Route Guidance System

Abstract

To provide a route guidance system capable of realizing a safe route guidance by suppressing a collision of a vehicle and a deadlock in the same link, or the like.SOLUTION: A route guidance system sets a travel route of an automatic driving vehicle from a departure place 40 to a destination 41 with the use of a plurality of links L1, L2, L3, ..., and La1, La2, La3, ..., and nodes N1, N2, N3, ... where the links cross, so as to guide a plurality of automatic driving vehicles in accordance with a predetermined priority sequence. Then, dangerous spaces A1 and A2 and passage right are set with respect to the links which form a guidance route from the departure place to the destination. When the guidance routes of the automatic driving vehicles cross at the node, the automatic driving vehicle in the lower priority sequence is allowed to wait in the link before the crossing node on the guidance route of the vehicle. The guidance is restarted after the automatic driving vehicle in the higher priority sequence passes the node.SELECTED DRAWING: Figure 8

Description

[Technical field]

[0001] The present invention relates to a route guidance system that guides multiple autonomous vehicles according to priority in a limited space, such as a parking lot. [Background technology]

[0002] Patent Document 1 describes a route search method in which, when a route from a starting point to a destination is searched for and a route that includes a difficult-to-travel section is found, a predetermined penalty cost is added to the cost of the route, and the route candidate with the smallest total cost is selected. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2018-136198 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, the route search method described in Patent Document 1 only provides an autonomous vehicle with a route that avoids difficult-to-drive sections, and does not take safety into consideration. Therefore, in order to ensure safety, it is necessary to select a safe route in advance and then recalculate an optimal route, which is a problem in that the process is complicated and time-consuming.

[0005] The present invention has been made in consideration of the above-mentioned circumstances, and an object of the present invention is to provide a route guidance system that can realize safe route guidance by suppressing vehicle collisions and deadlocks on the same link. [Means for solving the problem]

[0006] A route guidance system according to one aspect of the present invention is a system that sets a guidance route for an autonomous vehicle with a plurality of links and a node where these links intersect, and when the guidance routes of a plurality of autonomous vehicles intersect at the node, sets a virtual traffic light on the link to this node, turns the virtual traffic light red for autonomous vehicles with low priority and has them wait at the link before the intersecting node, and turns the virtual traffic light green after autonomous vehicles with high priority have passed the node and are guided. restarting the traffic control system, and if the waiting time is longer than a predetermined time, stopping the vehicle with higher priority and allowing the waiting vehicle to pass; It is characterized by: Effect of the Invention

[0007] According to the route guidance system of the present invention, when the guidance routes of multiple autonomous vehicles intersect at a node, the autonomous vehicle with a lower priority is made to wait on the link just before the intersecting node on its guidance route, and guidance is resumed after the autonomous vehicle with a higher priority has passed this node, thereby preventing vehicle collisions and deadlocks on the same link, and achieving safe route guidance. [Brief description of the drawings]

[0008] [Figure 1] 1 is a schematic configuration diagram of a traffic control system to which a route guidance system according to an embodiment of the present invention is applied; [Diagram 2] FIG. 2 is a schematic configuration diagram of the autonomous driving vehicle in FIG. [Diagram 3] FIG. 2 is a schematic diagram of a monitoring device installed at an intersection for explaining the monitoring device in FIG. 1. [Figure 4] FIG. 2 is a schematic diagram of a monitoring device installed at a boarding / alighting port for explaining the monitoring device in FIG. 1. [Diagram 5] FIG. 2 is a schematic diagram of the monitoring device in FIG. 1, which is installed in a garage or parking lot. [Figure 6] 4 is a block diagram showing an example of the configuration of the monitoring device shown in FIG. 3. [Figure 7] 5 is a block diagram showing an example of the configuration of the monitoring device shown in FIG. 4. [Figure 8]6 is a block diagram showing an example of the configuration of the monitoring device shown in FIG. 5. [Figure 9] FIG. 2 is a schematic diagram for explaining generation of a guide route in the route guidance system according to the embodiment of the present invention. [Figure 10] 3 is a flowchart showing a route guidance method in the route guidance system according to the embodiment of the present invention. [Figure 11] 11 is a flowchart illustrating the route guidance method following FIG. 10. [Figure 12] 12 is a flowchart illustrating the route guidance method following FIG. 11. [Figure 13] This is a schematic diagram of a parking lot drawn from node and link information. [Figure 14] FIG. 2 is a schematic diagram of an initial state of route guidance. [Figure 15] FIG. 15 is a schematic diagram for explaining route generation for a vehicle with the highest priority in FIG. 14. [Figure 16] FIG. 16 is a schematic diagram for explaining a virtual signal corresponding to FIG. 15. [Figure 17] FIG. 15 is a schematic diagram for explaining a state in which the vehicle with the second highest priority in FIG. 14 has arrived at an intermediate node. [Figure 18] FIG. 18 is a schematic diagram for explaining a virtual signal corresponding to FIG. 17. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. 1 shows a schematic configuration of a traffic control system to which a route guidance system according to an embodiment of the present invention is applied. In this traffic control system, various systems (servers) are provided on a cloud 1, and a control room 2 for a bus or taxi company, a user's information terminal (smartphone, tablet, personal computer, etc.) 3, an autonomous vehicle 4, and a field monitoring device (infrastructure) 5 are interconnected with the servers of the various systems on the cloud 1 via an Internet line, a mobile line provided by a communication carrier such as a mobile phone carrier, or a dedicated wireless communication line. In addition, the autonomous vehicle 4 and the monitoring device 5 are interconnected without going through the various systems on the cloud 1.

[0010] Servers such as a traffic management system, a centralized control system, an infrastructure management system, a web server, a timetable management system, and a remote control system are provided on the cloud 1. The route guidance system performs route guidance for an autonomous vehicle 4 using the server of the traffic management system and the server of the centralized control system on the cloud 1.

[0011] In the control room 2, a supervisor monitors the operation status of the autonomous vehicles 4 (usually multiple vehicles) while looking at the operation management monitor, and switches to remote control if an abnormality occurs. The operation management monitor receives various information for remote monitoring and remote control from servers on the cloud 1, such as the operation management system, centralized control system, infrastructure management system, timetable management system, and remote control system. For example, the operation management monitor displays route information, vehicle position, driving status, road information, images of the vehicle's surroundings, and images inside the vehicle.

[0012] According to the information displayed on these operation management monitors, when the monitored autonomous vehicle 4 (for example, a bus or taxi) is about to enter a dangerous state, the monitor uses a remote control system to control the vehicle to avoid the danger. In addition, intersections, boarding and alighting ports, garages, parking lots, etc. are also monitored using images from the monitoring device 5.

[0013] Meanwhile, a user can use the information terminal 3 to send registration information and reservation information to a web server on the cloud 1, thereby making it possible to make reservations for taxi dispatch, bus rides, automatic parking in a parking lot, and automatic leaving from a parking lot. The web server stores the user's registration information, and a reservation is possible if it matches the registration information entered from the information terminal 3. For example, a user selects "Make a reservation" from the top screen of the information terminal 3, and enters "Dispatch to a specific location," "Boarding and alighting port," "Automatic parking," "Automatic leaving," "Terms of use," and the like on the next screen to confirm the reservation. The user may select this information from the location, time, and conditions displayed on the information terminal 3.

[0014] An autonomous vehicle 4 receives map information, route information, and departure (stop) information from the server of the traffic management system and the server of the centralized control system on the cloud 1, and transmits its own vehicle position information and vehicle state information. As shown in Fig. 2, the autonomous vehicle 4 includes various actuators 11 used for steering and engine control, an ECU (Electronic Control Unit) 12 that controls these actuators 11 and various devices, an in-vehicle traffic command device (AIPC + communication unit) 13, a LiDAR (light detection and ranging) 14, and the like.

[0015] In addition, magnetic markers 16, 16, ... are buried in the road surface 15 of the travel path of the autonomous vehicle 4, and these magnetic markers 16, 16, ... are detected by a magnetic sensor not shown in the figure to calculate the absolute position of the autonomous vehicle 4 and control the steering.

[0016] The LiDAR 14 measures the distance and direction to an object by emitting laser light and measuring the time it takes for the light to bounce back after hitting the object. By using the LiDAR 14, the positions of vehicles and pedestrians traveling around the autonomous vehicle 4 and their movements can be grasped in three dimensions. In addition, the LiDAR 14 is configured to perform self-location estimation of the autonomous vehicle 4 by scan matching with point cloud information of a high-precision three-dimensional map (not shown) and control steering.

[0017] Furthermore, the ECU 12 receives positioning information from a Global Navigation Satellite System (GNSS) system 17, recognizes the vehicle's position, and inputs the position information to a server of the operation control system on the cloud 1 via an Internet line, a mobile line provided by a communication carrier such as a mobile phone carrier, or a dedicated wireless communication line. Various types of vehicle status information obtained from the ECU 12 are also input to the server of the operation control system on the cloud 1.

[0018] 3 to 5 are each intended to explain the monitoring device 5 in FIG. 1, and show a schematic configuration by extracting the main parts, with FIG. 3 being installed at an intersection, FIG. 4 at a boarding / alighting port, and FIG. 5 at a garage or parking lot. As shown in FIG. 3, a camera 22a is built into a signal lamp 21 at an intersection. An image taken by this camera 22a within or near the intersection is read into an image processing device 23a and processed to detect moving objects such as vehicles, bicycles, and pedestrians. The processing result (moving object information) of the image processing device 23a is input to a control module 24a.

[0019] The control module 24a receives signal information from a traffic signal controller (not shown) and moving object information from the camera 22a. The control module 24a detects the movement vectors of moving objects such as vehicles, bicycles, and pedestrians based on the moving object information from the camera 22a, and transmits roadside information SA5 (including signal information SA1 and danger information) that predicts the future positions of these moving objects to the server of the traffic management system.

[0020] 4, a camera 22b is provided at the boarding / alighting port, and the captured image of the boarding / alighting port is read into an image processing device 23b for image processing, and buses and taxis (autonomous vehicles 4) parked at the boarding / alighting port and passengers are detected. The processing results of the image processing device 23b are input to a control module 24b, and the presence or absence of buses and taxis at the boarding / alighting port and passengers is transmitted to the server of the traffic management system as port information SA7.

[0021] Furthermore, as shown in Fig. 5, a camera 22c is provided in the garage / parking lot. This camera 22c photographs the garage, parking lot, and aisles between the parking spaces, and the photographed images of the garage, parking lot, and aisles are read into an image processing device 23c for image processing, and vehicles and obstacles in the aisles, users of the parking lot, etc. are detected. The processing results of the image processing device 23c are input to a control module 24c, and information on vehicles and obstacles in the aisles, the presence or absence of users in the parking lot, and vacancy information of the garage / parking lot are transmitted to the server of the operation management system as parking information SA8.

[0022] Then, the monitoring device 5 transmits the moving object information and danger information extracted from the movement vector, as well as signal information from the traffic signal controller, to buses and taxis (autonomous vehicles 4), and the autonomous vehicles 4 transmit future route information to the monitoring device 5.

[0023] Fig. 6 shows a specific example of the configuration of the monitoring device 5 shown in Fig. 3. In this example, the monitoring device 5 is connected to a base station 30 via a mobile line provided by a telecommunications carrier, and transmits and receives information from the base station 30 to and from various servers on the cloud 1. Similarly, the autonomous vehicles 4-1, 4-2, and 4-3 are also connected to the base station 30 via a mobile line, and transmits and receives information from and to various servers on the cloud 1.

[0024] The housing 31 of the monitoring device 5 contains a control module 24a, a traffic signal controller 33, a hub 34, and a mobile router 35. The control module 24a receives signal information SA1 from the traffic signal controller 33, environmental information SA3 such as weather conditions and road surface conditions from an environmental sensor 36, and positioning information SA6 from the GNSS system 17. In this example, two cameras 22a-1 and 22a-2 are provided, and the image processing device 23a is composed of image processing units 23a-1 and 23a-2 corresponding to these cameras. An image of the intersection or the vicinity of the intersection captured by the camera 22a-1 is processed by the image processing unit 23a-1, and moving object information SA2a such as vehicles and pedestrians is input to the control module 24a via the hubs 38 and 34.

[0025] Similarly, an image captured by camera 22a-2 is processed by image processor 23a-2, and moving object information SA2b of vehicles, pedestrians, etc. is input to control module 24a via hubs 38, 34. Then, control module 24a calculates a movement vector of the moving object, such as a vehicle or pedestrian, and calculates danger information based on this movement vector and the current and future positions of the host vehicle.

[0026] The control module 24a calculates roadside information SA5 (hazard information, etc.) from the traffic light information SA1, environmental information SA3, positioning information SA6, and mobile object information SA2a, SA2b, etc. This roadside information SA5 and traffic light information SA1 are transmitted from the control module 24a to the base station 30 via the hub 34, mobile router 35, LTE antenna 39, and mobile line, and then transmitted from the base station 30 to the autonomous vehicle 4-1 of the corresponding identification information. In addition, this roadside information SA5 and traffic light information SA1 are transmitted from the control module 24a via the hub 34, the mobile router 35, the LTE antenna 39, and the mobile line to the base station 30, and then transmitted from this base station 30 to a server on the cloud 1.

[0027] Meanwhile, future route information SA4 from the autonomous vehicles 4-1, 4-2, and 4-3 is transmitted to the base station 30 using a mobile line provided by a telecommunications carrier, and is input from this base station 30 to the control module 24a via the LTE antenna 39, the mobile router 35, and the hub 34.

[0028] Fig. 7 shows a specific example of the configuration of the monitoring device 5 shown in Fig. 4. The housing 31 of the monitoring device 5 contains a control module 24b, a hub 34, and a mobile router 35. The control module 24b receives environmental information SA3 from an environmental sensor 36 and positioning information SA6 from the GNSS system 17.

[0029] Furthermore, an image of the boarding / alighting port taken by the camera 22b-1 is processed by the image processor 23b-1, and boarding / alighting port information SA2c is input to the control module 24b via the hubs 38 and 34. Similarly, an image taken by the camera 22b-2 is processed by the image processor 23b-2, and boarding / alighting port information SA2d is input to the control module 24b via the hubs 38 and 34.

[0030] Meanwhile, port information SA7, such as whether there is a bus or taxi at the boarding / alighting port and whether there are passengers getting on and off, is transmitted from control module 24b via hub 34, mobile router 35, LTE antenna 39, and mobile line to base station 30, and then transmitted from base station 30 to autonomous vehicle 4-1 of the corresponding identification information. Also, this port information SA7 is transmitted from control module 24b via hub 34, mobile router 35, LTE antenna 39, and mobile line to base station 30, and then transmitted from base station 30 to a server on cloud 1.

[0031] Fig. 8 shows a specific example of the configuration of the monitoring device 5 shown in Fig. 5. The basic configuration is the same as that in Fig. 7, so the same parts are given the same reference numerals and detailed description thereof will be omitted. That is, a control module 24c, a hub 34, and a mobile router 35 are housed in a housing 31 of the monitoring device 5. Environmental information SA3 from an environmental sensor 36 and positioning information SA6 from a GNSS system 17 are input to the control module 24c.

[0032] Furthermore, images captured by camera 22c-1 are processed by image processor 23c-1, and information SA2e about the garage and parking lot is input to control module 24c via hubs 38 and 34. Similarly, images captured by camera 22c-2 are processed by image processor 23c-2, and information SA2f about the garage and parking lot is input to control module 24c via hubs 38 and 34.

[0033] Meanwhile, parking information SA8 indicating vacant spaces such as garages and parking lots is transmitted from the control module 24c to the base station 30 via the hub 34, mobile router 35, LTE antenna 39, and mobile line, and then transmitted from this base station 30 to the autonomous vehicle 4-1 of the corresponding identification information. Also, this parking information SA8 is transmitted from the control module 24c to the base station 30 via the hub 34, mobile router 35, LTE antenna 39, and mobile line, and then transmitted from this base station 30 to a server on the cloud 1.

[0034] [Embodiment] Next, a detailed description will be given of the case where route guidance and automated parking (AVP: Automated Valet Parking) for autonomous vehicles 4 (4-1, 4-2, 4-3, ...) are performed using the traffic management system and the server of the centralized control system on the cloud 1 described above. Fig. 9 is a schematic diagram for explaining generation of a guided route in a route guidance system according to an embodiment of the present invention. A guided route for an autonomous vehicle 4 between a starting point 40 and a destination 41 in Fig. 9 is set by a plurality of links and nodes where these links intersect.

[0035] Here, the routes L1, L2, L3, ..., La1, La2, La3, ..., Lb1, Lb2, Lb3, ..., Lc1, Lc2, Lc3, ..., Ld1, Ld2, Ld3, ..., Le1, Le2, Le3, ... are called links, and the intersections N1, N2, N3, ... of the routes are called nodes. Links correspond to, for example, aisles between parking spaces in a parking lot, and the points where these aisles intersect correspond to nodes.

[0036] This route guidance system guides multiple autonomous vehicles in a limited space such as a parking lot according to priority without overlapping, for example, automatically parking the vehicles in the parking lot, and automatically guiding the vehicles to the parking lot exit. When the guidance routes of multiple autonomous vehicles intersect at a specific node, the autonomous vehicles with lower priority wait at the link before the intersection, and resume guidance after the autonomous vehicles with higher priority have passed the specific node.

[0037] Generating a guided route requires the recognition of dangerous spaces and the generation of safe timing, and the system obtains the position and obstacle information of the autonomous vehicle 4 from the garage / parking lot monitoring device 5 shown in Figures 5 and 8, generates a driving route and safe timing, and guides the autonomous vehicle 4 to an empty parking space. In the event of a dangerous event such as an accident or obstacle, links surrounded by nodes that can be detoured are recognized (defined) as dangerous spaces A1 and A2, and are excluded from the route selection.

[0038] In FIG. 9, for example, link L4 (danger space A1) between nodes N4 and N7 where an accident has occurred and link Ld2 (danger space A2) between nodes N10 and N11 where an obstacle is present are excluded from the route selection.

[0039] The safety timing is generated as follows: At points where the guided routes of multiple autonomous vehicles intersect, arbitration based on time differences can lead to communication delays and time discrepancies, which can result in differences from the calculated results and a risk of collision. Therefore, a virtual right of way is given to the side with priority on the route (the opposite side stops), and a state is created in which the vehicles will never cross paths, providing guidance.

[0040] In this way, danger spaces and rights of way (stopping areas) are set in the passages between parking spaces in a parking lot, and autonomous vehicles are guided from the entrance of the parking lot to a parking space according to a preset priority, or multiple autonomous vehicles parked in a parking space are guided to the exit of the parking lot via the passages between the parking spaces according to a preset priority. If the guidance route of an autonomous vehicle guiding from the entrance of the parking lot to a parking space and the guidance route of an autonomous vehicle guiding from a parking space to the exit of the parking lot intersect, the autonomous vehicle guiding to the exit of the parking lot is given priority.

[0041] As described above, by setting danger spaces and rights of way (stopping areas) for links that form the guided route from the starting point to the destination, vehicle collisions and deadlocks on the same link can be prevented, thereby realizing safe route guidance.

[0042] 10 to 12 are flowcharts showing the operation of the route guidance system as described above. Information on links and nodes corresponding to aisles in a parking lot is read into the server of the operation management system on the cloud 1 from parking lot map data generated by the parking lot drawing system. The parking lot drawing system draws a parking lot from node and link information, as shown in Fig. 13, for example. The aisles between parking spaces in a parking lot correspond to links, and the intersections of the aisles correspond to nodes N0 to N12, respectively.

[0043] FIG. 14 shows the initial state of route guidance, where autonomous vehicle A is parked at node N0, autonomous vehicle B is parked at node N4, and autonomous vehicle C is parked at node N1. From this initial state, the traffic management system determines the priority order of the autonomously driven vehicles A, B, and C, for example, in the order of "A>B>C" (step S1). With the priority order thus determined, the route guidance system starts route guidance. First, the optimal driving route (path) for each vehicle is calculated in the order of priority "A>B>C" (step S2). From the result of this optimal path calculation, information on which vehicle will pass through each node is calculated, and this information is stored in order.

[0044] Here, autonomous vehicle A moves from node N0, passing through nodes N2, N6, N10, and N12 as shown by solid lines, and automatically parks in the parking space beyond node N12. Furthermore, autonomous vehicle B moves from node N4, passing through nodes N5, N6, N7, and N8 as shown by dotted lines, and automatically parks in the parking space beyond node N8. This is an example in which autonomous vehicle C moves from node N1, passing through nodes N2, N6, N10, and N11 as shown by dashed lines, and automatically parks in the parking space beyond node N11.

[0045] Only the first vehicle in the proprietary information can enter each node, and when the entered vehicle moves past it, it is removed from the proprietary information and the next vehicle can enter. This proprietary information of a node is similar to the concept of track blocking used in railway signaling.

[0046] Next, it is determined whether there are any obstacles on the travel route (step S3). If it is determined that there are no obstacles, node exclusive information after the optimum route calculation based on the travel route is created (step S4), and if it is determined that there are obstacles, the process returns to step S2, where links surrounded by nodes that can be detoured are recognized (defined) as dangerous spaces, and are excluded from the route selection, and another travel route is calculated.

[0047] In the next step S5, a preferred route is generated for vehicle A. Vehicle A has the highest priority and can enter all of nodes N0, N2, N6, N10, and N12, so it generates a detailed route from node N0, which is the starting point, to node N12, which is the destination, and notifies vehicle A of this. Next, the right of way is given to vehicle A at all nodes on the priority route of vehicle A (step S6), which causes vehicle A to start automatic traveling according to the priority route instruction (step S7).

[0048] In the next step S8, it is determined whether a node that intersects with the travel route of vehicle A has been extracted, and if so, vehicle A is guided to a node (before the intersecting node) where other vehicles B and C do not intersect with vehicle A (step S9). In this example, as shown in Fig. 15 with passing vehicles superimposed on each node, there are intersections at nodes N2, N6, and N10, where vehicle A and vehicle C intersect at node N2, vehicle A, vehicle B, and vehicle C at node N6, and vehicle A and vehicle C at node N10.

[0049] 16, the virtual traffic light for the link from node N0 to node N2 is set to a green light, the virtual traffic light for the link from node N2 to node N6 is set to a green light, and the virtual traffic light for the link from node N6 to node N10 is set to a green light. In addition, the virtual traffic light for the link from node N6 to node N2, the virtual traffic light for the link from node N10 to node N6, and the virtual traffic light for the link from node N12 to node N10 are also set to a green light.

[0050] On the other hand, the virtual traffic light for the link from node N1 to node N2 is set to a red light, the virtual traffic light for the link from node N3 to node N2 is set to a red light, the virtual traffic light for the link from node N5 to node N6 is set to a red light, the virtual traffic light for the link from node N7 to node N6 is set to a red light, the virtual traffic light for the link from node N9 to node N10 is set to a red light, and the virtual traffic light for the link from node N11 to node N10 is set to a red light.

[0051] In Figure 16, a green virtual traffic light is represented by a white circle on the driving route, and a red virtual traffic light is represented by a circle with a cross inside. Virtual traffic lights do not actually exist, but control arbitration between autonomous vehicles. This virtual traffic light ensures safe timing by granting right of way only to the vehicle with the highest priority. The virtual traffic light is controlled by the route generation system. In this state, vehicle B is guided to node N5, and vehicle C is made to wait at node N1 (step S10). On the other hand, if no node intersecting with vehicle A is extracted in step S8, the process proceeds to step S15.

[0052] In the virtual traffic light settings described above, the traffic light set for a node with node exclusive information will be set to red for all directions. Also, even if there is no node exclusive information, if a connected node has exclusive information, the traffic light including traffic to and from that node will be set to red. Furthermore, if the light color differs depending on the direction of travel but the traffic light does not have a turn indicator and cannot be set, the light will be set to red. If there is no traffic light linked to the node, nothing in particular will be done.

[0053] In the next step S11, it is determined whether vehicle A has passed node N2. If vehicle A has passed node N2, vehicle B is made to wait at node N5 (step S12). If vehicle A has not passed node N2, the process returns to step S10 to guide vehicle B to node N5 and maintain vehicle C in a waiting state at node N1. In the next step S13, it is determined whether vehicle A has passed node N6, and if so, vehicle A passes node N12 (destination) and arrives at a vacant parking space (step S14). If not, the process returns to step S12 and vehicle B maintains a standby state at node N5.

[0054] In the next step S15, it is determined whether a node that intersects with the travel route of vehicle B has been extracted, and if so, vehicle C is guided to a node (before the intersecting node) where vehicle B does not intersect (step S16). In this example, vehicle B is guided to node N6, and vehicle C waits at node N2 (step S17). On the other hand, if no node intersecting with vehicle B is extracted in step S15, the process proceeds to step S20.

[0055] In the next step S18, it is determined whether vehicle B has passed node N6. If vehicle B has passed node N6, it passes node N8 (destination) and arrives at an available parking space (step S19). If vehicle B has not passed node N8, it returns to step S17 and vehicle C remains waiting at node N2. In the next step S20, it is determined whether or not a node that intersects with vehicle C is extracted, and in either case, vehicle C travels from node N6 through node N10, passes through node N11 (destination), and arrives at a vacant parking space, as shown in Figure 17. At this point, the setting of the virtual traffic light at node N2 is released, as shown in Figure 18, and vehicle C can travel in all directions.

[0056] According to the route guidance system configured as described above, by setting danger spaces and rights of way (stopping areas) for the links that form the guided route from the starting point to the destination, vehicle collisions and deadlocks on the same link can be prevented, thereby realizing safe and comfortable route guidance.

[0057] The circuit configurations and operation procedures described in the above embodiments are merely schematic illustrations to enable the present invention to be understood and implemented. Therefore, the present invention is not limited to the described embodiments, and may be modified in various forms without departing from the scope of the technical ideas set forth in the claims.

[0058] For example, we have used a parking lot as an example, but by setting up virtual traffic lights at intersections in limited areas where there are no traffic lights, it is possible to provide route guidance for self-driving vehicles. In addition, although the example has been given of guiding the route of multiple self-driving vehicles, the invention can also be applied to general vehicles other than self-driving vehicles, and similar route guidance can be performed by using virtual traffic lights to give instructions to the driver to start, drive, stop, turn right, turn left, etc.

[0059] Furthermore, if the time spent waiting for a vehicle with a higher priority to pass is longer than a specified time, it may be determined that an abnormality or malfunction has occurred, and the vehicle with the higher priority may be stopped and the waiting vehicle may be allowed to pass. By configuring in this way, deadlock can be effectively prevented. [Explanation of symbols]

[0060] 1...cloud, 2...control room, 3...information terminal, 4, 4-1, 4-2, 4-3...autonomous vehicle, 5...monitoring device, 11...actuator, 12...ECU, 13...vehicle operation command device, 14...LiDAR, 15...road surface, 16...magnetic marker, 17...GNSS system, 21...signal lamp, 22a, 22b, 22c, 22a-1, 22a-2, 22b-1, 22b-2, 22c-1, 22c-2...camera, 23a, 23b, 23c...image processing device, 23a-1, 23a-2, 23b-1, 23b-2, 23c-1, 23c-2...image processing unit, 24a, 24b, 24c...control module, 30...base Base station, 31...housing, 33...traffic signal controller, 34, 38...hub, 35...mobile router, 36...environmental sensor, 39...LTE antenna, 40...starting point, 41...destination, L1, L2, L3, La1, La2, La3, Lb1, Lb2, Lb3, Lc1, Lc2, Lc3, Ld1, Ld2, Ld3...links, N1, N2, N3...nodes, A1, A2...hazardous space, SA1...signal information, SA2a, SA2b...mobile object information, SA2c, SA2d...boarding and alighting port information, SA3...environmental information, SA4...future route information, SA5...roadside information, SA6...positioning information, SA7...port information, SA8...parking information

Claims

1. A system for setting a guidance route for an autonomous vehicle using a plurality of links and nodes at which these links intersect, When the guidance routes of multiple autonomous vehicles intersect at the node, a virtual traffic light is set on the link to this node, and the virtual traffic light is turned red for autonomous vehicles with low priority and made to wait on the link before the intersecting node, and after autonomous vehicles with high priority have passed the node, the virtual traffic light is turned green and guidance is resumed; A route guidance system that stops vehicles with higher priority and allows waiting vehicles to pass if the waiting time is longer than a predetermined time.

2. 2. The route guidance system according to claim 1, wherein, in the event of a hazardous event, a link surrounded by detourable nodes is removed from the guidance route of the plurality of autonomous vehicles.

3. 3. The route guidance system according to claim 2, wherein the dangerous incident is an obstacle on the guided route.

4. 4. The route guidance system according to claim 1, wherein the guided route is an aisle between parking spaces in a parking lot, and guides a plurality of self-driving vehicles from an entrance of the parking lot to the parking spaces according to a preset priority order.

5. 4. The route guidance system according to claim 1, wherein the guided route is an aisle between parking spaces in a parking lot, and guides multiple self-driving vehicles parked in the parking spaces to an exit of the parking lot according to a preset priority order.

6. The route guidance system according to any one of claims 1 to 3, characterized in that the guidance route is an aisle between parking spaces in a parking lot, and in the event that a guidance route for an autonomous vehicle guiding from an entrance of the parking lot to a parking space and a guidance route for an autonomous vehicle guiding from a parking space to an exit of the parking lot intersect, priority is given to the autonomous vehicle guiding to the exit of the parking lot.

Images