set in step S17 and the predicted position IDk of the other vehicle set in step S135. If there is no oncoming lane obstacle IDox within a predetermined predetermined distance Dp from the node position of the predicted position IDk of the other vehicle, the avoidance path generation unit 112 determines that the k-th unmanned vehicle 20 is not present in the vicinity of the obstacle 90 after the predicted arrival time Ta has passed, and the process proceeds to step S139. If there is an oncoming lane obstacle IDox within a predetermined distance Dp from the node position of the predicted position IDk of the other vehicle, the avoidance path generation unit 112 determines that the k-th unmanned vehicle 20 is present in the vicinity of the obstacle 90 after the predicted arrival time Ta has passed, and the process proceeds to step S143.

[0078] In step S139, the avoidance path generation unit 112 adds 1 to the variable k and proceeds to step S141. In step S141, the avoidance path generation unit 112 determines whether the variable k is greater than the variable threshold value kx. The variable threshold value kx corresponds to the total number of unmanned vehicles 20 to which the variable k is assigned in the work site. In step S141, if it is determined that the variable k set in step S139 is less than the variable threshold value kx, the process returns to step S133. In addition, in step S141, if it is determined that the variable k set in step S139 is greater than the variable threshold value kx, the process proceeds to step S153. Therefore, if the processes of steps S133 to S137 are executed for a certain unmanned vehicle 20 and a negative determination is made in step S137, the processes of steps S133 to S137 are similarly executed for the next unmanned vehicle 20.

[0079] The unmanned vehicle 20 at the work site obtains the detection information of the cargo sensor 102 of the unmanned vehicle 20 according to the prescribed control cycle, and transmits it to other unmanned vehicles 20 via the wireless communication line 40. In step S143, the avoidance path generation unit 112 obtains the cargo volume of the host vehicle 20A from the cargo sensor 102, and obtains the cargo volume of the unmanned vehicle 20 from the k-th unmanned vehicle 20, and proceeds to step S144. In addition, in the processing after step S143, for the convenience of explanation, the k-th unmanned vehicle 20 is also referred to as the oncoming vehicle 20B.

[0080] In step S144, the avoidance path generation unit 112 determines the cargo state of the host vehicle 20A and the cargo state of the oncoming vehicle 20B. When the cargo amount of the host vehicle 20A obtained in step S143 is greater than the cargo amount threshold, the avoidance path generation unit 112 determines the cargo state of the host vehicle 20A as a loaded state. When the cargo amount of the host vehicle 20A is less than the cargo amount threshold, the avoidance path generation unit 112 determines the cargo state of the host vehicle 20A as an unloaded state. Similarly, when the cargo amount of the unmanned vehicle 20 obtained in step S143 is greater than the cargo amount threshold, the avoidance path generation unit 112 determines the cargo state of the unmanned vehicle 20 as a loaded state. When the cargo amount of the unmanned vehicle 20 is less than the cargo amount threshold, the avoidance path generation unit 112 determines the cargo state of the unmanned vehicle 20 as an unloaded state.

[0081] In step S145, the avoidance path generation unit 112 determines whether the loading state of the host vehicle 20A is loaded and the loading state of the oncoming vehicle 20B is unloaded. In step S145, if it is determined that the loading state of the host vehicle 20A is loaded and the loading state of the oncoming vehicle 20B is unloaded, the process proceeds to step S153. In step S145, if it is determined that at least one of the loading state of the host vehicle 20A is unloaded and the loading state of the oncoming vehicle 20B is loaded is satisfied, the process proceeds to step S147.

[0082] Furthermore, the specifications of the host vehicle 20A and the oncoming vehicle 20B are the same, and therefore, if an affirmative determination is made in step S145 , this means that the cargo volume of the host vehicle 20A is greater than the cargo volume of the oncoming vehicle 20B.

[0083] In step S147, the avoidance path generation unit 112 obtains the slope of the driving path 11 after the host vehicle 20A passes the obstacle 90, that is, the slope of multiple nodes 12 of the driving path 11 that constitutes the back side of the obstacle 90 as viewed from the host vehicle 20A, and advances the processing to step S149. In addition, the slopes of the multiple nodes 12 obtained by step S147 are the slopes of the nodes 12 in front of the host vehicle 20A (in the direction of travel) from the driving lane obstacle IDdx, and are the slopes of the nodes 12 that exist within a predetermined acceleration distance Da from the driving lane obstacle IDdx. The acceleration distance Da is, for example, the distance in which the vehicle body 21 that has been decelerated due to the avoidance action is accelerated to the speed limit specified by the map information (refer to Figure 4A ) is determined by adding a margin value to the required distance.

[0084] In step S149, the avoidance path generation unit 112 determines whether the slopes of the plurality of nodes 12 acquired in step S147 include a slope greater than 0 (zero). The fact that the slopes of the plurality of nodes 12 acquired in step S147 include a slope greater than 0 (zero) means that there is an uphill slope on the back side of the obstacle 90 viewed from the host vehicle 20A and within the acceleration distance Da from the obstacle 90. On the other hand, the fact that the slopes of the plurality of nodes 12 acquired in step S147 do not include a slope greater than 0 means that there is no uphill slope on the back side of the obstacle 90 viewed from the host vehicle 20A and within the acceleration distance Da from the obstacle 90.

[0085] In step S149, if it is determined that the slopes of the plurality of nodes 12 acquired in step S147 do not include a slope greater than 0, the process proceeds to step S151. In step S149, if it is determined that the slopes of the plurality of nodes 12 acquired in step S147 include a slope greater than 0, the process proceeds to step S153.

[0086] The processing from step S143 to step S149 is equivalent to the processing of determining whether the driving priority of the host vehicle 20A is higher or lower than the driving priority of the oncoming vehicle 20B. In the first embodiment, when a negative determination is made by the determination processing of step S145 and a negative determination is made by the determination processing of step S149, it is determined that the driving priority of the host vehicle 20A is lower than the driving priority of the oncoming vehicle 20B, and the processing proceeds to step S151. On the other hand, when a positive determination is made by the determination processing of step S145 or when a positive determination is made by the determination processing of step S149, it is determined that the driving priority of the host vehicle 20A is higher than the driving priority of the oncoming vehicle 20B, and the processing proceeds to step S153.

[0087] In step S151, the avoidance path generation unit 112 determines only the driving lane 51 as the area that can be used for avoidance (avoidance area). In step S153, the avoidance path generation unit 112 determines the driving lane 51 and the oncoming lane 52 as the area that can be used for avoidance (avoidance area). When the avoidance area determination process (step S151 or step S153) is completed, the control cycle in this control cycle is completed. Figure 8 The processing shown in the flowchart is completed.

[0088] like Figure 7 As shown in FIG. 1 , if the avoidance area determination process (step S30) is completed, the process proceeds to step S60. In step S60, the avoidance path generation unit 112 generates an avoidance path for avoiding the obstacle 90 based on the avoidance area determined in step S30, and the process proceeds to step S90. Fig. 9 , details the generation process of the avoidance path.

[0089] Fig. 9 1 is a flowchart showing an example of the process of generating an avoidance path performed by the avoidance path generating unit 112. In the avoidance path generating unit (step S90), first, in step S161, the avoidance path generating unit 112 determines whether two or more obstacles 90 are detected in the avoidance area by the external sensor 101. If the avoidance path generating unit 112 determines that two or more obstacles 90 are detected in the avoidance area, the process proceeds to step S163. In step S163, the avoidance path generating unit 112 does not generate an avoidance path and decides to stop the vehicle 20A. Fig. 9 The processing shown in the flowchart is completed.

[0090] In step S161, if it is determined that two or more obstacles 90 are not detected by the external sensor 101 in the avoidance area, that is, if it is determined that there is only one obstacle 90 in the avoidance area detected by the external sensor 101, the processing proceeds to step S165.

[0091] In step S165 , the avoidance path generation unit 112 calculates left and right spatial distances Ds1 and Ds2 of the obstacle 90 as viewed from the host vehicle 20A based on the position Po of the obstacle 90 , the lateral width Wo of the obstacle 90 , and the avoidance area.

[0092] Reference Fig. 10A as well as Fig. 10B , indicating the spatial distances Ds1 and Ds2 corresponding to the avoidance area. Fig. 10A as well as Fig. 10B It is a diagram showing the spatial distances corresponding to the avoidance areas.

[0093] Fig. 10AThis indicates that the driving lane 51 and the oncoming lane 52 are set as avoidance areas. Fig. 10B This shows a case where only the driving lane 51 is set as the avoidance area. Fig. 10A as well as Fig. 10B In the figure, the avoidance area is indicated by shading of diagonal lines.

[0094] like Fig. 10A as well as Fig. 10B As shown in FIG. 1 , the spatial distance Ds1 corresponds to the distance from the left end of the obstacle 90 to the left boundary line of the avoidance area (that is, the lane formation line 51L). Fig. 10A As shown, when the avoidance area is composed of the driving lane 51 and the oncoming lane 52, the spatial distance Ds2 corresponds to the distance from the right end of the obstacle 90 to the right boundary line of the avoidance area (that is, the lane formation line 52L). Fig. 10B As shown, when the avoidance area is composed of only the driving lane 51, the spatial distance Ds2 corresponds to the distance from the right end of the obstacle 90 to the right boundary line of the avoidance area (that is, the lane formation line 51R).

[0095] Therefore, by Fig. 9 The value of the spatial distance Ds2 calculated in the process of step S165 will differ depending on the set avoidance area. When the calculation process of the spatial distances Ds1 and Ds2 (step S165) is completed, the process proceeds to step S167.

[0096] In step S167, the avoidance path generation unit 112 determines whether the host vehicle 20A can pass from the side of the obstacle 90 without contact with the obstacle 90. In the present embodiment, in step S167, the avoidance path generation unit 112 determines whether the spatial distances Ds1 and Ds2 calculated in step S165 are less than the vehicle width Wb of the host vehicle 20A. When the spatial distance Ds1 is less than the vehicle width Wb and the spatial distance Ds2 is less than the vehicle width Wb, the avoidance path generation unit 112 determines that the host vehicle 20A cannot pass from the side of the obstacle 90 without contact with the obstacle 90, and the process proceeds to step S173. On the other hand, when at least one of the spatial distance Ds1 and the spatial distance Ds2 is greater than the vehicle width Wb, the avoidance path generation unit 112 determines that the host vehicle 20A can pass from the side of the obstacle 90 without contact with the obstacle 90, and the process proceeds to step S169.

[0097] In step S169, the avoidance path generation unit 112 generates a detour path passing from the side of the obstacle 90 based on the position of the host vehicle 20A, the position of the obstacle 90, and the avoidance area. The detour path is set to have a node of the driving path 11 in front of the host vehicle 20A and near the obstacle 90 as a starting point and a node of the driving path 11 in front of the host vehicle 20A and behind the obstacle 90 as an end point. In addition, the avoidance path generation unit 112 generates a path passing through the center of the larger space between the spatial distance Ds1 and the spatial distance Ds2 as a detour path.

[0098] In addition, the method of generating the detour path is not limited to this. For example, the avoidance path generation unit 112 may generate the detour path as follows. When the spatial distance Ds1 and the spatial distance Ds2 are respectively greater than the vehicle width Wb, the avoidance path generation unit 112 generates a left-side detour path passing through the center of the space on the left side of the obstacle 90 and a right-side detour path passing through the center of the space on the right side of the obstacle 90. The avoidance path generation unit 112 selects the path with the smallest change in the forward route from the driving path 11 as the detour path candidate.

[0099] In addition, in the present embodiment, the bypass path is generated in such a manner that the center of the vehicle body 21 passes through the center of the space on the side of the obstacle 90 when viewed from above. In addition, the method of generating the bypass path is not limited to this. The bypass path only needs to be a path for the vehicle body 21 to pass from the side of the obstacle 90. Therefore, the bypass path may be generated, for example, so that a position deviated from the center of the vehicle body 21 to either the left or right side passes through the center of the space on the side of the obstacle 90 when viewed from above.

[0100] When the detour route generation process (step S169) is completed, the process proceeds to step S171. In step S171, the time required to pass through the detour route generated in step S169, that is, the first required time Tb is calculated. Specifically, the avoidance route generation unit 112 calculates the first required time Tb (Tb=L1 / V) based on the path length L1 from the start point to the end point of the detour route and the travel speed V of the host vehicle 20A acquired in step S23.

[0101] When it is determined that the host vehicle 20A cannot pass the obstacle 90 from the side without contacting the obstacle 90 (YES in step S167 ), in step S173 , the avoidance route generation unit 112 does not generate a detour route and sets an invalid value to the time required for the detour.

[0102] When the calculation process of the first required passage time Tb (step S171) or the invalid value setting process of the first required passage time Tb (step S173) is completed, the process proceeds to step S175. In step S175, the avoidance route generation unit 112 determines whether the crossing route generation condition is satisfied.

[0103] The crossing path generation condition is satisfied when both of the following (condition A) and (condition B) are satisfied, and is not satisfied when at least one of (condition A) and (condition B) is not satisfied.

[0104] (Condition A) The host vehicle 20A can pass over the obstacle 90 without making contact with the obstacle 90 .

[0105] (Condition B) The host vehicle 20A can pass over the obstacle 90 without departing from the avoidance area.

[0106] The avoidance path generator 112 determines that (condition A) is satisfied when the spatial distance Dw between the left and right wheels 22 of the host vehicle 20A is greater than the lateral width Wo of the obstacle 90 and the minimum ground clearance Cr of the host vehicle 20A is greater than the height Ho of the obstacle 90 .

[0107] The avoidance path generation unit 112 calculates the shortest distance Do from the travel path 11 to the position Po of the obstacle 90 based on the position Po of the obstacle 90. The avoidance path generation unit 112 calculates the shortest distance Do from the travel path 11 to the position Po of the obstacle 90 based on the map information (see Figure 4A as well as Figure 4B ), calculate the moving limit distance Do0 corresponding to the avoidance area.

[0108] Reference Fig.11A as well as Fig. 11B , indicating the moving limit distance Do0 corresponding to the avoidance area. Fig.11A as well as Fig. 11B A diagram showing the movement limit distance Do0 corresponding to the avoidance area. Fig.11A This indicates that the driving lane 51 and the oncoming lane 52 are set as avoidance areas. Fig. 11B This shows a case where only the driving lane 51 is set as the avoidance area. Fig.11A as well as Fig. 11B In the figure, the avoidance area is indicated by shading of diagonal lines.

[0109] like Fig.11A as well as Fig. 11B As shown in FIG. 1 , the limit distance Do0 corresponds to the maximum value of the distance that the vehicle body 21 can move laterally without leaving the avoidance area. In addition, leaving the avoidance area means that a part of the vehicle 20A overflows to the outside of the avoidance area when viewed from above. Fig.11AAs shown, when the avoidance area is composed of the driving lane 51 and the oncoming lane 52, the movement limit distance Do0 is calculated by, for example, subtracting 1 / 2 of the vehicle width Wb from the distance Do2 from the driving path 11 of the driving lane 51 to the lane formation line 52L of the oncoming lane 52 (Do0=Do2-Wb / 2). In addition, although not shown in the figure, the movement limit distance Do0 is preferably obtained by subtracting 1 / 2 of the vehicle width Wb from the distance Do2 and further subtracting a predetermined margin value.

[0110] like Fig. 11B As shown, when the avoidance area is composed of only the driving lane 51, the movement limit distance Do0 is calculated by, for example, subtracting 1 / 2 of the vehicle width Wb from the distance Do1 from the driving path 11 of the driving lane 51 to the lane forming line 51R of the driving lane 51 (Do0=Do1-Wb / 2). In addition, although not shown in the figure, the movement limit distance Do0 is preferably obtained by subtracting 1 / 2 of the vehicle width Wb from the distance Do1 and further subtracting a predetermined margin value.

[0111] The avoidance path generation unit 112 determines that (condition B) is satisfied when the shortest distance Do from the position Po of the obstacle 90 to the travel path 11 is less than the movement limit distance Do0. Fig.11A In the example shown, the shortest distance Do is less than the limit distance Do0, thus satisfying (condition B). When the shortest distance Do from the position Po of the obstacle 90 to the driving path 11 is greater than the limit distance Do0, the avoidance path generation unit 112 determines that (condition B) is not satisfied. Fig. 11B In the example shown, the shortest distance Do is greater than the movement limit distance Do0, and thus (condition B) is not satisfied.

[0112] Fig. 9 In step S175 shown in FIG. 1 , when it is determined that the crossing path generation condition is satisfied, the process proceeds to step S177 , and when it is determined that the crossing path generation condition is not satisfied, the process proceeds to step S187 .

[0113] In step S177, the avoidance path generation unit 112 generates a crossing path as a path that crosses the obstacle 90. The crossing path is set to have a node of the driving path 11 in front of the vehicle 20A and near the obstacle 90 as a starting point, and a node of the driving path 11 in front of the vehicle 20A and on the back of the obstacle 90 as an end point. In the present embodiment, the crossing path is generated in such a way that the center of the vehicle body 21 passes directly above the position (center position) Po of the obstacle 90. In addition, the method for generating the crossing path is not limited to this. The crossing path only needs to be a path for the vehicle body 21 to pass directly above the obstacle 90. Therefore, the crossing path can also be generated, for example, to pass through the position (center position) Po of the obstacle 90 at a position deviated from the center of the vehicle body 21 to either side.

[0114] When the generation process of the crossing path (step S177) is completed, the process proceeds to step S179. In step S179, the time required to pass the crossing path generated in step S177, that is, the second required time Tc is calculated. Specifically, the avoidance path generation unit 112 calculates the second required time Tc (Tc=L2 / V) based on the path length L2 from the start point to the end point of the crossing path and the travel speed V of the host vehicle 20A acquired in step S23.

[0115] When the calculation process of the second required passage time Tc (step S179) is completed, the process proceeds to step S181. In step S181, the avoidance path generation unit 112 determines whether an invalid value is set for the first required passage time Tb. In step S181, if it is determined that an invalid value is not set for the first required passage time Tb, the process proceeds to step S183, and if it is determined that an invalid value is set for the first required passage time Tb, the process proceeds to step S185.

[0116] In step S183, the avoidance path generation unit 112 determines whether the first required time Tb is greater than the second required time Tc. In step S183, if it is determined that the first required time Tb is greater than the second required time Tc, the process proceeds to step S185, and if it is determined that the first required time Tb is less than the second required time Tc, the process proceeds to step S189.

[0117] In step S187, the avoidance path generation unit 112 performs the same processing as step S181. In step S187, if it is determined that an invalid value is not set for the first required passage time Tb, the process proceeds to step S189, and if it is determined that an invalid value is set for the first required passage time Tb, the process proceeds to step S163.

[0118] In step S185, the avoidance path generation unit 112 sets the crossing path generated in step S177 as the avoidance path, and ends the control cycle. Fig. 9 In step S189, the avoidance path generation unit 112 sets the detour path generated in step S169 as the avoidance path, and ends the control cycle. Fig. 9 The process is shown in the flowchart.

[0119] like Figure 7 As shown, if the avoidance path generation process (step S60) is completed, the process proceeds to step S90. When the avoidance path is generated, in step S90, the control target generation unit 113 generates a control target (including a target speed Vt and a target steering angle) for causing the vehicle body 21 to travel along the avoidance path. In order to cause the vehicle body 21 to travel along the avoidance path, the control target generation unit 113 sets the target speed Vt of the node between the starting point and the end point of the avoidance path to be lower than the speed limit set for the nodes at the starting point and the end point of the avoidance path. In addition, the autonomous driving control unit 114 generates a driving control instruction based on the control target. The generated driving control instruction is output to the driving drive device 107. As a result, the various parts of the driving drive device 107 are controlled, and the vehicle body 21 travels along the avoidance path.

[0120] When a crossing path is generated as an avoidance path in step S60, the target value of the running speed of the host vehicle 20A, i.e., the target speed Vt, is set as follows. The control target generation unit 113 sets the target speed Vt of the host vehicle 20A in the crossing path to be smaller as the height Ho of the obstacle 90 is higher (that is, as the value obtained by subtracting the height Ho of the obstacle 90 from the lowest ground clearance Cr of the host vehicle 20A is smaller). In addition, the control target generation unit 113 sets the target speed Vt of the host vehicle 20A in the crossing path to be smaller as the lateral width Wo of the obstacle 90 is larger (that is, as the value obtained by subtracting the lateral width Wo of the obstacle 90 from the spatial distance Dw between the left and right wheels 22 of the host vehicle 20A is smaller). By making the vehicle body 21 travel at a low speed, the path following performance of the host vehicle 20A for the avoidance path can be improved. As a result, the contact between the host vehicle 20A traveling along the crossing path and the obstacle 90 can be more reliably prevented.

[0121] When it is determined that the vehicle 20A cannot pass through the obstacle 90 from the side or the top without contact with the obstacle 90 (No in step S175, Yes in S187), no avoidance path is generated, and it is decided to stop the vehicle 20A (step S163). In this case, in step S90, the control target generation unit 113 sets the target speed Vt of the node in front of the obstacle 90 from the perspective of the vehicle 20A to 0 (zero). In addition, the autonomous driving control unit 114 generates a driving control instruction based on the control target. The generated driving control instruction is output to the driving drive device 107. As a result, the various parts of the driving drive device 107 are controlled, and the vehicle 20A stops in front of the obstacle 90.

[0122] In addition, when there is an oncoming vehicle 20B and the generated avoidance path is a detour path passing through the oncoming lane 52, the vehicle control device 100 generates an intrusion prohibition instruction and sends the generated intrusion prohibition instruction to the oncoming vehicle 20B via the wireless communication device 109. The intrusion prohibition instruction is a control instruction that prohibits intrusion into an area closer to the vehicle 20A side than the end point of the avoidance path before the vehicle 20A reaches the end point of the avoidance path (detour path).

[0123] If the unmanned vehicle 20 (oncoming vehicle 20B) receives an intrusion prohibition instruction, the driving speed of the unmanned vehicle 20 (oncoming vehicle 20B) is slowed down in such a way that the unmanned vehicle 20 (oncoming vehicle 20B) does not intrude into the detour path before the unmanned vehicle 20 (own vehicle 20A) completes the passage of the avoidance path (detour path), or the unmanned vehicle 20 (oncoming vehicle 20B) is slowed down.

[0124] -action-

[0125] The operation of the vehicle 20A when an obstacle 90 is detected in front of the vehicle 20A in the driving lane 51 of the vehicle 20A is described. If the vehicle control device 100 detects the obstacle 90, it calculates the predicted arrival time Ta. When the vehicle control device 100 determines that there is no oncoming vehicle 20B near the obstacle 90 at the time point of the predicted arrival time Ta, it sets an avoidance area including not only the driving lane 51 but also the oncoming lane 52. As a result, the avoidance action using the oncoming lane 52 can be performed.

[0126] Even when it is determined that the oncoming vehicle 20B is present near the obstacle 90 at the time point of the predicted arrival time Ta, the vehicle control device 100 sets the driving lane 51 and the oncoming lane 52 as the avoidance area when the driving priority of the host vehicle 20A is higher than that of the oncoming vehicle 20B. In this case, the host vehicle 20A outputs an intrusion prohibition command to the oncoming vehicle 20B to decelerate or stop the oncoming vehicle 20B. In this way, the driving (avoidance) of the host vehicle 20A can be prioritized.

[0127] The fuel consumption in the case of re-acceleration in a loaded state is greater than the fuel consumption in the case of re-acceleration in an unloaded state. In the case where the cargo state of the vehicle 20A is loaded and the cargo state of the oncoming vehicle 20B is unloaded, if it is assumed that the avoidance area is set only in the driving lane 51 to give priority to the driving of the oncoming vehicle 20B, it is not preferred from the perspective of fuel consumption. In this case, the fuel consumption used by the vehicle 20A from deceleration and re-acceleration is greater than the case of giving priority to the driving of the vehicle 20A and re-accelerating other vehicles 20B. The result is that the operating cost when the work site is considered as a whole increases. In contrast, in the present embodiment, when the cargo state of the vehicle 20A is loaded and the cargo state of the oncoming vehicle 20B is unloaded, the avoidance area is set not only in the driving lane 51 but also in the oncoming lane 52. As a result, the reduction in driving speed can be reduced in the avoidance action of the vehicle 20A. The result is that the productivity of the work site as a whole can be improved.

[0128] In the driving path 11 after the vehicle 20A avoids the obstacle 90, when there is an uphill slope near the obstacle 90, the fuel consumption of the vehicle 20A becomes larger than when there is no uphill slope. This is because the re-acceleration on the uphill slope consumes more fuel than the re-acceleration on the flat ground and downhill slope. In this embodiment, when there is an uphill slope near the obstacle 90, the avoidance area is expanded, and the reduction amount of the driving speed in the avoidance action of the vehicle 20A is reduced, thereby improving the productivity of the entire work site.

[0129] When the crossing path generation condition is satisfied, the vehicle control device 100 generates the crossing path. When no detour path is generated, or when a detour path is generated but the first required time Tb is greater than the second required time Tc, the vehicle body 21 is driven along the crossing path. Thus, the host vehicle 20A can efficiently perform the avoidance action with respect to the obstacle 90.

[0130] In addition, when the space on the left and right sides of the obstacle 90 in the avoidance area is narrow, the detour path is not generated. In addition, when the crossing path generation condition is not satisfied, the crossing path is not generated. The vehicle control device 100 stops the host vehicle 20A when neither the crossing path nor the detour path is generated. Therefore, even when the avoidance path is not generated, the contact between the host vehicle 20A and the obstacle 90 can be appropriately prevented.

[0131] According to the above-mentioned embodiment, the following effects are achieved.

[0132] (1) In the present embodiment, the autonomous driving system is mounted on the unmanned vehicle (transport vehicle) 20. The autonomous driving system includes a vehicle control device (control device) 100 for controlling the host vehicle (transport vehicle) 20A that can autonomously travel along the travel path 11. When an obstacle 90 is located in the travel lane 51 of the host vehicle 20A, the vehicle control device 100 calculates the time until the host vehicle 20A reaches the position Po of the obstacle 90, that is, the predicted arrival time Ta ( Figure 7 Steps S20, S23, S26).

[0133] The vehicle control device 100 calculates the predicted position Pka (Pk) of the other vehicle 20B after the predicted arrival time Ta has passed, based on the position Pk and the travel speed Vk of the other vehicle 20B existing around the host vehicle 20A and the predicted arrival time Ta. Figure 8 The vehicle control device 100 determines whether the other vehicle 20B is near the obstacle 90 after the predicted arrival time Ta has passed, based on the position Po of the obstacle 90 and the predicted position Pka of the other vehicle 20B ( Figure 8 When the vehicle control device 100 determines that the other vehicle 20B is present near the obstacle 90 after the predicted arrival time Ta has passed, the vehicle control device 100 sets the driving lane 51 as the avoidance area, and does not set the lane adjacent to the driving lane 51, that is, the oncoming lane 52, as the avoidance area ( Figure 8 If the vehicle control device 100 determines that the other vehicle 20B is not near the obstacle 90 after the predicted arrival time Ta has passed, the vehicle control device 100 sets both the driving lane 51 and the oncoming lane 52 as the avoidance area ( Figure 8 The vehicle control device 100 generates an avoidance path ( ) in the avoidance area as a travel path for the host vehicle 20A to avoid the obstacle 90 based on the position of the host vehicle 20A, the position Po of the obstacle 90, and the avoidance area. Figure 7The vehicle control device 100 causes the host vehicle 20A to travel along the generated avoidance path ( Figure 7 Step S90).

[0134] Therefore, according to the present embodiment, when the obstacle 90 exists near the boundary line between the driving lane 51 of the host vehicle 20A and the lane adjacent to the driving lane 51, that is, the oncoming lane 52, the obstacle 90 can be avoided and the driving of the host vehicle 20A can be continued. As a result, compared with the technology of stopping the host vehicle 20A when the obstacle 90 exists near the boundary line, the productivity in the work site can be improved. In addition, when there is no possibility of contact with the oncoming vehicle 20B, the oncoming lane 52 can be used to perform the avoidance action. In this case, the avoidance action can be performed while suppressing the reduction of the driving speed, thereby suppressing the fuel consumption caused by re-acceleration.

[0135] (2) The vehicle control device 100 determines whether the host vehicle 20A can pass the obstacle 90 from the side without contacting the obstacle 90 based on the position Po of the obstacle 90, the lateral width Wo of the obstacle 90, and the avoidance area. Fig. 9 The vehicle control device 100 determines whether the host vehicle 20A can pass over the obstacle 90 without contact with the obstacle 90 based on the position Po of the obstacle 90, the lateral width Wo and height Ho of the obstacle 90, and the avoidance area ( Fig. 9 Step S175).

[0136] When the vehicle control device 100 determines that the host vehicle 20A cannot pass through the obstacle 90 from either the side or the top without contacting the obstacle 90, the host vehicle 20A stops in front of the obstacle 90 as viewed from the host vehicle 20A ( Fig. 9 When the vehicle control device 100 determines that the host vehicle 20A can pass the obstacle 90 from the side without contacting the obstacle 90, it generates a detour path passing from the side of the obstacle 90 as a candidate for an avoidance path ( Fig. 9 If the vehicle control device 100 determines that the host vehicle 20A can pass over the obstacle 90 without contacting the obstacle 90, it generates a crossing path over the obstacle 90 as a candidate for an avoidance path ( Fig. 9 In S175, it is yes, S177).

[0137] This configuration can realize an evasion action by using either the detour path or the crossing path as an evasion path. Therefore, according to this embodiment, the frequency of stopping the vehicle 20A can be reduced compared to a technique that generates only the detour path or only the crossing path as an evasion path. As a result, the productivity in the work site can be improved.

[0138] (3) When both the detour route and the bypass route are generated, the vehicle control device 100 calculates a first required time Tb, which is a time required for the host vehicle 20A to pass through the detour route, and a second required time Tc, which is a time required for the host vehicle 20A to pass through the bypass route. Fig. 9 Steps S171 and S179). When the first required time Tb for passing is shorter than the second required time Tc for passing, the vehicle control device 100 sets the detour route as the avoidance route ( Fig. 9 In step S183, the answer is No, S189). When the second required time Tc for passing is shorter than the first required time Tb for passing, the vehicle control device 100 sets the crossing path as the avoidance path ( Fig. 9 In step S183, the answer is yes, S185).

[0139] In this configuration, a plurality of avoidance paths that enable avoidance actions are generated, and a path with a short passing time is selected from among the plurality of avoidance paths. Therefore, the travel time of the host vehicle 20A, such as the transport time, is reduced, and productivity in the work site is improved.

[0140] (4) The vehicle control device 100 determines whether the driving priority of the host vehicle 20A is higher or lower than the driving priority of the other vehicle 20B. Figure 8 The vehicle control device 100 determines that the other vehicle 20B is located near the obstacle 90 after the predicted arrival time Ta has passed ( Figure 8 In the case where it is determined that the driving priority of the own vehicle 20A is lower than the driving priority of the other vehicle 20B ( Figure 8 In the case of S145 being No and S149 being No), the driving lane 51 is set as the avoidance area, and the oncoming lane 52 is not set as the avoidance area ( Figure 8 The vehicle control device 100 determines that the other vehicle 20B is located near the obstacle 90 after the predicted arrival time Ta has passed ( Figure 8 In the case where it is determined that the driving priority of the host vehicle 20A is higher than the driving priority of the other vehicle 20B ( Figure 8 If either of S145 and S149 is YES, both the driving lane 51 and the oncoming lane 52 are set as the avoidance area ( Figure 8S153).

[0141] According to this configuration, the avoidance area is set to be expanded under the condition that the fuel efficiency is greatly reduced due to the deceleration accompanying the avoidance action of the host vehicle 20A. This can suppress the deceleration accompanying the avoidance action of the host vehicle 20A, thereby suppressing the increase in operating costs and improving productivity.

[0142] (5) When the cargo load of the host vehicle 20A is greater than the cargo load of the oncoming vehicle (other vehicle) 20B, the vehicle control device 100 determines that the driving priority of the host vehicle 20A is higher than the driving priority of the oncoming vehicle 20B ( Figure 8 According to this configuration, it is possible to suppress an increase in fuel consumption caused by re-acceleration of the vehicle 20A in a loaded state. As a result, it is possible to improve productivity at the entire work site.

[0143] (6) The vehicle control device 100 obtains information on the slope of the driving lane 51 of the host vehicle 20A, and based on the obtained slope information, determines whether there is an uphill slope ( ) on the back side of the obstacle 90 as viewed from the host vehicle 20A and within the acceleration distance (predetermined distance) Da from the obstacle 90. Figure 8 When the vehicle control device 100 determines that there is an uphill slope, it determines that the driving priority of the host vehicle 20A is higher than the driving priority of the oncoming vehicle 20B ( Figure 8 According to this configuration, the vehicle 20A can suppress the increase in fuel consumption due to re-acceleration on an uphill slope. As a result, the productivity of the entire work site can be improved.

[0144] (7) When the vehicle control device 100 determines that the oncoming vehicle 20B is present in the vicinity of the obstacle 90 after the predicted arrival time Ta has passed, and determines that the driving priority of the host vehicle 20A is higher than the driving priority of the oncoming vehicle 20B, before the host vehicle 20A reaches the end point of the avoidance path, the vehicle control device 100 sends an intrusion prohibition instruction (control instruction) to the oncoming vehicle 20B to prohibit intrusion into the area on the side of the host vehicle 20A that is closer to the end point of the avoidance path. According to this configuration, the oncoming vehicle 20B can be decelerated or stopped while the host vehicle 20A is performing an avoidance action using the oncoming lane 52. As a result, the host vehicle 20A performing the avoidance action can be reliably prevented from contacting the oncoming vehicle 20B.

[0145] As described above, the vehicle control device 100 of the first embodiment calculates the avoidance area that the host vehicle 20A can use to avoid the obstacle 90 in consideration of the width of the travel lane 51, the width of the haul road 50, and the presence or absence of the oncoming vehicle 20B. As a result, an avoidance action that prevents the host vehicle 20A from escaping from the haul road 50 and contacting the oncoming vehicle 20B is achieved. In addition, the number of stops of the host vehicle 20A can be reduced, thereby improving the productivity of the work site.

[0146] <Second embodiment>

[0147] Reference Figure 12 to Figure 14 , an autonomous driving system according to a second embodiment of the present invention is described. In addition, the same reference numerals are given to the same or equivalent components as those described in the first embodiment, and the differences are mainly described. In the second embodiment, an example of generating an avoidance path in a control station 80 is described, and the control station 80 performs traffic control of a plurality of unmanned vehicles 20 and a plurality of mining machines 30 operating at a work site. The autonomous driving system according to the second embodiment includes a control server 200 of the control station 80.

[0148] Fig.12 1 is a schematic diagram showing a work site of an open-pit mine, and shows a control station 80 having an autonomous driving system according to a second embodiment. Fig.12 The control station 80 shown is located near the work site or at a location far from the work site. A control server 200 and a communication device 209 are provided in the control station 80. The control server 200 collects the operation information of one or more unmanned vehicles 20 and one or more mining machines 30 via the communication device 209 and the wireless communication line 40, and sends control signals to the multiple unmanned vehicles 20 based on the collected operation information. In this way, the control station 80 seeks to improve the productivity of the mine. In addition, in the figure, each mining machine 30 is represented as 30-1, 30-2...

[0149] Fig.13 It is a diagram showing the configuration of the unmanned vehicle 20 , the mining machine 30 , and the control station 80 . Fig.13 The control server 200 shown is similar to the vehicle control device 100 described in the first embodiment and is composed of a computer having a processing device, a volatile memory, a nonvolatile memory, an input / output interface, and other peripheral circuits. In addition, the communication device 209 has a communication interface capable of communicating with the wireless communication line 40.

[0150] The mining machine 30 has a machine control device 300, a wireless communication device 309, a storage device 308, a position sensor 303, and a speed sensor 305. The machine control device 300 is composed of a computer having a processing device, a volatile memory, a non-volatile memory, an input / output interface, and other peripheral circuits, similarly to the vehicle control device 100. In addition, the wireless communication device 309 has the same structure as the wireless communication device 109, and has a communication interface capable of communicating with the wireless communication line 40.

[0151] The control station 80, the unmanned vehicle 20, and the mining machine 30 exchange information with each other via the wireless communication line 40. The storage device of the control server 200 stores the same map information as the map information stored in the storage device 108B of each unmanned vehicle 20.

[0152] The storage device 108B of the unmanned vehicle 20 has an operation information storage unit 182. In the operation information storage unit 182, the time and the driving priority (operation priority) of the unmanned vehicle 20 are stored in association. The storage device 308 of the mining machine 30 has an operation information storage unit 382. In the operation information storage unit 382, ​​the time and the operation status of the mining machine 30 are stored in association. The operation information includes a "loading status" indicating that the mining machine 30 is performing a loading operation with respect to the unmanned vehicle 20, and a "standby status" indicating that the mining machine 30 is not performing a loading operation with respect to the unmanned vehicle 20.

[0153] The vehicle control device 100B of the unmanned vehicle 20 repeatedly calculates the travel priority according to a predetermined control cycle, and stores the calculated travel priority together with the time in the storage device 108B. The vehicle control device 100B calculates the travel priority α (α=α1+α2+α3+α4) by adding priority parameters α1, α2, α3, and α4 described below, for example.

[0154] The vehicle control device 100B determines whether each of the following (first condition) to (fourth condition) is satisfied, for example.

[0155] (First Condition) The loading state of the host vehicle 20A is an empty state, and the mining machine 30 operating at the end point (destination) of the travel route 11 in the empty state of the host vehicle 20A is in a standby state.

[0156] (Second Condition) The driving operation of the host vehicle 20A is operated by the operator (that is, the autonomous driving function is released and the host vehicle 20A is operating as a manned vehicle).

[0157] (Third Condition) The loading state of the host vehicle 20A is a loaded state.

[0158] (Fourth Condition) An uphill slope exists on the back side of the obstacle 90 viewed from the host vehicle 20A and within the acceleration distance Da from the obstacle 90 .

[0159] The vehicle control device 100B sets α10 (for example, 0) to the priority parameter α1 when (the first condition) is not satisfied, and sets α11 to the priority parameter α1 when (the first condition) is satisfied. α11 is greater than α10. The vehicle control device 100B sets α20 (for example, 0) to the priority parameter α2 when (the second condition) is not satisfied, and sets α21 to the priority parameter α2 when (the second condition) is satisfied. α21 is greater than α20. The vehicle control device 100B sets α30 (for example, 0) to the priority parameter α3 when (the third condition) is not satisfied, and sets α31 to the priority parameter α3 when (the third condition) is satisfied. α31 is greater than α30. The vehicle control device 100B sets α40 (for example, 0) to the priority parameter α4 when (the fourth condition) is not satisfied, and sets α41 to the priority parameter α4 when (the fourth condition) is satisfied. α41 is larger than α40. In addition, α11, α21, α31, and α41 may be the same value or different values.

[0160] The control server 200 has the same function as the avoidance route generation unit 112 of the vehicle control device 100 of the first embodiment. That is, the control server 200 can also be called an avoidance route generation device that generates an avoidance route.

[0161] When the vehicle control device 100 of the unmanned vehicle 20 detects the obstacle 90, it calculates the obstacle information and sends the calculation result to the control station 80 via the wireless communication line 40. The control server 200 determines the avoidance area based on the received obstacle information and the operation information of other unmanned vehicles 20 and mining machinery 30. The control server 200 generates an avoidance path according to the avoidance area, and sends the information of the generated avoidance path to the unmanned vehicle 20 that detects the obstacle 90 via the wireless communication line 40. Hereinafter, the unmanned vehicle 20 that will be the object of generating the avoidance path is also referred to as the object vehicle. The object vehicle is equivalent to the vehicle 20A in the first embodiment, and is therefore marked with the same figure mark. In addition, similarly to the first embodiment, the unmanned vehicle 20 that travels in the direction opposite to the travel direction of the object vehicle 20A is called the oncoming vehicle 20B.

[0162] Fig.14 is with Figure 8 The same figure is a flowchart showing an example of the flow of the avoidance area determination process executed by the control server 200 according to the second embodiment. Fig.14 In the flowchart, replace Figure 8 The processing of steps S143 to S149 of the flowchart is performed, and the processing of steps S142B and S146B is executed.

[0163] In step S142B, the control server 200 acquires the traveling priority αA of the target vehicle 20A and the traveling priority αB of the oncoming vehicle 20B, and proceeds with the process to step S146B.

[0164] In step S146B, the control server 200 determines whether the driving priority αB of the oncoming vehicle 20B is lower than the driving priority αA of the target vehicle 20A based on the driving priorities αA and αB of the target vehicle 20A and the oncoming vehicle 20B acquired in step S142B. In step S146B, if it is determined that the driving priority αB of the oncoming vehicle 20B is higher than the driving priority αA of the target vehicle 20A, the process proceeds to step S151. In this case, the target vehicle 20A is decelerated or stopped, and the oncoming vehicle 20B is given priority to travel. In step S146B, if it is determined that the driving priority αB of the oncoming vehicle 20B is lower than the driving priority αA of the target vehicle 20A, the process proceeds to step S153. In this case, the oncoming vehicle 20B is decelerated or stopped, and the target vehicle 20A is given priority to travel.

[0165] As described above, the vehicle control device 100B constituting the autonomous driving system of the second embodiment acquires information on the operating state of the mining machine 30 that loads the loading object to the host vehicle 20A. The vehicle control device 100B determines whether the loading state of the host vehicle 20A is an empty state or a loaded state. When the first condition is satisfied, including that the operating state of the mining machine 30 is in a standby state where no loading operation is performed and the loading state of the host vehicle 20A is an empty state, the vehicle control device 100B sets the driving priority of the host vehicle 20A to be higher (α1=α11>α10) than when the first condition is not satisfied.

[0166] When the mining machine 30 is in the loading state, the host vehicle 20A will temporarily wait even if it arrives at the loading site. On the other hand, when the mining machine 30 is in the waiting state, if the host vehicle 20A arrives at the loading site, the loading operation to the host vehicle 20A will be immediately started. Therefore, according to the above configuration, the time when the mining machine 30 is in the waiting state can be shortened, thereby improving the productivity of the entire work site.

[0167] The vehicle control device 100B determines whether the host vehicle 20A is a manned vehicle or an unmanned vehicle. The autonomous driving function can be set to be released (invalid) by a switch outside the unmanned vehicle 20 and in the cab of the unmanned vehicle 20. When the vehicle control device 100B determines that the host vehicle 20A is a manned vehicle, it sets the driving priority of the host vehicle 20A to be higher (α2=α21>α20) than when it determines that the host vehicle 20A is an unmanned vehicle.

[0168] This can reduce the chances of deceleration and stopping of the manned vehicle, thereby reducing the operational burden on the operator.

[0169] <Modification of the Second Embodiment>

[0170] In the second embodiment described above, an example in which the vehicle control device 100B of the unmanned vehicle 20 calculates the driving priority α is described. However, the driving priority α may be calculated by the control server 200. In this case, the control server 200 obtains the operation information of the unmanned vehicle 20 from each unmanned vehicle 20, and calculates the driving priority α based on the obtained operation information. The control server 200 determines whether the driving priority αA of the target vehicle 20A is higher or lower than the driving priority αB of the oncoming vehicle 20B based on the driving priority α obtained from each unmanned vehicle 20.

[0171] The modified examples described below also fall within the scope of the present invention, and it is also possible to combine the configuration shown in the modified examples with the configuration described in the above-mentioned embodiment, or to combine the configurations described in the above-mentioned different embodiments with each other, or to combine the configurations described in the following different modified examples with each other.

[0172] <Variation 1>

[0173] The configuration and order of the processing executed by the vehicle control device 100 and the control server 200 can be changed as appropriate. For example, Figure 8 The processing of steps S143 to S149 and Fig.14 Steps S142B and S146B may also be omitted. Figure 8 The processing of steps S143 to S145 may be omitted, or only the processing of steps S147 and S149 may be omitted.

[0174] <Variation 2>

[0175] In the second embodiment, an example of calculating the driving priority by adding priority parameters set based on whether the (first condition) to (fourth condition) are satisfied is described. However, the calculation method of the driving priority is not limited to this. The driving priority may also be calculated based on whether at least one of the (first condition) to (fourth condition) is satisfied.

[0176] As mentioned above, although the embodiment of the present invention was described, the above embodiment merely shows a part of application examples of the present invention, and it is not intended that the technical scope of the present invention is limited to the specific configuration of the above embodiment.

[0177] Description of Reference Numerals

[0178] 10…driving lane, 11…driving path, 12…node, 20…unmanned vehicle (transport vehicle, dump truck), 20A…own vehicle, target vehicle (unmanned vehicle), 20B…oncoming vehicle, other vehicle (unmanned vehicle), 21…vehicle body, 22…wheel, 30…mining machinery, 40…wireless communication line, 50…transport road, 51…driving lane, 51L, 51R…lane formation line, 52…oncoming lane, 52L, 52R…lane formation line, 80…control station, 90…obstacle, 91…rectangular block, 100, 100B…vehicle control device (control device), 101…external sensor, 103…position sensor, 104…direction sensor, 105…speed sensor, 106…operation Steering angle sensor, 107…travel drive device, 108, 108B…storage device, 109…wireless communication device, 111…obstacle information calculation unit, 112…avoidance path generation unit, 113…control target generation unit, 114…autonomous travel control unit, 181…map information storage unit, 182…operation information storage unit, 200…control server (control device), 209…communication device, 271…obstacle information calculation unit, 300…mechanical control device, 303…position sensor, 305…speed sensor, 308…storage device, 309…wireless communication device, 382…operation information storage unit, Ta…predicted arrival time, Tb…first passing time, Tc…second passing time.

Claims

1. An autonomous driving system having a control device for controlling a transport vehicle capable of autonomously driving along a driving path, wherein the autonomous driving system is characterized in that: The control device is configured as follows: When an obstacle is located in the driving lane of the transport vehicle, the estimated arrival time, which is the time required for the transport vehicle to reach the position of the obstacle, is calculated based on the position of the obstacle and the position and driving speed of the transport vehicle. Based on the positions and travel speeds of other vehicles existing around the transport vehicle and the predicted arrival time, the predicted positions of the other vehicles after the predicted arrival time has passed are calculated; determining whether the other vehicle is located near the obstacle after the predicted arrival time has elapsed based on the position of the obstacle and the predicted position of the other vehicle, When it is determined that the other vehicle is present near the obstacle after the predicted arrival time has elapsed, the driving lane is set as an avoidance area, and a lane adjacent to the driving lane is not set as an avoidance area, When it is determined that the other vehicle is no longer present near the obstacle after the predicted arrival time has elapsed, both the driving lane and a lane adjacent to the driving lane are set as avoidance areas, Based on the position of the transport vehicle, the position of the obstacle, and the avoidance area, an avoidance path is generated within the avoidance area as the travel path for the transport vehicle to avoid the obstacle.

2. The autonomous driving system according to claim 1, characterized in that: The control device is configured as follows: Based on the position of the obstacle, the lateral width of the obstacle, and the avoidance area, determining whether the transport vehicle can pass the obstacle from the side without contacting the obstacle, Based on the position of the obstacle, the lateral width and height of the obstacle, and the avoidance area, it is determined whether the transport vehicle can pass over the obstacle without contacting the obstacle. If it is determined that the transport vehicle cannot pass through the obstacle from either the side or the top of the obstacle without contacting the obstacle, the transport vehicle is stopped in front of the obstacle as viewed from the transport vehicle. If it is determined that the transport vehicle can pass the obstacle from the side without contacting the obstacle, a detour route passing the obstacle from the side is generated as a candidate for the avoidance route, When it is determined that the transport vehicle can pass over the obstacle without coming into contact with the obstacle, a crossing path that crosses the obstacle is generated as a candidate for the avoidance path.

3. The autonomous driving system according to claim 2, characterized in that: The control device is configured as follows: When both the detour route and the bypass route are generated, a first required time for the transport vehicle to pass through the detour route and a second required time for the transport vehicle to pass through the bypass route are calculated. When the first required time for passing is shorter than the second required time for passing, the detour route is set as the avoidance route, When the second required passage time is shorter than the first required passage time, the leaping path is set as the avoiding path.

4. The autonomous driving system according to claim 1, characterized in that: The control device is configured as follows: determining whether the driving priority of the transport vehicle is higher or lower than the driving priority of the other vehicles, When it is determined that the other vehicle is present near the obstacle after the predicted arrival time has passed and it is determined that the driving priority of the transport vehicle is lower than the driving priority of the other vehicle, the driving lane is set as an avoidance area, and a lane adjacent to the driving lane is not set as an avoidance area, When it is determined that the other vehicle is present near the obstacle after the predicted arrival time has passed and when it is determined that the travel priority of the transport vehicle is higher than that of the other vehicle, both the travel lane and a lane adjacent to the travel lane are set as avoidance areas.

5. The autonomous driving system according to claim 4, characterized in that: The control device determines that the travel priority of the transport vehicle is higher than the travel priority of the other vehicles when the cargo load of the transport vehicle is greater than the cargo load of the other vehicles.

6. The autonomous driving system according to claim 4, characterized in that: The control device is configured as follows: obtaining information on the slope of the driving lane of the transport vehicle, Based on the acquired information on the slope, it is determined whether there is an uphill slope on the back side of the obstacle as viewed from the transport vehicle and within a predetermined distance from the obstacle, When it is determined that the uphill gradient exists, it is determined that the travel priority of the transport vehicle is higher than the travel priority of the other vehicles.

7. The autonomous driving system according to claim 4, characterized in that: The control device is configured as follows: acquiring information on the operating status of a mining machine that loads a loading object onto the transport vehicle, Determine whether the cargo state of the transport vehicle is an empty state or a loaded state, When the conditions that the operation state of the mining machine is in the standby state without loading work and the loading state of the transport vehicle is in the empty state are satisfied, the travel priority of the transport vehicle is set higher than when the conditions are not satisfied.

8. The autonomous driving system according to claim 4, characterized in that: The control device is configured as follows: Determine whether the transport vehicle is a manned vehicle or an unmanned vehicle, When it is determined that the transport vehicle is a manned vehicle, the travel priority of the transport vehicle is set higher than when it is determined that the transport vehicle is an unmanned vehicle.

9. The autonomous driving system according to claim 4, characterized in that: When the control device determines that the other vehicle is present in the vicinity of the obstacle after the predicted arrival time has passed and determines that the driving priority of the transport vehicle is higher than the driving priority of the other vehicle, the control device sends a control instruction to the other vehicle prohibiting intrusion into an area closer to the transport vehicle than the end point of the avoidance path before the transport vehicle reaches the end point of the avoidance path.

10. The autonomous driving system according to claim 3, characterized in that: The control device is configured as follows: The higher the height of the obstacle, the smaller the target value of the travel speed of the transport vehicle in the crossing path. The larger the lateral width of the obstacle is, the smaller the target value of the travel speed of the transport vehicle in the crossing path is.

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