Driving path determination method, device and system and storage medium

Abstract

The invention discloses a driving path determination method, device and system and a storage medium, which are used for quickly responding to local changes and improving the flexibility of path planning. The method comprises the following steps: determining at least one driving area of a vehicle according to a starting point and an ending point corresponding to a path planning task; dividing the path planning task into sub-tasks corresponding to the driving areas according to the driving areas of the vehicle; distributing the sub-tasks corresponding to each driving area to the corresponding driving area, so that each driving area calculates the driving cost of all paths included in the driving area; summarizing the driving cost of all paths included in each driving area; and determining the path with the minimum driving cost from the starting point to the end point as the optimal driving path according to the driving cost of all the paths contained in each driving area. According to the scheme, global data does not need to be obtained, the data processing speed and the response speed of local changes are improved, and global planning under partition cooperation has better flexibility.

Description

Technical Field

[0001] The present application relates to the technical field of path planning, and in particular to a driving path determination method, device, system and storage medium. Background Art

[0002] Existing global path planning often requires obtaining all relevant data in order to plan the overall path. However, for regional distributed systems with relatively isolated data, the data may be distributed in different nodes or regions, and due to privacy, security or technical limitations, the data may not be shared across regions. Even if the data can be shared in theory, in practice, due to network latency or data synchronization issues, the global planning algorithm may not be able to obtain the latest data in real time, resulting in planning results that are inconsistent with the actual situation. In addition, centralized processing of global data requires a large amount of computing resources and communication bandwidth, which may be a bottleneck for distributed systems, especially in large-scale or resource-constrained scenarios. Therefore, when facing regional distributed systems, existing global path planning is often not flexible enough and cannot reflect changes in the local environment in a timely manner.

[0003] Therefore, how to provide a driving path determination method to quickly respond to local changes and improve the flexibility of path planning. Summary of the invention

[0004] The present application provides a driving path determination method, device, system and storage medium for quickly responding to local changes and improving the flexibility of path planning.

[0005] The present application provides a method for determining a driving path, comprising:

[0006] Determine at least one driving area of ​​the vehicle according to the starting point and the end point corresponding to the path planning task;

[0007] Dividing the path planning task into subtasks corresponding to each driving area according to the driving area of ​​the vehicle;

[0008] Distribute the subtasks corresponding to each driving area to the corresponding driving area, so that each driving area calculates the driving costs of all paths contained in the driving area;

[0009] Summarize the travel costs of all paths included in each travel area;

[0010] According to the travel costs of all the paths included in each travel area, the path with the smallest travel cost from the starting point to the end point is determined as the optimal travel path.

[0011] The beneficial effects of the present application are: determining at least one driving area of ​​the vehicle according to the starting point and the end point corresponding to the path planning task; then, dividing the path planning task into subtasks corresponding to each driving area according to the driving area of ​​the vehicle, and distributing the subtasks corresponding to each driving area to the corresponding driving area, so that each driving area calculates the driving costs of all the paths contained in the driving area; and then the driving costs of all the paths contained in each driving area can be summarized; and the path with the minimum driving cost from the starting point to the end point is determined as the optimal driving path according to the driving costs of all the paths contained in each driving area. Since the present application distributes the path planning tasks to each driving area respectively, and each driving area calculates the driving costs of all the paths within its own range, there is no need to obtain and process global data, thereby improving the data processing speed, improving the response speed of local changes, and making the global planning under partition coordination more flexible.

[0012] In one embodiment, determining at least one driving area of ​​the vehicle according to the starting point and the end point corresponding to the path planning task includes:

[0013] Determine the line from the starting point to the end point on the electronic map;

[0014] Determine a rectangular frame of a preset size that can enclose the line connecting the starting point to the end point;

[0015] The area within the rectangular frame is divided according to administrative area division rules to form at least one driving area of ​​the vehicle, and each driving area corresponds to an administrative area of ​​a preset level.

[0016] In one embodiment, the path planning task is divided into subtasks corresponding to each driving area according to the driving area of ​​the vehicle, including:

[0017] Determine an adjacency matrix of vehicles in a plurality of driving intervals;

[0018] The subtasks are divided according to the adjacency relationship matrix of the vehicle driving task.

[0019] In one embodiment, determining an adjacency matrix of a vehicle in a plurality of driving intervals includes:

[0020] The intersection points of each adjacent area boundary line and the road are taken as endpoints, and each endpoint is numbered;

[0021] An adjacency relationship matrix of the vehicle in a plurality of driving intervals is determined according to the number.

[0022] In one embodiment, distributing the subtasks corresponding to each driving area to the corresponding driving area includes:

[0023] Determine all endpoints of the first driving area where the starting point is located according to the adjacency relationship matrix;

[0024] Determine the subtask corresponding to the first driving area as the driving cost from the starting point to all endpoints of the first driving area;

[0025] Determine a second driving area adjacent to the first driving area according to the adjacency relationship matrix;

[0026] The subtask corresponding to the second driving area is determined to be a driving cost from an end point to an end point common to the first driving area and the second driving area, and the first driving area distributes the subtask corresponding to the second driving area to the second driving area.

[0027] In one embodiment, when there is a third driving area adjacent to the second driving area, the method further includes:

[0028] The subtask corresponding to the third driving area is determined to be the driving cost from the endpoint to the end point shared by the second driving area and the third driving area, and the second driving area distributes the subtask corresponding to the third driving area to the third driving area, and so on, until the subtask at the end point is generated.

[0029] In one embodiment, the summarizing the travel costs of all paths included in each travel area includes:

[0030] When the subtasks of each driving area are completed, each driving area reports the driving cost calculation results corresponding to the subtasks to the driving area that distributes the subtasks, until the subtasks of each driving area are reported to the first driving area where the starting point is located, and the first driving area summarizes the calculation results.

[0031] The present application also provides a driving path determination device, comprising:

[0032] A first determination module, configured to determine at least one driving area of ​​the vehicle according to a starting point and an end point corresponding to the path planning task;

[0033] A division module, used for dividing the path planning task into subtasks corresponding to each driving area according to the driving area of ​​the vehicle;

[0034] A distribution module, used to distribute the subtasks corresponding to each driving area to the corresponding driving area, so that each driving area calculates the driving costs of all paths contained in the driving area;

[0035] A summary module is used to summarize the travel costs of all paths included in each travel area;

[0036] The second determination module determines, according to the driving costs of all the paths included in each driving area, a path with the minimum driving cost from the starting point to the end point as the optimal driving path.

[0037] In one embodiment, the first determining module includes:

[0038] A first determination submodule is used to determine a line from a starting point to an end point on an electronic map;

[0039] A second determining submodule is used to determine a rectangular frame of a preset size that can enclose the line from the starting point to the end point;

[0040] The segmentation submodule is used to segment the area within the rectangular frame according to the administrative area division rule to form at least one driving area of ​​the vehicle, and each driving area corresponds to an administrative area of ​​a preset level.

[0041] In one embodiment, the partitioning module comprises:

[0042] A third determination submodule is used to determine an adjacency relationship matrix of the vehicle in a plurality of driving intervals;

[0043] The division submodule is used to divide the subtasks according to the adjacency relationship matrix of the vehicle driving task.

[0044] In one embodiment, the third determining submodule is further used to:

[0045] The intersection points of each adjacent area boundary line and the road are taken as endpoints, and each endpoint is numbered;

[0046] An adjacency relationship matrix of the vehicle in a plurality of driving intervals is determined according to the number.

[0047] In one embodiment, the distribution module includes:

[0048] A fourth determination submodule, configured to determine all endpoints of the first driving area where the starting point is located according to the adjacency relationship matrix;

[0049] A fifth determination submodule is used to determine that the subtask corresponding to the first driving area is the driving cost from the starting point to all endpoints of the first driving area;

[0050] a sixth determining submodule, configured to determine a second driving area adjacent to the first driving area according to the adjacency relationship matrix;

[0051] The seventh determination submodule is used to determine that the subtask corresponding to the second driving area is the driving cost from the end point to the end point common to the first driving area and the second driving area, and the first driving area distributes the subtask corresponding to the second driving area to the second driving area.

[0052] In one embodiment, when there is a third driving area adjacent to the second driving area, the seventh determining submodule is further configured to:

[0053] The subtask corresponding to the third driving area is determined to be the driving cost from the endpoint to the end point shared by the second driving area and the third driving area, and the second driving area distributes the subtask corresponding to the third driving area to the third driving area, and so on, until the subtask at the end point is generated.

[0054] In one embodiment, the aggregation module is further used to:

[0055] When the subtasks of each driving area are completed, each driving area reports the driving cost calculation results corresponding to the subtasks to the driving area that distributes the subtasks, until the subtasks of each driving area are reported to the first driving area where the starting point is located, and the first driving area summarizes the calculation results.

[0056] The present application also provides a driving path determination system, comprising:

[0057] at least one processor; and,

[0058] a memory communicatively connected to the at least one processor; wherein,

[0059] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to implement the driving path determination method recorded in any of the above embodiments.

[0060] The present application also provides a computer-readable storage medium. When the instructions in the storage medium are executed by a processor corresponding to the driving path determination system, the driving path determination system can implement the driving path determination method recorded in any of the above embodiments.

[0061] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or be understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description, claims, and drawings.

[0062] The technical solution of the present application is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The accompanying drawings are used to provide a further understanding of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation of the present application. In the accompanying drawings:

[0064] Figure 1 This is a flow chart of a method for determining a driving path in one embodiment of the present application;

[0065] Figure 2 This is a schematic diagram of path planning in an embodiment of the present application;

[0066] Figure 3 This is a schematic diagram of determining the optimal driving path in an embodiment of the present application;

[0067] Figure 4 This is a schematic diagram of the structure of a driving path determination device in one embodiment of the present application;

[0068] Figure 5 This is a schematic diagram of the hardware structure of a driving path determination system in one embodiment of the present application. DETAILED DESCRIPTION

[0069] The preferred embodiments of the present application are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application and are not used to limit the present application.

[0070] Figure 1 Flow chart of a method for determining a driving path in one embodiment of the present application. Figure 1 As shown, the method can be implemented as the following steps S101-S105:

[0071] In step S101, at least one driving area of ​​the vehicle is determined according to the starting point and the end point corresponding to the path planning task;

[0072] In step S102, the path planning task is divided into subtasks corresponding to each driving area according to the driving area of ​​the vehicle;

[0073] In step S103, the subtasks corresponding to each driving area are distributed to the corresponding driving area, so that each driving area calculates the driving costs of all paths contained in the driving area;

[0074] In step S104, the travel costs of all paths included in each travel area are summarized;

[0075] In step S105 , the path with the smallest travel cost from the starting point to the end point is determined as the optimal travel path according to the travel costs of all the paths included in each travel area.

[0076] Determine at least one driving area of ​​the vehicle according to the starting point and the end point corresponding to the path planning task;

[0077] First, the starting point and the end point of the vehicle are obtained; when the user input includes the starting point and the end point, the starting point and the end point of the vehicle are determined according to the user input. When the user input only includes the end point, the end point of the vehicle is determined according to the user input, and the current position of the vehicle is obtained, and the current position of the vehicle is assumed to be the starting point of the vehicle. It can be understood that during the driving process of the vehicle, the current position of the vehicle is obtained in real time as the current starting point of the vehicle, and real-time path planning is performed.

[0078] Then, the driving area of ​​the vehicle is determined according to the starting point and the end point of the vehicle. In one embodiment of the present application, after obtaining the starting point and the end point of the vehicle, first determine the connection line from the starting point to the end point on the electronic map, for example, the connection line can be all the driving routes planned under the static global data view; determine a rectangular frame of a preset size that can enclose the connection line from the starting point to the end point, the rectangular frame can be set according to the preset distance from the starting point to the end point, and can also be determined as the minimum rectangular frame that encloses all the connections; then divide the area within the rectangular frame according to the administrative area division rule to form at least one driving area of ​​the vehicle, and each driving area corresponds to an administrative area of ​​a preset level. Figure 2 This is a schematic diagram of path planning in an embodiment of the present application, such as Figure 2 As shown, according to the starting point s and the end point e of the vehicle, a rectangular frame area that can wrap the line connecting the starting point and the end point is determined, and the area in the rectangular frame is divided according to the administrative area division, and divided into area A, area B, area C and area D. In another embodiment of the present application, the map is divided into multiple areas according to a preset area division rule, wherein the division of the map must ensure that the union of all areas constitutes the entire map, and each area does not intersect with each other. There are many regional division rules, for example, the map can be divided according to administrative areas, such as administrative towns and administrative villages; it can also be divided according to a preset area range, such as dividing the map into a range of 5Km×5Km; it can also be divided according to the camera monitoring range to ensure that the entire driving route of the vehicle can be monitored. Furthermore, when determining the driving area of ​​the vehicle, first plan all the driving routes of the vehicle under static global data according to the starting point and the end point of the vehicle. Then, determine all the areas passed by all the driving routes of the vehicle under static global data as the driving area of ​​the vehicle.

[0079] The path planning task is divided into subtasks corresponding to each driving area according to the driving area of ​​the vehicle. In the present application, the path planning task is achieved by calculating the minimum driving cost to determine the optimal driving path. There are many ways to determine the driving cost, such as determining the optimal path with the shortest driving time. Of course, when determining the driving cost, the number of times the red lights are passed, the degree of road congestion, the number of turns during driving, etc. can also be taken into account. Since the prior art of the specific determination method is relatively mature, this application will not expand on this. In order to improve the flexibility of road planning, the present application divides and distributes the planning tasks. First, determine the adjacency relationship matrix of the vehicle in multiple driving intervals; specifically, according to the driving direction of the vehicle, the intersection of each adjacent driving area boundary line and the road is used as an endpoint, and each endpoint is numbered. In one embodiment, in order to improve the calculation efficiency, only the intersection of each adjacent driving area boundary line and all driving routes of the vehicle under static global data is used as an endpoint, thereby improving data processing efficiency; such as Figure 2 For example, the endpoints of area A and area B are 1 and 2, and the endpoints of area B and area C are 9 and 10. The adjacency matrix of the vehicle in multiple driving intervals is determined according to the vehicle driving direction and the number, and the elements in the matrix are the endpoints passed when moving between each area. As shown in Table 1, Figure 2 An example table of the adjacency matrix within the driving area shown.

[0080] Table 1 Example of vehicle driving adjacency matrix

[0081] Starting point\end point A B C D A \ 1,2 3,4 \ B \ \ 9,10 5,6 C \ 9,10 \ 7,8 D \ \ \ \

[0082] Furthermore, the subtasks can be divided according to the adjacency matrix of the vehicle driving task, and the subtasks corresponding to each driving area can be distributed to the corresponding driving area, so that each driving area can calculate the driving costs of all paths contained in the driving area. Figure 2 The original task shown is to determine the minimum driving cost from s to e. First, all endpoints of the first driving area where the starting point is located are determined according to the adjacency matrix, and the subtask corresponding to the first driving area is determined as the driving cost from the starting point to all endpoints of the first driving area. Figure 2The first driving area where the starting point s is located is area A. According to the adjacency matrix shown in Table 1, it can be seen that all endpoints of area A include endpoints 1 and 2 from area A to area B, and endpoints 3 and 4 from area A to area C. Further, the subtask of area A is to determine the driving costs of s→1, s→2, s→3 and s→4. Then, the second driving area adjacent to the first driving area is determined according to the adjacency matrix; the subtask corresponding to the second driving area is determined to be the driving cost from the endpoint to the end point shared by the first driving area and the second driving area, and the first driving area distributes the subtask corresponding to the second driving area to the second driving area. As shown in Table 1, the second driving areas adjacent to area A are area B and area C. For the subtask corresponding to area B, the driving costs of 1→B→e and 2→B→e are determined; for the subtask corresponding to area C, the driving costs of 3→C→e and 4→C→e are determined. It can be understood that when there is a third driving area adjacent to the second driving area, the subtask corresponding to the third driving area can be further determined as the travel cost from the end point to the end point shared by the second driving area and the third driving area, and the second driving area distributes the subtask corresponding to the third driving area to the third driving area, and so on, until the subtask at the end point is generated. For example, the third driving area adjacent to area B is area D, and the values ​​of area B and area D are 5 and 6, so 1→B→e can be further decomposed into 1→5, 5→D→e, 1→6, 6→D→e, so that the subtask corresponding to area D is to determine the travel cost of 5→D→e and 6→D→e, and so on.

[0083] Summarize the driving costs of all paths included in each driving area. D returns the driving costs to B and C, and B and C return the driving costs to A, so that A can finally determine the minimum driving cost. According to the driving costs of all paths included in each driving area, the path with the minimum driving cost from the starting point to the end point is determined as the optimal driving path.

[0084] In such Figure 2 In the embodiment shown, the calculation process is as follows: In order to determine the optimal path planning from the starting point s to the end point e, which is converted into determining the driving path with the minimum total driving cost, the calculation method of setting the driving cost is as follows:

[0085] cost(s→e)=min(local_cost(s→Port)+remote_cost(Port→Area→e)),

[0086] Among them, cost is the total driving cost, min is the minimum value function, local_cost is the driving cost function of this area, remote_cost is the distributed driving cost function, s is the starting point, Port is the endpoint, Area is the adjacent area, and e is the end point.

[0087] For area A, local_cost(s→Port) is completed by area A itself; remote_cost(1→B→e) is sent to area B for completion; remote_cost(2→B→e) is sent to area B for completion; remote_cost(3→C→e) is sent to area C for completion; remote_cost(4→C→e) is sent to area C for completion.

[0088] After receiving the subtask, areas B and C complete the planning in the area according to the relay (traditional heuristic algorithms can be used), and the destination partition calculation is completed and the results will be returned in the reverse original path of the task distribution.

[0089] For the B area, accept the task and further decompose it:

[0090] ①remote_cost(1→B→e)=min(local_cost(1→Port)+remote_cost(Port→D→e)), where Port=5,6

[0091] ②remote_cost(2→B→e)=min(local_cost(2→Port)+remote_cost(Port→D→e)), where Port=5,6

[0092] Furthermore, subtasks remote_cost(5→D→e) and remote_cost(6→D→e) are distributed to zone D for completion.

[0093] The tasks of partition C are similar to those of partition B and are decomposed into:

[0094] remote_cost(3→C→e)=min(local_cost(3→Port)+remote_cost(Port→D→e));

[0095] remote_cost(4→C→e)=min(local_cost(4→Port)+remote_cost(Port→D→e)).

[0096] Figure 3 This is a schematic diagram of determining the optimal driving path in an embodiment of the present application, such as Figure 3As shown, the starting point partition collects the results of each partition and then centrally calculates and decides on this path planning.

[0097] cost=min(local_cost(s->Port)+remote_cost(Port->Area->e)), where Area=B,C. According to this example and the final solution with path cost, the result is cost(s->3->7->e)=9.5. Specifically, D returns cost(7->e) as the minimum cost result of this area to C, and C returns cost(3->e)=cost(3->7)+cost(7->e) to A. A obtains min_cost=cost(s->3)+cost(3->e)=cost(s->3)+cost(3->7)+cost(7->e)=2.5+2+5=9.5.

[0098] In practical applications, when calculating the travel cost between two endpoints in a certain area, it is necessary to take into account the actual changing traffic conditions, including the current connectivity of roads in the area, road congestion (the congested area cannot be perceived or calculated, so the free flow speed is considered), etc.; in addition, it is also necessary to consider the global planning for road network balance induction in the area, that is, the overall optimization of the path planning of vehicles within and entering the boundary for the goals of traffic flow balance in the area and avoiding local traffic hotspots.

[0099] It is understandable that the results calculated for each area may be used by other rounds of planning requirements. Therefore, the travel cost of each area can be calculated in advance and updated regularly (considering the slow change of traffic, minute-level cache can be used)

[0100] This application uses a "relay" approach to distribute tasks layer by layer instead of unified deployment, which makes the global planning calculation under partition collaboration more flexible and the zones more decoupled.

[0101] The beneficial effects of the present application are: determining at least one driving area of ​​the vehicle according to the starting point and the end point corresponding to the path planning task; then, dividing the path planning task into subtasks corresponding to each driving area according to the driving area of ​​the vehicle, and distributing the subtasks corresponding to each driving area to the corresponding driving area, so that each driving area calculates the driving costs of all the paths contained in the driving area; and then the driving costs of all the paths contained in each driving area can be summarized; and the path with the minimum driving cost from the starting point to the end point is determined as the optimal driving path according to the driving costs of all the paths contained in each driving area. Since the present application distributes the path planning tasks to each driving area respectively, and each driving area calculates the driving costs of all the paths within its own range, there is no need to obtain and process global data, thereby improving the data processing speed, improving the response speed of local changes, and making the global planning under partition coordination more flexible.

[0102] In one embodiment, the above step S101 may be implemented as the following steps A1-A2:

[0103] In step A1, a line connecting a starting point to an end point is determined on an electronic map;

[0104] In step A2, a rectangular frame of a preset size that can enclose the line connecting the starting point to the end point is determined;

[0105] In step A3, the area within the rectangular frame is segmented according to administrative area division rules to form at least one driving area of ​​the vehicle, and each driving area corresponds to an administrative area of ​​a preset level.

[0106] In one embodiment, the above step S102 may be implemented as the following steps B1-B2:

[0107] In step B1, an adjacency relationship matrix of the vehicle in a plurality of driving intervals is determined;

[0108] In step B2, subtasks are divided according to the adjacency relationship matrix of the vehicle driving task.

[0109] In one embodiment, the above step B1 can be implemented as the following steps B11-B12:

[0110] In step B11, the intersection points of each adjacent area boundary line and the road are taken as endpoints, and each endpoint is numbered;

[0111] In step B12, an adjacency matrix of the vehicle in a plurality of driving intervals is determined according to the serial number.

[0112] In one embodiment, the above step S103 may be implemented as the following steps C1-C4:

[0113] In step C1, all endpoints of the first driving area where the starting point is located are determined according to the adjacency relationship matrix;

[0114] In step C2, the subtask corresponding to the first driving area is determined as the driving cost from the starting point to all endpoints of the first driving area;

[0115] In step C3, a second driving area adjacent to the first driving area is determined according to the adjacency relationship matrix;

[0116] In step C4, the subtask corresponding to the second driving area is determined to be the driving cost from the end point to the end point common to the first driving area and the second driving area, and the first driving area distributes the subtask corresponding to the second driving area to the second driving area.

[0117] In one embodiment, when there is a third driving area adjacent to the second driving area, the method may also be implemented as the following step C5:

[0118] In step C5, the subtask corresponding to the third driving area is determined to be the driving cost from the endpoint to the end point shared by the second driving area and the third driving area, and the second driving area distributes the subtask corresponding to the third driving area to the third driving area, and so on, until the subtask at the end point is generated.

[0119] In one embodiment, the above step S104 may be implemented as the following steps:

[0120] When the subtasks of each driving area are completed, each driving area reports the driving cost calculation results corresponding to the subtasks to the driving area that distributes the subtasks, until the subtasks of each driving area are reported to the first driving area where the starting point is located, and the first driving area summarizes the calculation results.

[0121] Figure 4 FIG. 1 is a schematic diagram of a driving path determination device in an embodiment of the present application. Figure 4 As shown, the device comprises:

[0122] A first determination module 401 is used to determine at least one driving area of ​​the vehicle according to the starting point and the end point corresponding to the path planning task;

[0123] A division module 402, configured to divide the path planning task into subtasks corresponding to each driving area according to the driving area of ​​the vehicle;

[0124] A distribution module 403 is used to distribute the subtasks corresponding to each driving area to the corresponding driving area, so that each driving area calculates the driving costs of all paths included in the driving area;

[0125] A summary module 404 is used to summarize the travel costs of all paths included in each travel area;

[0126] The second determination module 405 determines, according to the driving costs of all the paths included in each driving area, a path with the minimum driving cost from the starting point to the end point as the optimal driving path.

[0127] In one embodiment, the first determining module includes:

[0128] A first determination submodule is used to determine a line from a starting point to an end point on an electronic map;

[0129] A second determining submodule is used to determine a rectangular frame of a preset size that can enclose the line from the starting point to the end point;

[0130] The segmentation submodule is used to segment the area within the rectangular frame according to the administrative area division rule to form at least one driving area of ​​the vehicle, and each driving area corresponds to an administrative area of ​​a preset level.

[0131] In one embodiment, the partitioning module comprises:

[0132] A third determination submodule is used to determine an adjacency relationship matrix of the vehicle in a plurality of driving intervals;

[0133] The division submodule is used to divide the subtasks according to the adjacency relationship matrix of the vehicle driving task.

[0134] In one embodiment, the third determining submodule is further used to:

[0135] The intersection points of each adjacent area boundary line and the road are taken as endpoints, and each endpoint is numbered;

[0136] An adjacency relationship matrix of the vehicle in a plurality of driving intervals is determined according to the number.

[0137] In one embodiment, the distribution module includes:

[0138] A fourth determination submodule, configured to determine all endpoints of the first driving area where the starting point is located according to the adjacency relationship matrix;

[0139] A fifth determination submodule is used to determine that the subtask corresponding to the first driving area is the driving cost from the starting point to all endpoints of the first driving area;

[0140] a sixth determining submodule, configured to determine a second driving area adjacent to the first driving area according to the adjacency relationship matrix;

[0141] The seventh determination submodule is used to determine that the subtask corresponding to the second driving area is the driving cost from the end point to the end point common to the first driving area and the second driving area, and the first driving area distributes the subtask corresponding to the second driving area to the second driving area.

[0142] In one embodiment, when there is a third driving area adjacent to the second driving area, the seventh determining submodule is further configured to:

[0143] The subtask corresponding to the third driving area is determined to be the driving cost from the endpoint to the end point shared by the second driving area and the third driving area, and the second driving area distributes the subtask corresponding to the third driving area to the third driving area, and so on, until the subtask at the end point is generated.

[0144] In one embodiment, the aggregation module is further used to:

[0145] When the subtasks of each driving area are completed, each driving area reports the driving cost calculation results corresponding to the subtasks to the driving area that distributes the subtasks, until the subtasks of each driving area are reported to the first driving area where the starting point is located, and the first driving area summarizes the calculation results.

[0146] Figure 5 FIG. 1 is a schematic diagram of the hardware structure of a driving path determination system in one embodiment of the present application. Figure 5 As shown, the driving path determination system includes:

[0147] at least one processor 520; and,

[0148] A memory 504 in communication with the at least one processor 520; wherein,

[0149] The memory 504 stores instructions that can be executed by the at least one processor 520, and the instructions are executed by the at least one processor 520 to implement the driving path determination method recorded in any of the above embodiments.

[0150] Reference Figure 5 The driving path determination system 500 may include one or more of the following components: a processing component 502, a memory 504, a power component 506, a multimedia component 508, an audio component 510, an input / output (I / O) interface 512, a sensor component 514, and a communication component 516.

[0151] The processing component 502 generally controls the overall operation of the driving path determination system 500. The processing component 502 may include one or more processors 520 to execute instructions to complete all or part of the steps of the above method. In addition, the processing component 502 may include one or more modules to facilitate the interaction between the processing component 502 and other components. For example, the processing component 502 may include a multimedia module to facilitate the interaction between the multimedia component 508 and the processing component 502.

[0152] The memory 504 is configured to store various types of data to support the operation of the driving path determination system 500. Examples of such data include instructions for any application or method operating on the driving path determination system 500, such as text, pictures, videos, etc. The memory 504 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0153] The power component 506 provides power to various components of the travel path determination system 500. The power component 506 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the travel path determination system 500.

[0154] The multimedia component 508 includes a screen that provides an output interface between the driving path determination system 500 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 508 may also include a front camera and / or a rear camera. When the driving path determination system 500 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0155] The audio component 510 is configured to output and / or input audio signals. For example, the audio component 510 includes a microphone (MIC), and when the driving path determination system 500 is in an operating mode, such as an alarm mode, a recording mode, a voice recognition mode, and a voice output mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 504 or sent via the communication component 516. In some embodiments, the audio component 510 also includes a speaker for outputting audio signals.

[0156] I / O interface 512 provides an interface between processing component 502 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0157] The sensor assembly 514 includes one or more sensors for providing various aspects of status assessment for the driving path determination system 500. For example, the sensor assembly 514 may include a sound sensor. In addition, the sensor assembly 514 may detect the on / off state of the driving path determination system 500, the relative positioning of the components, such as the display and keypad of the driving path determination system 500, and the sensor assembly 514 may also detect the operating state of the driving path determination system 500 or a component of the driving path determination system 500, the driving path determination system 500 orientation or acceleration / deceleration and the temperature change of the driving path determination system 500. The sensor assembly 514 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 514 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 514 may also include an acceleration sensor, a gyroscope sensor, etc.

[0158] The communication component 516 is configured to enable the driving path determination system 500 to provide the ability to communicate with other devices and cloud platforms in a wired or wireless manner. The driving path determination system 500 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 516 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 516 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0159] In an exemplary embodiment, the driving path determination system 500 can be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to execute the driving path determination method described in any of the above embodiments.

[0160] The present application also provides a computer-readable storage medium. When the instructions in the storage medium are executed by a processor corresponding to the driving path determination system, the driving path determination system can implement the driving path determination method recorded in any of the above embodiments.

[0161] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) that contain computer-usable program code.

[0162] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0163] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0164] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0165] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for determining a driving path, characterized in that: include: Determine at least one driving area of ​​the vehicle according to the starting point and the end point corresponding to the path planning task; Dividing the path planning task into subtasks corresponding to each driving area according to the driving area of ​​the vehicle; Distribute the subtasks corresponding to each driving area to the corresponding driving area, so that each driving area calculates the driving costs of all paths contained in the driving area; Summarize the travel costs of all paths included in each travel area; According to the travel costs of all the paths included in each travel area, the path with the smallest travel cost from the starting point to the end point is determined as the optimal travel path.

2. The method according to claim 1, characterized in that The step of determining at least one driving area of ​​the vehicle according to the starting point and the end point corresponding to the path planning task includes: Determine the line from the starting point to the end point on the electronic map; Determine a rectangular frame of a preset size that can enclose the line connecting the starting point to the end point; The area within the rectangular frame is divided according to administrative area division rules to form at least one driving area of ​​the vehicle, and each driving area corresponds to an administrative area of ​​a preset level.

3. The method according to claim 1, characterized in that According to the driving area of ​​the vehicle, the path planning task is divided into subtasks corresponding to each driving area, including: Determine an adjacency matrix of vehicles in a plurality of driving intervals; The subtasks are divided according to the adjacency relationship matrix of the vehicle driving task.

4. The method according to claim 3, characterized in that Determine the adjacency matrix of the vehicle in multiple driving intervals, including: The intersection points of each adjacent area boundary line and the road are taken as endpoints, and each endpoint is numbered; An adjacency relationship matrix of the vehicle in a plurality of driving intervals is determined according to the number.

5. The method according to claim 4, characterized in that The step of distributing the subtasks corresponding to each driving area to the corresponding driving area includes: Determine all endpoints of the first driving area where the starting point is located according to the adjacency relationship matrix; Determine the subtask corresponding to the first driving area as the driving cost from the starting point to all endpoints of the first driving area; Determine a second driving area adjacent to the first driving area according to the adjacency relationship matrix; The subtask corresponding to the second driving area is determined to be a driving cost from an end point to an end point common to the first driving area and the second driving area, and the first driving area distributes the subtask corresponding to the second driving area to the second driving area.

6. The method according to claim 5, characterized in that When there is a third driving area adjacent to the second driving area, the method further includes: The subtask corresponding to the third driving area is determined to be the driving cost from the endpoint to the end point shared by the second driving area and the third driving area, and the second driving area distributes the subtask corresponding to the third driving area to the third driving area, and so on, until the subtask at the end point is generated.

7. The method according to claim 1, characterized in that The summarization of the travel costs of all paths included in each travel area includes: When the subtasks of each driving area are completed, each driving area reports the driving cost calculation results corresponding to the subtasks to the driving area that distributes the subtasks, until the subtasks of each driving area are reported to the first driving area where the starting point is located, and the first driving area summarizes the calculation results.

8. A driving path determination device, characterized in that: include: A first determination module, configured to determine at least one driving area of ​​the vehicle according to a starting point and an end point corresponding to the path planning task; A division module, used for dividing the path planning task into subtasks corresponding to each driving area according to the driving area of ​​the vehicle; A distribution module, used to distribute the subtasks corresponding to each driving area to the corresponding driving area, so that each driving area calculates the driving costs of all paths contained in the driving area; A summary module is used to summarize the travel costs of all paths included in each travel area; The second determination module determines, according to the driving costs of all the paths included in each driving area, a path with the minimum driving cost from the starting point to the end point as the optimal driving path.

9. A driving path determination system, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to implement the driving path determination method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor corresponding to the driving path determination system, the driving path determination system can implement the driving path determination method as described in any one of claims 1 to 7.

Images