Scheduling decision-making method and device, equipment, storage medium and product

Abstract

The invention discloses a scheduling decision method and device, equipment, a storage medium and a product. The method comprises the steps that under the condition that it is detected that a vehicle enters a coverage area of a first base station, route planning is carried out on the vehicle in the coverage area through preset lane lattice point information, a first route is obtained, and the lane lattice point information comprises lane information represented by an array matrix; and under the condition that the vehicle travels to an edge lattice in the coverage area according to the first route, vehicle information of the vehicle is sent to a second base station, so that the second base station performs route planning on the vehicle entering the area of the second base station by using the vehicle information. According to the embodiment of the invention, the driving path of the vehicle can be planned through the base station, and the problem of safety accidents caused by untimely decision making of the vehicle is avoided.

Description

Technical Field

[0001] The present application belongs to the field of vehicle autonomous driving technology, and in particular, relates to a scheduling decision method, device, equipment, storage medium and product. Background Art

[0002] To realize intelligent driving, the existing technology has proposed a vehicle-to-everything (V2X) vehicle-road collaborative mechanism with single-vehicle intelligence as the core. This mechanism obtains data on traffic lights and other vehicles during driving by means of vehicle networking, and realizes assisted driving through the data obtained.

[0003] However, when there are too many smart cars on the road, each car is a decision-making core. When making decisions, driving conflicts and decision weights will arise. Since each smart car needs to process a large amount of data from multiple sources, including the location, speed, driving intention, etc. of other vehicles. This data needs to be processed quickly to generate real-time driving decisions. However, each car needs to transmit information to each other, and the process of transmitting information takes time, which will inevitably delay the decision-making time and easily cause safety hazards during driving. Summary of the invention

[0004] The embodiments of the present application provide a scheduling decision method, apparatus, device, storage medium and product to solve the problem of potential safety hazards that may easily arise during the process of vehicle adopting V2X autonomous driving.

[0005] In a first aspect, an embodiment of the present application provides a scheduling decision method, which is applied to a first base station, and the method includes:

[0006] When a vehicle is detected to have entered a coverage area of ​​the first base station, a route is planned for the vehicle within the coverage area using preset lane grid point information to obtain a first route, wherein the lane grid point information includes lane information represented by an array matrix;

[0007] When the vehicle travels to an edge cell in the coverage area according to the first route, vehicle information of the vehicle is sent to the second base station, so that the second base station plans a route for the vehicle entering the area of ​​the second base station using the vehicle information.

[0008] In a second aspect, an embodiment of the present application provides a scheduling decision device, the device comprising:

[0009] a planning module, configured to, when detecting that a vehicle enters a coverage area of ​​the first base station, plan a route for the vehicle within the coverage area using preset lane grid point information to obtain a first route, wherein the lane grid point information includes lane information within the coverage area represented by an array matrix;

[0010] The sending module is used to send the vehicle information of the vehicle to the second base station when the vehicle travels to the edge grid in the coverage area according to the first route, so that the second base station can use the vehicle information to plan the route of the vehicle entering the area of ​​the second base station.

[0011] In a third aspect, an embodiment of the present application provides a terminal device, the device comprising: a processor and a memory storing computer program instructions;

[0012] When the processor executes the computer program instructions, the scheduling decision method of the first aspect is implemented.

[0013] In a fourth aspect, an embodiment of the present application provides a computer storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the scheduling decision method of the first aspect is implemented.

[0014] In a fifth aspect, an embodiment of the present application provides a computer program product. When instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the scheduling decision method of the first aspect.

[0015] The scheduling decision method provided in the embodiment of the present application, when the first base station detects that a vehicle enters its coverage area, uses the base station to plan the path of the vehicle according to the lane grid information, and when the vehicle enters the coverage area of ​​the next second base station, notifies the second base station to plan the path of the vehicle. During the driving of the vehicle, the decision object of the route planning can be optimized from the vehicle in the prior art to the communication base station, and the base station is used to uniformly make route scheduling decisions for the vehicles in the cell, so as to prevent too many vehicles during driving and too long time for vehicles to transmit information to each other, which leads to untimely vehicle decision-making and the occurrence of safety accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0017] Figure 1 It is a flowchart of a scheduling decision method provided in an embodiment of the present application;

[0018] Figure 2 It is a schematic diagram of a navigation planning path of a vehicle provided in an embodiment of the present application;

[0019] Figure 3 is a path planning flow chart provided in an embodiment of the present application;

[0020] Figure 4 is a schematic diagram of dividing a curved lane provided in an embodiment of the present application;

[0021] Figure 5 is a schematic diagram of a special grid provided in an embodiment of the present application;

[0022] Figure 6 is a schematic diagram of the numbering of grid points provided in an embodiment of the present application;

[0023] Figure 7 is an overall flow chart of the scheduling decision method provided in an embodiment of the present application;

[0024] Figure 8 is a structural diagram of a scheduling decision-making device provided in an embodiment of the present application;

[0025] Fig. 9 It is a schematic diagram of the structure of the terminal device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0027] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0028] In order to solve the problems of the prior art, the embodiments of the present application provide a scheduling decision method, apparatus, device, storage medium and product.

[0029] The following first introduces the scheduling decision method provided in the embodiment of the present application.

[0030] Figure 1 FIG. 1 is a flow chart showing a scheduling decision method provided by an embodiment of the present application. Figure 1 As shown, the method includes:

[0031] Step 101, when a vehicle is detected to enter a coverage area of ​​the first base station, a route is planned for the vehicle within the coverage area using preset lane grid point information to obtain a first route, wherein the lane grid point information includes lane information represented by an array matrix;

[0032] In this embodiment, the first base station is equipped with a packaged computing module component, which can send and receive information at high speed. The computing module component encapsulates the lane grid point information within the coverage area of ​​the corresponding base station, and the lane grid point information is lane information represented by an array matrix. The lane grid point information divides the lanes in the coverage area into multiple grid points, and each grid point is represented by an array matrix. The computing module component is also used to plan routes for vehicles in the coverage area of ​​the base station in conjunction with the base station.

[0033] Specifically, in one embodiment, using preset lane grid point information, route planning is performed on the vehicle in the coverage area to obtain a first route, including:

[0034] Determining, by using the vehicle grid point information and the navigation planning path of the vehicle, cell information of a second cell passed by the vehicle among the plurality of first cells, and a driving priority of the vehicle in the second cell;

[0035] The driving priority is used to plan a route for the vehicle to obtain a first route for the vehicle in the second community.

[0036] In this embodiment, the coverage area includes a plurality of first cells. The above-mentioned navigation planning path refers to the planned route between the starting point and the destination of the vehicle. The navigation planning path is set by the user and can be set through the vehicle computer.

[0037] As an example, see Figure 2 , Figure 2 The figure is a schematic diagram of the navigation planning path of the vehicle. The navigation planning path passes through base stations A, B, C and D, the starting point is located in base station A, and the destination is located in base station D.

[0038] For cell information, when a vehicle enters the coverage area of ​​the first base station, the first base station will send lane grid point information to the vehicle. The vehicle only needs to combine the lane grid point information with the navigation planning path to determine the cell information of the second cell that the vehicle will pass through among multiple first cells. The vehicle then feeds back the cell information to the first base station, so that the base station obtains the cell information.

[0039] Regarding driving priority, when the vehicle feeds back the cell information to the first base station, the vehicle information will also be fed back to the first base station. The first base station then determines the driving priority of the vehicle based on the information field and vehicle type in the vehicle information.

[0040] Furthermore, the vehicle priority is allocated according to the following table. Vehicles of the same level are assigned priority according to the time they enter the community. If multiple priorities are met at the same time, the highest priority will prevail. When the priority changes, the first route will be replanned:

[0041] Priority Vehicle Type Information Fields 1 Special vehicles Vehicle Information 2 There is a security anomaly in the vehicle information Vehicle Information 3 There is a risk of missing the intersection Self-assessment of priorities 4 Normal driving vehicle Self-assessment of priorities

[0042] Table 1, Vehicle priority table

[0043] The cell information also includes the starting and ending points of the vehicle in the second cell, and whether the destination of the vehicle is in the second cell. In addition, in addition to the cell information and vehicle information, the vehicle also feeds back the vehicle speed to the first base station.

[0044] After the first base station obtains the driving priority and the cell information, it can use the driving priority and the cell information to plan the route of the vehicle to obtain the first route.

[0045] Step 102, when the vehicle travels to an edge cell in the coverage area according to the first route, the vehicle information of the vehicle is sent to the second base station, so that the second base station plans a route for the vehicle entering the area of ​​the second base station using the vehicle information.

[0046] In this embodiment, the edge grid refers to the grid point at the edge of the first cell divided in the lane grid point information, that is, the grid point where the end point of the start and end points is located. When the vehicle is located at the edge grid, it means that the vehicle is about to enter the second base station from the first base station. At this time, the first base station needs to send the vehicle information to the second base station so that the second base station can establish a connection with the vehicle and continue to plan a path for the vehicle until the vehicle reaches the destination in the navigation planning path.

[0047] It should be noted that in step 101, after obtaining the vehicle information, the first base station will share the vehicle information through the bearer network and the core network to all base stations that the vehicle will pass through, so as to realize information exchange between base stations. Among them, all base stations that the vehicle will pass through are determined by the vehicle navigation planning path. When entering the second base station, the first base station sends the vehicle information to the second base station, so that the second base station can determine the vehicle that is about to arrive in advance by comparing the vehicle information.

[0048] The scheduling decision method provided in the embodiment of the present application, when the first base station detects that a vehicle enters its coverage area, uses the base station to plan the path of the vehicle according to the lane grid information, and when the vehicle enters the coverage area of ​​the next second base station, notifies the second base station to plan the path of the vehicle. During the driving of the vehicle, the decision object of the route planning can be optimized from the vehicle in the prior art to the communication base station, and the base station is used to uniformly make route scheduling decisions for the vehicles in the cell, so as to prevent too many vehicles during driving and too long time for vehicles to transmit information to each other, which leads to untimely vehicle decision-making and the occurrence of safety accidents.

[0049] In one embodiment of the present application, the step of planning a route for the vehicle by using the driving priority to obtain a first route for the vehicle in the second cell includes:

[0050] When the driving priority of the vehicle in the second cell is the highest level and the cell information indicates that the driving destination of the vehicle is not located in the second cell, obtaining the first route by using a search algorithm;

[0051] When the driving priority of the vehicle in the second cell is the highest level and the cell information indicates that the driving destination of the vehicle is located in the second cell, the first route is obtained by using the A-star algorithm.

[0052] In this example, see Figure 3 , Figure 3 The flowchart for vehicle path planning is shown in FIG.

[0053] When the driving priority of the vehicle is the highest level, the vehicle needs to be granted the highest driving authority so that the vehicle can quickly pass through the second community. When the driving destination of the vehicle is not located in the second community, it means that the vehicle is only passing through the second community, not the destination community. Therefore, a search algorithm is used to plan the path of the vehicle to obtain the first route. It should be noted that the first route is a route consisting of a starting point in the second community.

[0054] The search algorithm is a method that uses the high performance of computers to purposefully exhaust part or all of the possible situations in a problem solution space to find the solution to the problem. It finds the optimal solution or feasible solution to the problem by systematically traversing or searching for possible candidate solutions. Vehicle path planning refers to planning the optimal path from the starting point to the end point for the vehicle under a given road network and other constraints. This process needs to consider many factors, such as road conditions, traffic rules, vehicle performance, driving time, etc. Therefore, the vehicle path planning problem is essentially a complex optimization problem, which requires selecting the best path from many possible paths. Therefore, a search algorithm can be used to plan the driving path of the vehicle in the second community. Among them, the search algorithm generally refers to a class of algorithms that can traverse the problem space and find the optimal solution, such as breadth-first search (BFS), depth-first search (DFS) or its variants.

[0055] When the vehicle's destination is within the second cell, it means that the second cell is the destination cell, and the second cell is the end point. At this time, the A-star algorithm is used for path planning to obtain the first route. Among them, the A-star algorithm is the A* search algorithm. In this case, the A-star algorithm (A* algorithm) is used to plan the first route. The A-star algorithm is an algorithm that finds a path with the lowest cost from the starting point to the end point in a path with multiple nodes on a graph plane. It combines the advantages of the best-first search and the Dijkstra algorithm, and introduces a heuristic function to evaluate the estimated cost from any node to the target node, thereby significantly improving the search efficiency. When the vehicle's destination is within the current cell, the A-star algorithm can be used to find a shortest or optimal path from the current location to the destination more quickly.

[0056] In this embodiment, according to the driving priority and destination location of the vehicle, a search algorithm or an A-star algorithm is flexibly selected to plan the driving route of the vehicle in the second cell, thereby ensuring the efficiency and accuracy of the scheduling decision.

[0057] In an embodiment of the present application, the step of planning a route for the vehicle by using the driving priority and the cell information to obtain a first route of the vehicle in the second cell includes:

[0058] When the driving priority of the vehicle in the second cell is not the highest level, obtaining a current frame time of the vehicle, where the current frame time is a ratio between a grid point length in lane grid point information and a speed of the vehicle;

[0059] When the cell information indicates that the destination of the vehicle is not located in the second cell and the vehicle is not located in an edge cell of the second cell, the grid points passed by other vehicles having a higher driving priority than the vehicle in the second cell within the current frame time are set as obstacles;

[0060] The first route is obtained by performing calculations based on the obstacles and the artificial potential field method.

[0061] In this embodiment, when the driving priority of a vehicle is not the highest level, it is necessary to give priority to the driving route of the vehicle with the highest driving level to avoid affecting the driving of the vehicle with the highest driving level.

[0062] See also Figure 3 First, the first base station needs to calculate the current frame time of the vehicle. This time is determined based on the ratio between the grid length in the lane grid information and the current speed of the vehicle. The current frame time can be understood as the time required for the vehicle to pass through a grid point at the current speed.

[0063] Next, the first base station checks the cell information to determine whether the vehicle's destination is located in the second cell. If the destination is not in the second cell and the vehicle is not currently located in an edge cell in the second cell, the first base station needs to further consider the impact of other vehicles in the cell.

[0064] In this case, the first base station sets the grid points that other vehicles with higher driving priority than the current vehicle in the second cell may pass through within the current frame time as obstacles. This is because these high-priority vehicles may have occupied these grid points before the current vehicle attempts to pass through them, so the current vehicle needs to avoid these potential conflict points.

[0065] Once the obstacles are identified, the first base station can calculate the first route using the Artificial Potential Field Method (APF). The APF is a path planning method that simulates a virtual force field in which the target point generates gravity and the obstacles generate repulsion. The movement trend of the vehicle in this force field is determined by the combined force of gravity and repulsion.

[0066] In this scenario, the first base station will regard the lane grid points in the second cell as points in the potential field, and calculate the potential field value (i.e. the combined force of gravity and repulsion) at each grid point based on the location of the obstacle and the current location of the vehicle. The system will then select the path with the smallest potential field value as the first route, because the combined force on this path is the smallest, which means that the vehicle can more easily travel along this path without having to overcome too much resistance.

[0067] In summary, this description shows that when the vehicle driving priority is not the highest level, the artificial potential field method is used to plan the vehicle's driving route in the second cell by considering the vehicle's current state, cell information, lane grid information, and the influence of other vehicles in the cell. This can effectively avoid potential conflicts and congestion and improve the overall efficiency and safety of the transportation system.

[0068] In an embodiment of the present application, after the route of the vehicle is planned in the coverage area using the preset lane grid point information to obtain a first route, when the vehicle travels to an edge grid in the coverage area according to the first route, before sending the vehicle information of the vehicle to the second base station, the method further includes:

[0069] When the vehicle travels from the third cell to the fourth cell in the coverage area according to the first route, a measurement control message of the fourth cell is sent to the vehicle, wherein the measurement control message is used to establish a connection between the vehicle and the fourth cell, and the third cell and the fourth cell are different cells in the coverage area.

[0070] In this embodiment, since the coverage area of ​​the first base station includes multiple cells, when the vehicle travels in the coverage area according to the planned first route, it may cross from the current cell (such as the third cell) to another adjacent cell (such as the fourth cell). In order to ensure that the vehicle can receive services smoothly and continuously, the first base station needs to take some necessary measures before the vehicle enters the new cell.

[0071] Specifically, when the first base station detects that the vehicle is about to travel from the third cell to the fourth cell (which can usually be predicted by the vehicle's current position, speed and information of the first route), the first base station sends a measurement control message for the fourth cell to the vehicle.

[0072] The measurement control message is used to instruct the vehicle to measure the signal quality of the neighboring cell so that the first base station can more accurately determine when to perform cell switching. By receiving this measurement control message, the vehicle can start measuring and evaluating the new cell to ensure that it can smoothly switch to the new cell and maintain communication connection during or after the crossing.

[0073] If the next cell predicted by the vehicle is still within the coverage of the current first base station, the first base station will directly send an RRC (Radio Resource Control) reconfiguration message with a Mobility Control Info information element. This message contains all the configuration information required for intra-cell switching, allowing the vehicle to quickly establish a connection with the new fourth cell, thereby reducing the interruption time and signal loss risk during the switching process. Among them, the configuration information includes a series of parameters and instructions related to the new cell, such as the cell's identity, operating frequency, channel configuration, etc.

[0074] In this embodiment, by timely sending the measurement control message related to the new cell to the vehicle, it is ensured that the vehicle can establish a stable connection with the new cell, thereby ensuring the continuity of communication and service quality.

[0075] In one embodiment of the present application, when a vehicle is detected to enter a coverage area of ​​the first base station, the method further includes: planning a route for the vehicle within the coverage area using preset lane grid point information, and obtaining the first route.

[0076] Dividing the lanes in the coverage area into grids of a preset size;

[0077] The grids are numbered according to the bifurcation intersections, fan-out intersections, column numbers, and level numbers of the lane to obtain the lane grid point information.

[0078] In this embodiment, considering the size of the vehicle, the size of the grid can be set to 3.5m, so that a vehicle occupies 1 to 2 grids during driving and 2 to 4 grids when changing lanes. Since the lanes include straight lanes and curved lanes, the straight lanes can be directly divided according to the preset size. For curved lanes, please refer to Figure 4 , Figure 4 This is a schematic diagram of the division of curved lanes. The curve is divided layer by layer from the inner lane to the outer side. A bending algorithm is used to make it fit the actual level of the lane. The part with an area less than 50% of the grid is ignored, and the part greater than or equal to 50% is merged into the adjacent grid of the same lane.

[0079] Also, see Figure 5 , for some special intersections such as Figure 4 AB is linked, and the area overlaps, such as Figure 5 All overlapping squares involved in C are considered to be the same square.

[0080] After dividing the lane into squares, Figure 6For example, starting from the fork in the road, extending to the edge exits in three directions, number each square in the form of an array of lane forks, fan-out intersections, column numbers, and levels, such as A(3,0,0,0), B(3,0,0,1), C(3,2,0,0), D(3,2,1,0). Among them, the fork in the road refers to the lanes that branch off from the same fork in the road, for example, Figure 5 The lanes in the three directions belong to the same fork. A fan-out intersection refers to different lane directions. For example, the lane where AB is located is a fan-out intersection, the lane where C is located is a fan-out intersection, and the lane in the other direction belongs to a fan-out intersection. The number of columns and levels is numbered starting from the first square after the fan-out of the fork. For example, for the fan-out intersection where AB is located, A and B are in the same column, but in different rows, that is, different levels. For the fan-out intersection where C and D are located, C and D belong to the same level, but belong to different columns.

[0081] All lanes and grids in the cell are traversed in the above encoding manner to obtain lane grid point information.

[0082] In this embodiment, by encoding vehicles and accurately dividing and numbering lanes in the coverage area, accurate management and scheduling of vehicles are achieved.

[0083] In another embodiment of the present application, the overall process of the scheduling decision method in the above embodiment is introduced.

[0084] See also Figure 7 , Figure 7 The overall flow chart of the scheduling decision method.

[0085] When the vehicle leaves base station A and goes to base station B (i.e., the first base station), the vehicle information is sent to base station B, and the base station B information is sent to vehicle A at the same time, wherein the base station B information includes the lane grid point information of base station B. Vehicle A uses the base station B information to establish a connection with base station B, and sends the start and end points and driving priority confirmed by the lane grid point information to base station B.

[0086] Base station B uses the driving priority to determine that the vehicle is the highest level, and if there is no route planned, it will plan the route for the vehicle, obtain the route decision (i.e., the first route), and send the route decision to vehicle A. After planning the first route, adjust the route planning of other vehicles, obtain the route decisions of other vehicles, and send the route decisions to other vehicles. When it is detected that the vehicle enters the edge grid, base station B deletes the relevant information of vehicle A and clears the memory. At the same time, it sends the vehicle information to the second base station so that the second base station can continue to plan the route for the vehicle.

[0087] In the case where the vehicle is not of the highest priority, the highest priority vehicle is planned (ie, the first route is obtained according to the obstacle and artificial potential field method in the above embodiment).

[0088] like Figure 6 As shown, the embodiment of the present application further provides a scheduling decision device 600, the device comprising:

[0089] A planning module 601 is used to, when detecting that a vehicle enters a coverage area of ​​the first base station, plan a route for the vehicle within the coverage area using preset lane grid point information to obtain a first route, wherein the lane grid point information includes lane information within the coverage area represented by an array matrix;

[0090] The sending module 602 is used to send the vehicle information of the vehicle to the second base station when the vehicle travels to the edge grid in the coverage area according to the first route, so that the second base station can use the vehicle information to plan the route of the vehicle entering the area of ​​the second base station.

[0091] Optionally, the planning module 601 includes:

[0092] A first planning submodule, configured to determine, by using the lane grid point information and the navigation planning path of the vehicle, cell information of a second cell passed by the vehicle among the plurality of first cells, and a driving priority of the vehicle in the second cell;

[0093] The second planning submodule is used to plan the route of the vehicle by using the driving priority and the cell information to obtain a first route of the vehicle in the second cell.

[0094] Optionally, the second planning submodule includes:

[0095] A first planning unit is configured to obtain the first route by using a search algorithm when the driving priority of the vehicle in the second cell is the highest level and the cell information indicates that the driving destination of the vehicle is not located in the second cell;

[0096] The second planning unit is used to obtain the first route by using the A-star algorithm when the driving priority of the vehicle in the second cell is the highest level and the cell information indicates that the driving destination of the vehicle is located in the second cell.

[0097] Optionally, the second planning submodule includes:

[0098] an acquisition unit, configured to acquire, when the driving priority of the vehicle in the second cell is not the highest level, a current frame time of the vehicle, the current frame time being a ratio between a grid point length in lane grid point information and a speed of the vehicle;

[0099] A setting unit, configured to set, when the cell information indicates that the destination of the vehicle is not located in the second cell and the vehicle is not located in an edge cell of the second cell, grid points passed by other vehicles having a higher driving priority than the vehicle in the second cell within the current frame time as obstacles;

[0100] A calculation unit is used to perform calculations based on the obstacles and the artificial potential field method to obtain the first route.

[0101] Optionally, the scheduling decision device 600 is specifically configured to:

[0102] When the vehicle travels from the third cell to the fourth cell in the coverage area according to the first route, a measurement control message of the fourth cell is sent to the vehicle, wherein the measurement control message is used to establish a connection between the vehicle and the fourth cell, and the third cell and the fourth cell are different cells in the coverage area.

[0103] Optionally, the scheduling decision device 600 further includes:

[0104] A division module, used to divide the lanes in the coverage area into grids of a preset size;

[0105] The numbering module is used to number the squares according to the bifurcation intersection, fan-out intersection, column number and level number of the lane to obtain the lane grid point information.

[0106] Figure 7 A schematic diagram of the hardware structure of a terminal device provided in an embodiment of the present application is shown.

[0107] The terminal device may include a processor 701 and a memory 702 storing computer program instructions.

[0108] Specifically, the processor 701 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0109] The memory 702 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 702 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 702 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 702 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 702 is a non-volatile solid-state memory.

[0110] In certain embodiments, the memory 702 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage media device, an optical storage media device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0111] The processor 701 implements any one of the scheduling decision methods in the above embodiments by reading and executing computer program instructions stored in the memory 702 .

[0112] In one example, the terminal device may further include a communication interface 707 and a bus 710. Figure 7 As shown, the processor 701, the memory 702, and the communication interface 707 are connected via a bus 710 and communicate with each other.

[0113] The communication interface 707 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0114] Bus 710 includes hardware, software or both, and the parts of online data flow billing equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 710 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.

[0115] In addition, in combination with the scheduling decision method in the above embodiment, the embodiment of the present application can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any one of the scheduling decision methods in the above embodiment is implemented.

[0116] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0117] The functional blocks shown in the above block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0118] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0119] Aspects of the present disclosure are described above 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 disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box 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, or other programmable scheduling decision device to produce a machine so that these instructions executed by the processor of the computer or other programmable scheduling decision device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0120] The above are only specific implementation methods of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A scheduling decision method, characterized in that: Applied to a first base station, the method includes: When a vehicle is detected to have entered a coverage area of ​​the first base station, a route is planned for the vehicle within the coverage area using preset lane grid point information to obtain a first route, wherein the lane grid point information includes lane information represented by an array matrix; When the vehicle travels to an edge cell in the coverage area according to the first route, vehicle information of the vehicle is sent to the second base station, so that the second base station plans a route for the vehicle entering the area of ​​the second base station using the vehicle information.

2. The scheduling decision method according to claim 1, characterized in that: The coverage area includes a plurality of first cells; The method of using the preset lane grid point information to plan a route for the vehicle within the coverage area to obtain a first route includes: Determining, by using the lane grid point information and the navigation planning path of the vehicle, cell information of a second cell passed by the vehicle among the plurality of first cells, and a driving priority of the vehicle in the second cell; The driving priority and the cell information are used to plan a route for the vehicle to obtain a first route for the vehicle in the second cell.

3. The scheduling decision method according to claim 2, characterized in that: The step of planning a route for the vehicle by using the driving priority and the cell information to obtain a first route for the vehicle in the second cell includes: When the driving priority of the vehicle in the second cell is the highest level and the cell information indicates that the driving destination of the vehicle is not located in the second cell, obtaining the first route by using a search algorithm; When the driving priority of the vehicle in the second cell is the highest level and the cell information indicates that the driving destination of the vehicle is located in the second cell, the first route is obtained by using the A-star algorithm.

4. The scheduling decision method according to claim 2, characterized in that: The step of planning a route for the vehicle by using the driving priority and the cell information to obtain a first route for the vehicle in the second cell includes: When the driving priority of the vehicle in the second cell is not the highest level, obtaining a current frame time of the vehicle, where the current frame time is a ratio between a grid point length in lane grid point information and a speed of the vehicle; When the cell information indicates that the destination of the vehicle is not located in the second cell and the vehicle is not located in an edge cell of the second cell, the grid points passed by other vehicles having a higher driving priority than the vehicle in the second cell within the current frame time are set as obstacles; The first route is obtained by performing calculations based on the obstacles and the artificial potential field method.

5. The scheduling decision method according to claim 1, characterized in that: After the route of the vehicle is planned in the coverage area by using the preset lane grid point information to obtain a first route, before the vehicle information of the vehicle is sent to the second base station when the vehicle travels to an edge grid in the coverage area according to the first route, the method further includes: When the vehicle travels from the third cell to the fourth cell in the coverage area according to the first route, a measurement control message of the fourth cell is sent to the vehicle, wherein the measurement control message is used to establish a connection between the vehicle and the fourth cell, and the third cell and the fourth cell are different cells in the coverage area.

6. The scheduling decision method according to claim 1, characterized in that: In the case where it is detected that the vehicle enters the coverage area of ​​the first base station, before the first route is obtained by planning a route for the vehicle within the coverage area using preset lane grid point information, the method further includes: Dividing the lanes in the coverage area into grids of a preset size; The grids are numbered according to the bifurcation intersections, fan-out intersections, column numbers, and level numbers of the lane to obtain the lane grid point information.

7. A scheduling decision device, characterized in that: The device comprises: a planning module, configured to, when detecting that a vehicle enters a coverage area of ​​the first base station, plan a route for the vehicle within the coverage area using preset lane grid point information to obtain a first route, wherein the lane grid point information includes lane information within the coverage area represented by an array matrix; The sending module is used to send the vehicle information of the vehicle to the second base station when the vehicle travels to the edge grid in the coverage area according to the first route, so that the second base station can use the vehicle information to plan the route of the vehicle entering the area of ​​the second base station.

8. A terminal device, characterized in that: The device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the scheduling decision method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the scheduling decision method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer product includes a computer program, and when the computer program is executed by a processor, the scheduling decision method according to any one of claims 1 to 6 is implemented.

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