Autonomous travel assistance device

Abstract

The autonomous driving assistance device includes a server unit. The server unit receives road condition information from roadside equipment. In the server unit, map information is stored as a combination of multiple nodes and multiple links. The server unit maintains the path information of the target vehicle. The server unit receives vehicle information related to the target vehicle's location and driving status, and based on the vehicle information and path information, selects a subset of nodes as selected nodes and a subset of links as selected links. The server unit appends the road condition information related to the selected nodes and links to the map information to obtain dynamic map information, which is then sent to the target vehicle autonomously driving along the predetermined driving path.

Description

Technical Field

[0001] This disclosure relates to autonomous driving assistance devices. Background Technology

[0002] In existing methods for installing dynamic objects in digital maps of autonomous vehicles, the digital map is distributed to the autonomous vehicle for driving assistance. The digital map is map data with dynamic road information overlaid on it. This dynamic road information includes, for example, information related to other vehicles on the driving path, road signal information, and congestion information (e.g., see Patent Document 1).

[0003] Existing technical documents

[0004] Patent documents

[0005] Patent Document 1: US Patent No. 10605612 Summary of the Invention

[0006] The technical problem that the invention aims to solve

[0007] In the existing methods described above, the dynamic road information contains insufficient information, which may make it difficult to provide appropriate driving assistance.

[0008] This disclosure was made to solve the problems mentioned above, and its purpose is to provide an autonomous driving assistance device that can more appropriately assist the autonomous driving of a vehicle.

[0009] Technical means for solving technical problems

[0010] The autonomous driving assistance device disclosed herein includes a server device. The server device receives road condition information (related to the conditions around the roadside equipment) from the roadside equipment and sends dynamic map information (related to the road condition information) to the target vehicle autonomously driving along a predetermined driving path. In the server device, the map information is stored as a combination of multiple nodes and multiple links. Each node corresponds to an intersection, and each link corresponds to a road connecting two adjacent intersections. The server device maintains path information (related to the driving path) and receives vehicle information (related to the vehicle's position and driving status) from the target vehicle. Based on the vehicle information and path information, the server device selects a subset of nodes from the multiple nodes and selects a subset of links from the multiple links. The server device sends dynamic map information (related to the road condition information related to the selected nodes and links) to the target vehicle.

[0011] Invention Effects

[0012] The autonomous driving assistance device disclosed herein enables more appropriate autonomous driving assistance for vehicles. Attached Figure Description

[0013] Figure 1 This is a block diagram representing the autonomous driving assistance device, server device, roadside equipment, and vehicle involved in Implementation Method 1.

[0014] Figure 2 It indicates applicability. Figure 1 A diagram showing the situation at intersections where autonomous driving assistance devices are installed.

[0015] Figure 3 It means Figure 1 A flowchart of the autonomous driving assistance control program executed by the control unit of the autonomous driving assistance device.

[0016] Figure 4 This is a diagram used to illustrate the arrival cost in the autonomous driving assistance device according to Embodiment 2.

[0017] Figure 5 This is a diagram used to illustrate the arrival cost in the autonomous driving assistance device according to Embodiment 2.

[0018] Figure 6 This is a flowchart illustrating the autonomous driving assistance control program executed by the control unit of the autonomous driving assistance device according to Embodiment 2.

[0019] Figure 7 This is a diagram illustrating an example of the control of the autonomous driving assistance device according to Embodiment 3.

[0020] Figure 8 This is a diagram illustrating an example of the control of the autonomous driving assistance device according to Embodiment 3.

[0021] Figure 9 This is a structural diagram of a first example of a processing circuit that implements the functions of the autonomous driving assistance device in embodiments 1 to 3.

[0022] Figure 10 This is a structural diagram of a first example of a processing circuit that implements the functions of the autonomous driving assistance device in embodiments 1 to 3. Detailed Implementation

[0023] Hereinafter, the embodiments will be described with reference to the accompanying drawings.

[0024] Implementation method 1.

[0025] Figure 1This is a block diagram representing the autonomous driving assistance device, server device, roadside equipment, and vehicle involved in Implementation Method 1.

[0026] The autonomous driving assistance device 10 includes a server device 20. The server device 20 includes, as a functional block, a communication unit 21, a road condition information acquisition unit 22, a vehicle information acquisition unit 23, a control unit 24, a dynamic map transmission unit 25, and a storage unit 26.

[0027] As a server device 20, for example, a server configured within the core network of a mobile phone network known as MEC (Multi-Access Edge Computing) can be used. Alternatively, the server device 20 can also utilize a dedicated network built within a limited area, similar to that used in a factory. For example, it can connect to a network capable of connecting to a 5G network only within a limited foundation area.

[0028] The communication unit 21 receives road condition information from the roadside device 30. This road condition information is detected by the sensors 33 of the roadside device 30 and is related to the surrounding conditions of the roadside device 30. Examples of information related to the surrounding conditions of the roadside device 30 include information related to moving vehicles, parked vehicles, pedestrians, obstacles, and road surface conditions.

[0029] Sensor 33 can include, for example, a camera, millimeter-wave radar, and LiDAR (Light Detection and Range). Furthermore, communication between the server device 20 and the roadside device 30 uses wireless or wired communication. For wired communication, fiber optic cables, LAN cables, etc., are used.

[0030] The communication unit 21 receives vehicle information from the vehicle 40, which is the target vehicle. The target vehicle refers to a vehicle that autonomously travels along a predetermined driving path and is the vehicle that serves as the object of autonomous driving assistance. The vehicle information includes information related to the position of the vehicle 40 and information related to the driving status of the vehicle 40. The information related to the driving status of the vehicle 40 includes the speed of the vehicle 40, the acceleration of the vehicle 40, the driving history of the vehicle 40, the direction indicator information of the vehicle 40, and at least a portion of the predetermined driving path of the vehicle 40.

[0031] The communication unit 41 of vehicle 40 includes a communicator and an antenna capable of wireless communication. Wireless communication utilizes C-V2X (Cellular V2X) technologies such as LTE (Long Term Evolution) and 5G. Additionally, wireless communication utilizing OTA (Over-The-Air) or Wi-Fi-based wireless communication is sometimes used. The communication unit 41 transmits vehicle information and route information to the server device 20 at regular intervals.

[0032] The road condition information acquisition unit 22 acquires road condition information from the roadside equipment 30 via the communication unit 21.

[0033] The vehicle information acquisition unit 23 acquires vehicle information from the vehicle 40 via the communication unit 21.

[0034] In storage unit 26, map information is stored as a combination of multiple nodes and multiple links. Each node corresponds to an intersection. Each link corresponds to a road connecting two adjacent intersections. Intersections include three-way intersections, crossroads, five-way intersections, roundabouts, etc.

[0035] Storage unit 26 maintains the path information of vehicle 40. Path information is information related to the travel path of vehicle 40. Server device 20 maintains the path information of the target vehicle in storage unit 26 in association with lane information. Lane information is information related to the lanes of a road. For example, server device 20 can maintain not only the information of the link the target vehicle is traveling on, but also information of which lane the target vehicle is traveling in among the multiple lanes of the road corresponding to that link.

[0036] In addition, the storage unit 26 stores overview information about the vehicles targeted for autonomous driving assistance. The control unit 24 periodically transmits dynamic map information to each vehicle included in the overview information.

[0037] Based on the received vehicle information and the maintained path information, the control unit 24 selects a subset of nodes from multiple nodes as selected nodes and selects a subset of links from multiple links as selected links.

[0038] The control unit 24 generates dynamic map information based on the road condition information related to the selected node and selected link from the acquired road condition information and the map information stored in the storage unit 26. Dynamic map information is obtained by adding road condition information to the map information. For example, dynamic map information includes point cluster data representing the location of pedestrians, pedestrian movement paths, the travel paths of vehicles 40 within a certain time period, and data representing the locations of parked vehicles, works of art, and obstacles on the road.

[0039] The dynamic map sending unit 25 sends the information generated in the control unit 24 as dynamic map information to the vehicle 40.

[0040] The control unit 32 of the roadside device 30 acquires road condition information around the roadside device 30 from the sensor 33 and outputs it to the communication unit 31. The communication unit 31 sends the acquired road condition information to the server device 20. In addition, the control unit 42 of the vehicle 40 controls the drive device, braking device, steering device, etc. (not shown) of the vehicle 40 according to the vehicle information and the road condition information received from the server device 20, thereby enabling the vehicle 40 to drive autonomously.

[0041] When vehicle 40 receives dynamic map information, the received dynamic map information overlaps with the map information stored in storage unit 43 of vehicle 40, and is used to determine the acceleration, deceleration, and stopping of vehicle 40. Server device 20 refers to the location information contained in the vehicle information received from the target vehicle that sent the dynamic map information and the map information stored in storage unit 26 to obtain the path or node that vehicle 40 is traveling on.

[0042] The map information stored in server device 20 and vehicle 40 is static map information. Static map information includes terrain, road information, etc. As static map information, for example, GDF5.0 (Geographic Data Files 5.0), which is one of the international standards for road maps, can be used, but maps based on other international standards or their own standards can also be used.

[0043] In addition, Figure 1 Only one roadside device 30 and one vehicle 40 are shown in the illustration, but in Embodiment 1, a server device 20 can communicate with multiple roadside devices and multiple vehicles. Therefore, the communication unit 21 also receives vehicle information from vehicles that are not the target vehicle. In this case, the communication unit 21 receives vehicle information asynchronously and periodically from multiple vehicles 40, and receives road condition information asynchronously and periodically from multiple roadside devices 30.

[0044] Figure 2 It indicates applicability. Figure 1 A diagram showing the intersection conditions of the autonomous driving assistance device 10. Figure 2 The intersection 50 shown connects four roads 61, 62, 63, and 64. That is, in this example, there are four links connected at one node. Hereinafter, intersection 50 will also be referred to as node #1, and roads 61, 62, 63, and 64 will be referred to as link #1, link #2, link #3, and link #4, respectively.

[0045] Roads 61, 62, 63, and 64 are two-lane, one-way roads with left-hand traffic. Road 62 is an extension of road 61. That is, vehicles traveling on road 61 can proceed straight onto road 62, and vehicles traveling on road 62 can proceed straight onto road 61.

[0046] A first roadside device 301 and a second roadside device 302 are installed at the roadside of intersection 50. Although not shown, sensors are installed on both the first roadside device 301 and the second roadside device 302. Each sensor is equivalent to... Figure 1 Sensor 33. Each sensor detects road condition information.

[0047] The detectable area AR1 of the sensor of the first roadside device 301 is a portion of intersection 50, a portion of road 62, and a portion of road 64. The sensor of the first roadside device 301 primarily detects the condition of road 62. The detectable area AR2 of the sensor of the second roadside device 302 is a portion of intersection 50, a portion of road 62, a portion of road 63, and a portion of road 64. The sensor of the second roadside device 302 primarily detects the condition of road 64.

[0048] exist Figure 2 Among them, eight vehicles, 401 to 408, are either moving or stopped. Vehicle 401 is traveling straight in lane 61a of road 61, that is, in Figure 2 Vehicle 402 travels in lane 61a of road 61 and then turns right at intersection 50 to enter road 64. Vehicles 403 and 404 travel straight in the opposite lane 62b of road 62. Figure 2 Vehicles 405, 406, and 407 are stopped on road 64 waiting for the signal. Vehicle 408 is stopped on road 63 waiting for the signal.

[0049] Additionally, a base station 70 is installed near intersection 50. Base station 70 relays communication between server device 20 and the first roadside device 301, between server device 20 and the second roadside device 302, and between server device 20 and vehicle 402. Relaying by base station 70 is not necessarily required, and base station 70 may not be installed. In this case, the first roadside device 301, the second roadside device 302, and vehicle 402 can communicate directly with server device 20.

[0050] The sensors of the first roadside device 301 can detect vehicles 403 and 404. The server device 20 receives road condition information about road 62 from the first roadside device 301 via the base station 70. Therefore, the road condition information about road 62 includes information related to vehicles 403 and 404.

[0051] The sensors of the second roadside device 302 can detect vehicles 405, 406, and 407. The server device 20 receives road condition information about road 64 from the second roadside device 302 via the base station 70. Therefore, the road condition information about road 64 includes information related to vehicles 405, 406, and 407.

[0052] Here, we consider vehicle 402 as an autonomous vehicle, the object vehicle whose dynamic map information is sent by server device 20. The travel path of vehicle 402 is road 61 → intersection 50 → road 64, that is, link #1 → node #1 → link #4.

[0053] Vehicles 403 and 404 travel on link #2, an extension of link #1 traveled by vehicle 402, and travel in the opposite direction of vehicle 402 in lane 62b of lane 61a. This mode of travel for vehicles 403 and 404 is referred to as the first mode of travel.

[0054] Vehicles 405, 406, and 407 detected by the sensors of the second roadside device 302 are vehicles on the travel path of vehicle 402, but road 64 does not exist on the extension of the link traveled by vehicle 402.

[0055] The control unit 24 of the server device 20 receives road condition information of road 62 from the first roadside device 301 via the base station 70. The road condition information of road 62 includes information related to vehicles 403 and 404. Additionally, the control unit 24 obtains vehicle information of vehicle 402 from the base station 70. Furthermore, the control unit 24 obtains map information from the storage unit 26. Then, based on the road condition information of road 62, the vehicle information of vehicle 402, and the map information, the control unit 24 determines that vehicles 403 and 404 are traveling according to the aforementioned "first driving mode".

[0056] Additionally, the control unit 24 obtains road condition information for road 64 from the second roadside device 302 via base station 70. The road condition information for road 64 includes information related to vehicles 405, 406, and 407. Based on the road condition information for road 64, the vehicle information for vehicle 402, and the map information, the control unit 24 determines that the driving mode of vehicles 405, 406, and 407 does not conform to the aforementioned "first driving mode".

[0057] In this example, the control unit 24 appends road condition information from the first roadside device 301 to the static map information, but does not append road condition information from the second roadside device 302 to the static map information. Then, the dynamic map sending unit 25 of the server device 20 sends the map information with the road condition information from the first roadside device 301 appended as dynamic map information to the vehicle 402.

[0058] When the communication unit of vehicle 402 receives dynamic map information from server device 20, the control unit of vehicle 402 assists in the autonomous driving of vehicle 402 based on the received dynamic map information. For example, the control unit of vehicle 402 stops vehicle 402 before vehicle 403 and vehicle 404 pass through intersection 50, and causes vehicle 402 to turn right after vehicle 403 and vehicle 404 pass through intersection 50.

[0059] exist Figure 2 In the example shown, the target vehicle, i.e., vehicle 402, is traveling on a node, but there are also cases where the target vehicle is traveling on a link. Therefore, in the autonomous driving assistance device 10 according to Embodiment 1, it is determined whether the target vehicle is traveling on a node or on a link, and the range of road condition information attached to the map information is changed as dynamic map information.

[0060] For example, when the vehicle 40 is traveling on a node, the server device 20 attaches road condition information contained in the range of the map corresponding to the node and the links adjacent to the node to the map information and sends it to the vehicle 40 as dynamic map information.

[0061] On the other hand, when the vehicle 40 is traveling on the link, the server device 20 adds road condition information contained in the range of the map corresponding to the link and the next node to be reached, and the link adjacent to the node, to the map information and sends it to the vehicle 40 as dynamic map information.

[0062] In addition, Figure 2 The example shown selects road condition information for links where a vehicle corresponding to the first mode of travel exists. However, road condition information for links connecting to the node the target vehicle is currently traveling to, or for links connecting to a predetermined node the target vehicle will travel to next, can also be appended to the map information. (See reference...) Figure 3 This section explains the processing in the control unit 24 of the server device 20 under these circumstances.

[0063] Figure 3 It means Figure 1 A flowchart of the autonomous driving assistance program executed by the control unit 24 of the autonomous driving assistance device 10. Figure 3The program, for example, is initiated by turning on the vehicle's ignition key switch and is executed after a certain amount of time.

[0064] When it begins Figure 3 During the procedure, the control unit 24 first obtains the vehicle information of the vehicle 40 from the vehicle 40 in step S101.

[0065] Next, in step S102, the control unit 24 obtains road condition information from the roadside device 30.

[0066] Next, in step S103, the control unit 24 determines whether the target vehicle for sending dynamic map information is currently traveling on the link. If the target vehicle for sending dynamic map information is currently traveling on the link, in step S104, the control unit 24 selects the currently traveling link and the link connected to the next arriving node as the selected link. Additionally, the control unit 24 selects the next arriving node as the selected node.

[0067] On the other hand, when the vehicle used to send dynamic map information is not traveling on a link, that is, when it is traveling on a node, the control unit 24 selects the link connected to the currently traveling node as the selected link in step S105. Additionally, the control unit 24 selects the currently traveling node as the selected node.

[0068] Next, in step S106, the control unit 24 acquires vehicle information and road condition information contained in the map range of the acquired links and nodes.

[0069] Next, in step S107, the control unit 24 sends the acquired vehicle information and road condition information as dynamic map information to the target vehicle 40, temporarily ending the program.

[0070] As described above, the autonomous driving assistance device 10 according to Embodiment 1 includes a server device 20. The server device 20 receives road condition information from a roadside device 30 and sends dynamic map information to a vehicle 40, which is the target vehicle. In the server device 20, the map information is stored as a combination of multiple nodes and multiple links. Additionally, the server device 20 maintains the target vehicle's path information. The server device 20 receives vehicle information from the vehicle 40. Based on the path information and the received vehicle information, the server device 20 selects a subset of nodes from the multiple nodes as selected nodes and selects a subset of links from the multiple links as selected links. The server device 20 sends the information obtained by appending road condition information related to the selected nodes and selected links to the map information as dynamic map information to the vehicle 40.

[0071] According to the autonomous driving assistance device 10, since the dynamic information of the dynamic map information also includes information about paths other than the driving path of the target vehicle, it is possible to suppress the situation where appropriate autonomous driving assistance cannot be performed due to insufficient information.

[0072] Furthermore, according to the autonomous driving assistance device 10, the dynamic map information sent from the server device 20 to the target vehicle does not contain information unnecessary for the target vehicle's driving assistance. Therefore, in the target vehicle's control unit, there is no risk of control delay caused by increased computational processing load due to a large amount of information, nor is there a risk of unnecessary information becoming noise and causing errors in the calculation results. In other words, according to the autonomous driving assistance device 10, autonomous driving assistance for the vehicle can be performed more appropriately.

[0073] Furthermore, according to the autonomous driving assistance device 10, when the target vehicle is driving on one of multiple links, the selected link is the link that satisfies the following condition 1.

[0074] Condition 1: The target vehicle is currently traveling on one link, and there are at least one other link connected to this link and connected to the next node the target vehicle will reach, which is different from this link.

[0075] Additionally, select a node that is connected to the link currently being traveled by the target vehicle, and that is the node the target vehicle will arrive at next.

[0076] On the other hand, when the target vehicle is traveling on one of multiple nodes, the selected link is a link that connects to the node the target vehicle is currently traveling on and is different from the links the target vehicle has already traversed. Furthermore, the selected node is the node the target vehicle is currently traveling on.

[0077] Therefore, regardless of whether the target vehicle is traveling on the link or at the node, it is possible to provide more appropriate autonomous driving assistance to the target vehicle.

[0078] Furthermore, according to this autonomous driving assistance device 10, the server device 20 maintains the path information in association with the lane-related information of the road, i.e., lane information. Thus, for example, it is possible to distinguish between vehicles traveling in the opposite lane and vehicles traveling in other lanes, thereby enabling more appropriate autonomous driving assistance for the vehicle.

[0079] Implementation method 2.

[0080] Next, the autonomous driving assistance device according to Embodiment 2 will be described. In Embodiment 2, an arrival cost is defined for each link in the map information defined by links and nodes. The arrival cost is a numerical representation of the difficulty of movement when a vehicle moves between two nodes connected by a link. For example, the longer the link distance, the higher the arrival cost tends to be. In addition, for example, the arrival cost increases when the link is congested.

[0081] Here, arrival cost is defined as the cost of movement calculated based on the average travel time required to move between two nodes and the distance between the two nodes. In other words, arrival cost is a relative weighted average for each link.

[0082] Except for the cost of arrival, the structure is the same as that of the autonomous driving assistance device 10 involved in Embodiment 1.

[0083] Figure 4 This is a diagram used to illustrate the arrival cost in the autonomous driving assistance device according to Embodiment 2. Figure 4 The diagram shows eight nodes N1 to N8 and 13 links L1 to L13 connected to them. Link L1 connects nodes N1 and N2. The arrival cost of link L1 is 3. Additionally, link L13 connects nodes N7 and N8. The arrival cost of link L13 is 6.

[0084] For example, when the arrival cost is determined based on time, it means that it takes twice as long for link L13 to move relative to link L1. Conversely, when the arrival cost is determined based on distance, it means that link L13 is twice the distance relative to link L1.

[0085] Additionally, for example, when a vehicle moves from node N1 to node N3 via node N2, the arrival cost of the path "A→B→G" is calculated as the sum of the arrival costs of link L1 and link L2. In this example, the total arrival cost is calculated as the cumulative value of each arrival cost. That is, the arrival cost of the path "A→B→G" is 5.9.

[0086] Figure 5 This is a diagram used to illustrate the arrival cost in the autonomous driving assistance device according to Embodiment 2. Figure 5 The path “S→C→D→G” shown is the path with the minimum total arrival cost when moving from the vehicle's starting point (node ​​N4) to its destination (node ​​N3). In this example, the vehicle travels through links L8, L9, and L7, and the total arrival cost is 6.3.

[0087] In Implementation Method 2, the server device 20 determines the selected nodes and links based on the vehicle information of the target vehicle, the path information of the target vehicle, and the arrival costs of each link. For example, links whose arrival costs, including the current route of the target vehicle and the arrival costs of links originating from the next node reached by the target vehicle, are below a certain threshold are selected as the selected links. If the arrival cost of the current route of the target vehicle exceeds the threshold, only that link is selected.

[0088] The following is for reference Figure 4 The following example illustrates the scenario where the decision value is set to "4" and the vehicle travels along the path "S→C→D→G". When the vehicle starts from node N4 and travels on link L8, the arrival cost of the travel link is 4. Therefore, server device 20 selects only the travel link as the chosen link.

[0089] Next, when the vehicle travels on link L9, the arrival cost of the travel link is 1.3, which is 2.7 less than the decision value. In this case, the server device 20 selects the link with an arrival cost of 2.7 or less from the links connecting to the next node N6 that the vehicle will reach. Therefore, the server device 20 selects link L9, link L6 with an arrival cost of 1.5, and link L7 with an arrival cost of 1 as the selected links.

[0090] When the vehicle is traveling on link L7, the arrival cost of the travel link is 1, which is 3 less than the decision value. In this case, the server device 20 selects the link with an arrival cost of 3 or less from the links connecting to the next node N3 that the vehicle will reach. Therefore, the server device 20 selects link L7 and link L2, which has an arrival cost of 2.9, as the selected links.

[0091] Here, assuming the cost of links L12 and L13 is 1, when the vehicle travels on link L9, the total cost of reaching the destination via link L9, link L12, and link L13 is 3.3, which is less than the decision value. Therefore, in this case, in addition to selecting links L9, L6, and L7, server device 20 also selects links L12 and L13 as selected links.

[0092] Figure 6 This is a flowchart showing the autonomous driving assistance program executed by the control unit 24 of the autonomous driving assistance device 10 according to Embodiment 2. Figure 6 The program, for example, begins when the vehicle's ignition key is switched on, and executes after a certain amount of time. Figure 6 In the middle, to and Figure 3 Steps that are identical in the program are assigned the same step number. Descriptions are omitted for these identical steps.

[0093] When the autonomous driving assistance device starts, the control unit 24 performs the processing from step S101 to step S103.

[0094] When the target vehicle used to send dynamic map information is traveling on a link, the control unit 24 selects a link in step S201 as follows: The control unit 24 selects a link whose total arrival cost, including the currently traveling link and the links originating from the next node, is below a decision value.

[0095] On the other hand, when the target vehicle used to send dynamic map information is not traveling on the link, that is, when the target vehicle is traveling on a node, the control unit 24 selects the link in step S202 as follows: The control unit 24 selects the link whose total arrival cost from the currently traveling node is below the judgment value as the selected link. In addition, the control unit 24 selects the next arriving node and the node between the selected links as the selected node.

[0096] After executing the processing of step S201 or step S202, the control unit 24 executes the processing of step S106 and step S107 in sequence, and temporarily terminates the program.

[0097] As described above, in the autonomous driving assistance device 10 according to Embodiment 2, an arrival cost is assigned as a relative weighted average for each link. The server device 20 determines the selected node and the selected link based on the vehicle information of the target vehicle, the path information of the target vehicle, and the arrival cost.

[0098] Even for links other than the one the target vehicle is currently traveling on, it is envisioned that the closer the target vehicle is to other links, the greater the necessity to consider road condition information about other links for the purpose of assisting the control of the target vehicle. Therefore, as with the autonomous driving assistance device according to Embodiment 2, by taking into account the arrival cost when deciding on the selection of nodes and links, the autonomous driving assistance of the target vehicle can be performed more appropriately.

[0099] Furthermore, in the autonomous driving assistance device 10 according to Embodiment 2, the arrival cost is determined based on the time required for the target vehicle to move between the two nodes connected by each link. Therefore, autonomous driving assistance for the target vehicle can be performed more appropriately.

[0100] Furthermore, in the autonomous driving assistance device 10 according to Embodiment 2, the arrival cost is determined according to the distance of each link. Therefore, autonomous driving assistance for the target vehicle can be performed more appropriately.

[0101] Furthermore, in the autonomous driving assistance device 10 according to Embodiment 2, the selected links are a group of links in which the total arrival cost of each link within the selected links is less than or equal to a decision value. Therefore, autonomous driving assistance for the target vehicle can be performed more appropriately.

[0102] Although the total arrival costs is a simple sum of the individual arrival costs, it can also be the sum of the squares of the individual arrival costs, or it can be accumulated using other methods.

[0103] In addition, the arrival cost is calculated based on the average travel time required to move between two nodes and the distance between the two nodes. However, in addition to time and distance, other variable factors such as weather and road conditions can also be considered in the calculation.

[0104] Implementation method 3.

[0105] Next, the autonomous driving assistance device according to Embodiment 3 will be described. In the autonomous driving assistance device according to Embodiment 3, an example of autonomous driving assistance for the target vehicle when turning right or left at an intersection will be described. The structure of the autonomous driving assistance device according to Embodiment 3 is the same as that of the autonomous driving assistance device 10 according to Embodiment 1 and the autonomous driving assistance device 10 according to Embodiment 2.

[0106] Figure 7 This is a diagram illustrating an example of the control of the autonomous driving assistance device according to Embodiment 3. Figure 7 The diagram shows intersection 50 as a node and four roads 61, 62, 63, and 64 as links connecting to intersection 50. Roads 61, 62, 63, and 64 are two-lane roads for left-hand traffic.

[0107] Additionally, roadside devices 311, 312, and 313 are installed at three of the four corners of intersection 50. The detectable area AR3 of the sensor of roadside device 311 is a portion of road 64. The detectable area AR4 of the sensor of roadside device 312 is a portion of road 61. The detectable area AR5 of the sensor of roadside device 313 is a portion of road 63.

[0108] Vehicle 411 is traveling on road 62 towards intersection 50, and vehicle 412 is traveling on road 61 towards intersection 50. Vehicle 411 is a vehicle capable of autonomous driving and serves as an aid to autonomous driving. Vehicle 411 then intends to turn left at intersection 50 and travel on road 64. Vehicle 411a represents the future vehicle 411 traveling on the predetermined path.

[0109] Here, vehicle 412 is traveling in the opposite direction to vehicle 411 and is approaching vehicle 411. Hereinafter, such a vehicle is referred to as an "approaching vehicle in the opposite direction".

[0110] In addition, Figure 7 In the middle, pedestrian 81 is crossing road 64, and pedestrian 82 is crossing road 63.

[0111] Although Figure 7 Not shown in the diagram, but server device 20 receives road condition information within the detectable area AR3 from roadside device 311. Therefore, the road condition information from roadside device 311 includes information related to pedestrian 81. Server device 20 receives road condition information within the detectable area AR4 from roadside device 312. Therefore, the road condition information from roadside device 312 includes information related to vehicle 412.

[0112] Server device 20 receives road condition information within the detectable area AR5 from roadside device 313. Therefore, the road condition information from roadside device 313 includes information related to pedestrian 82. In addition, server device 20 receives vehicle information and the travel path of vehicle 411 from vehicle 411.

[0113] Server device 20 maintains the path information of vehicle 411. In addition, server device 20 receives vehicle information of vehicle 411.

[0114] Server device 20 selects the links corresponding to road 62 and road 64 as selected links. Server device 20 attaches the road condition information of the selected links to the map information stored in server device 20, and sends the resulting information as dynamic map information to vehicle 411.

[0115] Therefore, the control unit of vehicle 411 recognizes the presence of pedestrian 81 crossing road 64, and vehicle 411 stops in front of pedestrian 81, just as vehicle 411a does. Thus, in a left-hand traffic lane, when the target vehicle turns left, only links on the travel path connecting to the next node reached by the target vehicle are selected as the selected links. The same applies to a right-hand traffic lane when the target vehicle turns right; only links on the travel path are selected as the selected links.

[0116] That is, in server device 20, when the target vehicle, i.e. vehicle 411, is traveling on the link and intends to turn right or left at the next node that vehicle 411 will reach, the road condition information of the link that is connected to the next node that vehicle 411 will reach and exists in the direction that vehicle 411 is turning will be sent to vehicle 411 as dynamic map information.

[0117] Therefore, since unnecessary road condition information is not sent to the target vehicle, autonomous driving assistance can be provided more appropriately.

[0118] Figure 8 This is a diagram illustrating an example of the control of the autonomous driving assistance device according to Embodiment 3. Figure 8 This is a picture of vehicle 411 intending to turn right at intersection 50. Aside from the fact that vehicle 411 intends to turn right, it is... Figure 7 same.

[0119] In this example, server device 20 selects the links corresponding to road 62, road 63, and road 61 as selected links. Server device 20 attaches the road condition information of the selected links to the map information stored in server device 20, and sends the resulting information as dynamic map information to vehicle 411.

[0120] Therefore, the control unit of vehicle 411 detects the presence of pedestrian 82 crossing road 63, and also detects the presence of vehicle 412 traveling on road 61 and approaching vehicle 411. Vehicle 411 stops in front of pedestrian 82, just as vehicle 411b does.

[0121] Therefore, on roads where traffic flows on the left, when a vehicle turns right and there are oncoming vehicles approaching, the link connecting to the next node the vehicle will reach is selected from the links on the current travel path and the extension of the current travel path. Additionally, links in the direction the vehicle is turning (411) are also selected. The same applies when the vehicle turns left on roads where traffic flows on the right.

[0122] That is, in the server device 20, when the target vehicle, i.e. vehicle 411, is traveling on the link, and vehicle 411 intends to turn right or left at the next node it will reach, and when the predetermined travel path of the oncoming vehicle, i.e. vehicle 412, intersects with the predetermined travel path of vehicle 411, the vehicle information of vehicle 412 is sent to vehicle 411 as dynamic map information.

[0123] Therefore, since unnecessary road condition information is not sent to the target vehicle, autonomous driving assistance can be provided more appropriately.

[0124] If one or more vehicles are traveling in the opposite direction to the target vehicle and in a direction away from the target vehicle, the server device 20 may not send information related to the location and driving status of the one or more vehicles to the target vehicle.

[0125] As a result, by further reducing unnecessary information, the server device 20 is able to provide more appropriate autonomous driving assistance.

[0126] In addition, in embodiments 1 to 3, MEC was used as server device 20, but server device 20 is not particularly limited to MEC.

[0127] In addition, the functions of the autonomous driving assistance devices in embodiments 1 to 3 are implemented by processing circuits. Figure 9 This is a structural diagram illustrating a first example of a processing circuit that implements the functions of the autonomous driving assistance device according to embodiments 1 to 3. The processing circuit 100 of the first example is dedicated hardware.

[0128] Additionally, the processing circuit 100 may be, for example, a single circuit, a composite circuit, a programmable processor, a parallel programmable processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a combination thereof.

[0129] in addition, Figure 10 This is a structural diagram illustrating a second example of a processing circuit that implements the functions of the autonomous driving assistance device according to embodiments 1 to 3. The processing circuit 200 of the second example includes a processor 201 and a memory 202.

[0130] In the processing circuit 200, the functions of the autonomous driving assistance device are implemented by software, firmware, or a combination of software and firmware. The software and firmware are expressed in the form of programs and stored in the memory 202. The processor 201 reads the program stored in the memory 202 and executes it, thereby implementing the functions.

[0131] The program stored in memory 202 can also be described as a program that causes the computer to execute the steps or methods described above. Here, memory 202 is, for example, a non-volatile or volatile semiconductor memory such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), or EEPROM (Electrically Erasable Programmable Read Only Memory). Additionally, disks, floppy disks, optical disks, compressed disks, mini disks, DVDs, etc., can also be memory 202.

[0132] The functions of the aforementioned autonomous driving assistance devices can be implemented using dedicated hardware for some functions and software or firmware for others.

[0133] Therefore, the processing circuit can utilize hardware, software, firmware, or a combination thereof to implement the functions of the aforementioned autonomous driving assistance device.

[0134] Label Explanation

[0135] 10 Autonomous driving assistance device, 20 Server device, 24 Control unit, 25 Dynamic map transmission unit, 26 Storage unit, 30 Roadside equipment, 31 Communication unit, 32 Control unit, 33 Sensor, 40 Vehicle (object vehicle), 41 Communication unit, 42 Control unit, 43 Storage unit, 50 Intersection (node), 61-64 Road (link), 311-313 Roadside equipment, 401-408, 411, 412 Vehicle, L1-L13 Link, N1-N9 Node.

Claims

1. An autonomous driving assistance device, characterized in that, The system includes a server device that receives road condition information (related to the conditions around the roadside equipment) from roadside equipment and sends dynamic map information (resulting from appending the road condition information) to the target vehicle autonomously traveling along a predetermined path. In the server device, the map information is stored as a combination of multiple nodes and multiple links. Each of the nodes corresponds to an intersection. Each of the links corresponds to a road connecting two adjacent intersections. The server device maintains information related to the travel path, namely path information. Receive vehicle information, which includes information related to the location of the target vehicle and information related to the driving status of the target vehicle. Based on the vehicle information and the path information, it is determined whether the target vehicle is traveling on a link or on a node. Based on the determination result, a subset of nodes are selected as selected nodes from the plurality of nodes, and a subset of links are selected as selected links from the plurality of links. The information obtained by appending the road condition information related to the selected node and the selected link to the map information is sent as the dynamic map information to the target vehicle. The determination result is that the target vehicle is traveling on one of the multiple links. The selected link is the link that the target vehicle is currently traveling on, and one or more links that are connected to the target vehicle and to the next node the target vehicle will reach, and that are different from the target link. The selected node is connected to the link that the target vehicle is currently traveling on and is the node that the target vehicle will arrive at next. The determination result is based on the condition that the target vehicle is traveling at one of the multiple nodes. The selected link is a link that connects to the node the target vehicle is currently traveling on and is different from the links the target vehicle has already passed. The selected node is the node where the target vehicle is currently driving.

2. The autonomous driving assistance device as described in claim 1, characterized in that, Assign a relative weighted cost, i.e., a cost of arrival, to each of the links. The server device determines the selected node and the selected link based on the vehicle information, the route information, and the arrival cost.

3. The autonomous driving assistance device as described in claim 2, characterized in that, The arrival cost is determined in accordance with the time required for the target vehicle to move between the two nodes connected by each of the links.

4. The autonomous driving assistance device as described in claim 2, characterized in that, The arrival cost is determined based on the distance of each of the links.

5. The autonomous driving assistance device as described in any one of claims 2 to 4, characterized in that, The selected links are a group of links whose total arrival cost is below a certain threshold.

6. The autonomous driving assistance device as described in any one of claims 1 to 4, characterized in that, The server device does not send the following information to the target vehicle: information related to the position and driving status of one or more vehicles traveling in the direction opposite to the target vehicle on the predetermined driving path.

7. The autonomous driving assistance device as described in any one of claims 1 to 4, characterized in that, If the target vehicle is traveling on the link and intends to turn right or left at the node that the target vehicle will arrive at next, the server device will send the road condition information of the link that is connected to the node that the target vehicle will arrive at next and exists in the turning direction of the target vehicle as the dynamic map information to the target vehicle.

8. The autonomous driving assistance device as described in any one of claims 1 to 4, characterized in that, If the target vehicle is traveling on the link and intends to turn right or left at the node it will reach next, and if the predetermined travel path of one or more vehicles traveling in the opposite direction and approaching the target vehicle intersects with the predetermined travel path of the target vehicle, then the server device will send the vehicle information of the approaching vehicles as the dynamic map information to the target vehicle.

9. The autonomous driving assistance device as described in any one of claims 1 to 4, characterized in that, The server device maintains the path information in association with lane information about the road.

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