Vehicle path planning method, device, electronic device, and storage medium

Abstract

The present application discloses a vehicle path planning method, device, electronic device, and storage medium, the method comprising: obtaining a reference trajectory of a vehicle and local high-precision map data corresponding to the vehicle, the reference trajectory including a terminal trajectory point of the reference trajectory; determining a target lane set for the vehicle according to the terminal trajectory point of the reference trajectory and the local high-precision map data corresponding to the vehicle; generating a set of alternative paths for the vehicle according to the target lane set of the vehicle and a preset map algorithm; and determining a driving path for the vehicle based on the set of alternative paths. The vehicle path planning method of the embodiment of the present application is based on the reference trajectory of the vehicle in combination with local high-precision map data, and generates a set of alternative paths that conform to the actual scenario through a preset map algorithm, providing a precondition for later scenario decision-making and avoiding the problem that some sections of the road cannot reach the destination due to the vehicle's lane change behavior.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving technology, and in particular to a vehicle path planning method, device, electronic device, and storage medium. Background Art

[0002] The Advanced Driver Assistant System (ADAS) uses various on-board sensors and decision-making planning and control algorithms to enable the vehicle to change lanes, merge, overtake, follow other vehicles, and perform other actions.

[0003] Due to the complexity of actual road conditions, the constraints of traffic regulations, and the requirements of real-time decision-making, planning and control, a global search is usually not performed to obtain a global path during the decision-making and planning stage of the path. This will result in some sections of the road being unable to reach the destination after the vehicle changes lanes. Summary of the invention

[0004] The embodiments of the present application provide a vehicle path planning method, device, electronic device, and storage medium to generate a set of alternative paths that conform to actual scenarios and provide prerequisites for subsequent scenario decisions.

[0005] The present application embodiment adopts the following technical solutions:

[0006] In a first aspect, an embodiment of the present application provides a vehicle path planning method, wherein the method comprises:

[0007] Acquire a reference trajectory of a vehicle and local high-precision map data corresponding to the vehicle, wherein the reference trajectory includes an end trajectory point of the reference trajectory;

[0008] Determining a target lane set for the vehicle according to the end trajectory point of the reference trajectory and the local high-precision map data corresponding to the vehicle;

[0009] Generating a set of candidate paths for the vehicle according to a set of target lanes for the vehicle and a preset graph algorithm;

[0010] A driving path of the vehicle is determined based on the set of candidate paths.

[0011] Optionally, determining the target lane set of the vehicle according to the end trajectory point of the reference trajectory and the local high-precision map data corresponding to the vehicle includes:

[0012] Obtaining a destination of the vehicle;

[0013] Determine whether the end track point of the reference track is the same as the destination point of the vehicle to obtain a first determination result;

[0014] A target lane set for the vehicle is determined according to the first determination result and the local high-precision map data corresponding to the vehicle.

[0015] Optionally, determining the target lane set of the vehicle according to the first determination result and the local high-precision map data corresponding to the vehicle includes:

[0016] If the end track point of the reference track is the same as the destination of the vehicle, the lane where the end track point is located is determined according to the local high-precision map data corresponding to the vehicle, and the lane where the end track point is located is stored as the target lane in the target lane set of the vehicle;

[0017] If the end trajectory point of the reference trajectory is different from the destination of the vehicle, determine whether the end trajectory point is located on the lane connection line based on the local high-precision map data corresponding to the vehicle, obtain a second determination result, and determine the target lane set of the vehicle based on the second determination result and the local high-precision map data.

[0018] Optionally, determining the target lane set of the vehicle according to the second determination result and the local high-precision map data includes:

[0019] If the end track point is located on a lane connection line, an associated lane is determined according to the lane connection line where the end track point is located, a corresponding lane of the same type is obtained from the local high-precision map data according to the lane type of the associated lane, and the associated lane and the corresponding lane of the same type are stored as target lanes in the target lane set;

[0020] If the termination trajectory point is not located on the lane connection line, the corresponding lane of the same type is obtained from the local high-precision map data according to the lane type of the lane where the termination trajectory point is located, and the lane where the termination trajectory point is located and the corresponding lane of the same type are stored as target lanes in the target lane set.

[0021] Optionally, generating a set of candidate paths for the vehicle according to the target lane set for the vehicle and a preset graph algorithm comprises:

[0022] Constructing the directed graph and the corresponding matrix based on the local high-precision map data;

[0023] The target lanes are sequentially taken from the target lane set of the vehicle, and a set of candidate paths of the vehicle is generated by using a graph search algorithm based on the directed graph and the corresponding matrix.

[0024] Optionally, constructing the directed graph and the corresponding matrix based on the local high-precision map data includes:

[0025] Determine a lane set and a lane connection line set based on the local high-precision map data;

[0026] Constructing a vertex set of the directed graph according to the lane set, and constructing an edge set of the directed graph according to the lane connection line set, to obtain a constructed directed graph;

[0027] A matrix of a preset size is constructed based on the constructed directed graph, where the preset size is the size of the vertex set of the directed graph.

[0028] Optionally, determining the driving path of the vehicle based on the set of candidate paths includes:

[0029] Filtering the candidate path set using a preset filtering rule to obtain a filtered candidate path set, wherein the preset filtering rule includes a loop path filtering rule;

[0030] A driving path of the vehicle is determined based on the filtered set of candidate paths.

[0031] In a second aspect, an embodiment of the present application further provides a path planning device for a vehicle, wherein the device comprises:

[0032] An acquisition unit, configured to acquire a reference trajectory of a vehicle and local high-precision map data corresponding to the vehicle, wherein the reference trajectory includes a terminal trajectory point of the reference trajectory;

[0033] A first determining unit, configured to determine a target lane set of the vehicle according to a terminal trajectory point of the reference trajectory and local high-precision map data corresponding to the vehicle;

[0034] A generating unit, configured to generate a set of candidate paths for the vehicle according to a set of target lanes for the vehicle and a preset graph algorithm;

[0035] The second determining unit is used to determine the driving path of the vehicle based on the set of candidate paths.

[0036] In a third aspect, an embodiment of the present application further provides an electronic device, including:

[0037] Processor; and

[0038] A memory arranged to store computer executable instructions which, when executed, cause the processor to perform any of the methods described above.

[0039] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, which stores one or more programs. When the one or more programs are executed by an electronic device including multiple application programs, the electronic device executes any of the aforementioned methods.

[0040] At least one of the above technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects: the path planning method for the vehicle in the embodiments of the present application first obtains the reference trajectory of the vehicle and the local high-precision map data corresponding to the vehicle, the reference trajectory includes the terminal trajectory point of the reference trajectory; then, the target lane set of the vehicle is determined according to the terminal trajectory point of the reference trajectory and the local high-precision map data corresponding to the vehicle; then, the alternative path set of the vehicle is generated according to the target lane set of the vehicle and the preset map algorithm; finally, the driving path of the vehicle is determined based on the alternative path set. The path planning method for the vehicle in the embodiments of the present application is based on the reference trajectory of the vehicle combined with the local high-precision map data, and generates an alternative path set that conforms to the actual scenario through the preset map algorithm, which provides a precondition for the later scenario decision and avoids the problem that some sections of the road cannot reach the destination due to the vehicle's lane change behavior. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0042] Figure 1 A schematic diagram of a process flow of a vehicle path planning method in an embodiment of the present application;

[0043] Figure 2 This is a schematic diagram of the structure of a path planning device for a vehicle in an embodiment of the present application;

[0044] Figure 3 It is a schematic diagram of the structure of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0046] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0047] The present application embodiment provides a vehicle path planning method, such as Figure 1 As shown, a flow chart of a vehicle path planning method in an embodiment of the present application is provided, and the method at least includes the following steps S110 to S140:

[0048] Step S110, obtaining a reference trajectory of the vehicle and local high-precision map data corresponding to the vehicle, wherein the reference trajectory includes an end trajectory point of the reference trajectory.

[0049] When performing vehicle path planning in the embodiment of the present application, it is necessary to first obtain a reference trajectory corresponding to the vehicle's current position. The reference trajectory here can be understood as a local reference trajectory that travels a certain distance forward from the vehicle's current position. Therefore, the reference trajectory includes the vehicle's current position point and the terminal trajectory point of the reference trajectory. The reference trajectory can be specifically provided by an external trajectory planning module.

[0050] In addition, it is also necessary to obtain local high-precision map data corresponding to the vehicle. Here, local high-precision map data within a certain range can be obtained based on the vehicle's current positioning information. The local high-precision map data can provide rich lane structured information, providing important support for lane-level path planning.

[0051] Step S120: determining a target lane set for the vehicle based on the end trajectory point of the reference trajectory and the local high-precision map data corresponding to the vehicle.

[0052] After obtaining the local high-precision map data, all possible target lanes for the vehicle at the terminal trajectory point of the reference trajectory can be determined based on the local high-precision map data. These target lanes constitute a target lane set, which serves as the basis for subsequent path planning.

[0053] Step S130, generating a set of candidate paths for the vehicle according to the target lane set of the vehicle and a preset graph algorithm.

[0054] After determining the target lane set, the embodiment of the present application can use the lane where the vehicle is currently located as the starting point and each target lane in the target lane set as the end point, and use the preset graph algorithm to generate corresponding multiple connected paths as the vehicle's alternative path set. The preset graph algorithm here can be flexibly selected by those skilled in the art according to actual needs, for example, it can be a depth first search (DFS) algorithm, a breadth first search (BFS) algorithm, a greedy best first search (GBFS) algorithm or an A* algorithm, etc., which are not specifically limited here.

[0055] Step S140: determining a driving path of the vehicle based on the set of candidate paths.

[0056] The alternative path set of the embodiment of the present application provides all feasible driving paths for the vehicle, and provides a precondition for later scene decision-making. For example, when there is an obstacle or a traffic accident in a lane in the original reference trajectory of the vehicle, the lane needs to change lanes. At this time, the driving path of the vehicle after changing lanes can be selected based on all the paths provided in the alternative path set, so that the vehicle can arrive at the destination smoothly and in time.

[0057] The vehicle path planning method of the embodiment of the present application is based on the vehicle's reference trajectory combined with local high-precision map data, and generates a set of alternative paths that conform to the actual scenario through a preset graph algorithm, providing a prerequisite for subsequent scenario decisions and avoiding the problem of the vehicle changing lanes and causing some sections of the road to be unable to reach the destination.

[0058] In one embodiment of the present application, determining the target lane set of the vehicle based on the terminal trajectory point of the reference trajectory and the local high-precision map data corresponding to the vehicle includes: obtaining the destination of the vehicle; determining whether the terminal trajectory point of the reference trajectory is the same as the destination of the vehicle to obtain a first determination result; and determining the target lane set of the vehicle based on the first determination result and the local high-precision map data corresponding to the vehicle.

[0059] The embodiment of the present application initializes the dynamic target lane set S-lane in advance, and the initial length of the target lane set is 0, which serves as the basis for the subsequent update of the target lane information. When dynamically updating the target lane information in the target lane set S-lane of the vehicle, the destination that the vehicle is ultimately going to reach can be determined first, and then the end track point Pn of the currently acquired reference track Traj (the length of the reference track Traj is n) is compared with the destination that the vehicle is ultimately going to reach, and it is determined whether the end track point of the reference track is the destination that the vehicle is ultimately going to reach, and then the corresponding target lane set update strategy is adopted according to different determination results.

[0060] In one embodiment of the present application, determining the target lane set of the vehicle based on the first determination result and the local high-precision map data corresponding to the vehicle includes: if the terminal trajectory point of the reference trajectory is the same as the destination of the vehicle, determining the lane where the terminal trajectory point is located based on the local high-precision map data corresponding to the vehicle, and storing the lane where the terminal trajectory point is located as the target lane in the target lane set of the vehicle; if the terminal trajectory point of the reference trajectory is different from the destination of the vehicle, determining whether the terminal trajectory point is located on a lane connecting line based on the local high-precision map data corresponding to the vehicle, obtaining a second determination result, and determining the target lane set of the vehicle based on the second determination result and the local high-precision map data.

[0061] Based on the above embodiment, it can be determined whether the end point Pn of the current reference trajectory is the final destination of the vehicle. Therefore, the target lane set of the vehicle can be further determined in two cases. Case (1) is that the end point Pn of the reference trajectory is the final destination of the vehicle, indicating that the reference trajectory is the last segment of the vehicle. Therefore, it can be determined that the end point Pn of the reference trajectory of the vehicle is the final location of the lane. Then, the lane Lane0 where the end point Pn is located is the final lane of the vehicle. Therefore, the lane can be directly stored as the target lane in the target lane set S-lane of the vehicle.

[0062] Case (2) is that the end trajectory point Pn of the reference trajectory is not the final destination of the vehicle, that is, a certain position point in the middle of the entire driving path. In this case, it is possible to further determine whether the end trajectory point Pn is located on the lane or on the lane connection line, because when determining the target lane set, it is necessary to determine all lanes that can ensure that the vehicle reaches the destination. When the end trajectory point Pn is not the final destination, the end trajectory point Pn is located on the lane and on the lane connection line. The associated other lanes are different, so different target lane set update strategies can be adopted based on this difference.

[0063] The lane connecting line mentioned above can be understood as a line connecting any two lanes, and is generally set for areas without lane lines at traffic intersections.

[0064] In one embodiment of the present application, determining the target lane set of the vehicle based on the second determination result and the local high-precision map data includes: if the termination trajectory point is located on a lane connecting line, determining the associated lane based on the lane connecting line where the termination trajectory point is located, obtaining the corresponding lane of the same type from the local high-precision map data based on the lane type of the associated lane, and storing the associated lane and the corresponding lane of the same type as target lanes in the target lane set; if the termination trajectory point is not located on the lane connecting line, obtaining the corresponding lane of the same type from the local high-precision map data based on the lane type of the lane where the termination trajectory point is located, and storing the lane where the termination trajectory point is located and the corresponding lane of the same type as target lanes in the target lane set.

[0065] For the case (2) of the above embodiment, it can be further divided into two cases to determine the target lane set of the vehicle. Case (2-1) is that the end trajectory point Pn is located on the lane connection line, indicating that the vehicle may currently be driving to the traffic intersection area. Although there is no lane line information, two or more connected lanes can be determined based on the lane connection line where the vehicle is located. Here, the driving direction of the vehicle can be further determined in combination with the reference trajectory of the vehicle, so as to determine the lane that the vehicle is going to enter as the associated lane corresponding to the lane connection line. Then, the lane type of the associated lane is determined, such as a straight lane, a left turn lane, a right turn lane, or a straight + turn lane, etc. According to the lane type of the associated lane, the lane LaneN of the same type as the associated lane in the same road section is searched in the local high-precision map data, and they are stored together as target lanes in the target lane set S-lane.

[0066] For example, assuming that the lane connection line where the end trajectory point Pn is located connects lane 01 and lane 02, combined with the vehicle's driving direction, it can be determined that the vehicle is going to exit from lane 01, so lane 02 can be used as an associated lane. Assuming that the lane type of lane 02 is a straight lane, then all straight lanes in the section where lane 02 is located, such as lane 03 and lane 04, can ensure that the vehicle reaches the destination. Therefore, lane 02, lane 03 and lane 04 can all be stored as target lanes in the target lane set S-lane.

[0067] Case (2-2) is that the end trajectory point Pn is not located on the lane connection line, that is, it is located on the lane. Then, based on the local high-precision map data, the lane Lane0 where the end trajectory point Pn is located can be determined. Then, according to the lane type of the lane Lane0 where the end trajectory point Pn is located, the local high-precision map data is searched for the lane LaneN of the same type as Lane0 in the same road section, and they are stored together as target lanes in the target lane set S-lane.

[0068] For example, assuming that the lane where the end trajectory point Pn is located is lane 01, and the lane type is a through lane, then all through lanes in the section where lane 01 is located, such as lane 03 and lane 04, can ensure that the vehicle reaches the destination. Therefore, lane 01, lane 03 and lane 04 can all be stored as target lanes in the target lane set S-lane.

[0069] In one embodiment of the present application, generating the set of alternative paths for the vehicle based on the target lane set of the vehicle and a preset graph algorithm includes: constructing the directed graph and the corresponding matrix based on the local high-precision map data; taking out the target lanes from the target lane set of the vehicle in turn, and generating the set of alternative paths for the vehicle based on the directed graph and the corresponding matrix using a graph search algorithm.

[0070] When generating a set of alternative paths for a vehicle, the embodiment of the present application can first use local high-precision map data to construct a directed graph G and a corresponding matrix M. The directed graph and matrix describe the connection relationship between all lanes within the area corresponding to the local high-precision map, which can greatly improve the efficiency of path planning.

[0071] Each target lane in the target lane set S-lane is a lane that the vehicle may reach, so each target lane can be planned separately. Specifically, the target lanes can be taken out from the target lane set S-lane of the vehicle in turn as the end point of the path planning, and the current lane Lane-ego where the vehicle is located can be taken as the starting point of the path planning. Then, based on the above-constructed directed graph and the corresponding matrix, a graph search algorithm such as DFS is used to traverse the directed graph G and the corresponding matrix M, thereby generating multiple alternative paths, thereby forming the vehicle's alternative path set Routs.

[0072] In one embodiment of the present application, constructing the directed graph and the corresponding matrix based on the local high-precision map data includes: determining a lane set and a lane connection line set based on the local high-precision map data; constructing a vertex set of the directed graph according to the lane set, and constructing an edge set of the directed graph according to the lane connection line set to obtain a constructed directed graph; constructing a matrix of a preset size based on the constructed directed graph, wherein the preset size is the size of the vertex set of the directed graph.

[0073] When constructing a directed graph G and a corresponding matrix M, the embodiment of the present application can first extract a lane set and a lane connection line set from the local high-precision map data, and then construct a vertex set Vs of the directed graph G based on the lane set, and construct an edge set Es of the directed graph G based on the lane connection line set, wherein Vs can specifically be composed of a lane ID set, and Es can specifically be composed of a lane connection line length set.

[0074] Afterwards, an N*N matrix M is constructed based on the directed graph G, where N is the Vs length of the directed graph G, M(i,j) belongs to Es, and its value is (-1, Es(i,j)), where Es(i,j) represents the length of the edge connecting nodes i and j, -1 means no connection, and the boundary line type of adjacent lanes a and b is a dotted line, then M(a, b) = 0.

[0075] In one embodiment of the present application, determining the driving path of the vehicle based on the alternative path set includes: filtering the alternative path set using preset filtering rules to obtain a filtered alternative path set, the preset filtering rules including a loop path filtering rule; determining the driving path of the vehicle based on the filtered alternative path set.

[0076] There may be paths in the set of alternative paths that do not conform to the actual driving scenario, so these unqualified paths can be filtered out using preset filtering rules. For example, there may be loop paths among all connected paths calculated based on the directed graph and matrix, that is, a path that starts from the starting position and returns to the starting position. Obviously, this path does not conform to the actual driving scenario of the vehicle, so the loop path can be deleted and the remaining paths can be used as alternative paths to provide prerequisites for the vehicle's later scenario decisions.

[0077] The present application also provides a vehicle path planning device 200, such as Figure 2 As shown, a schematic diagram of the structure of a vehicle path planning device in an embodiment of the present application is provided, wherein the device 200 includes: an acquisition unit 210, a first determination unit 220, a generation unit 230, and a second determination unit 240, wherein:

[0078] An acquisition unit 210 is used to acquire a reference trajectory of a vehicle and local high-precision map data corresponding to the vehicle, wherein the reference trajectory includes a terminal trajectory point of the reference trajectory;

[0079] A first determining unit 220, configured to determine a target lane set of the vehicle according to the end trajectory point of the reference trajectory and the local high-precision map data corresponding to the vehicle;

[0080] A generating unit 230, configured to generate a set of candidate paths for the vehicle according to a set of target lanes for the vehicle and a preset graph algorithm;

[0081] The second determining unit 240 is configured to determine a driving path of the vehicle based on the set of candidate paths.

[0082] In one embodiment of the present application, the first determination unit 220 is specifically used to: obtain the destination of the vehicle; determine whether the end trajectory point of the reference trajectory is the same as the destination of the vehicle to obtain a first determination result; and determine the target lane set of the vehicle based on the first determination result and the local high-precision map data corresponding to the vehicle.

[0083] In one embodiment of the present application, the first determination unit 220 is specifically used to: if the terminal trajectory point of the reference trajectory is the same as the destination of the vehicle, determine the lane where the terminal trajectory point is located according to the local high-precision map data corresponding to the vehicle, and store the lane where the terminal trajectory point is located as the target lane in the target lane set of the vehicle; if the terminal trajectory point of the reference trajectory is different from the destination of the vehicle, determine whether the terminal trajectory point is located on the lane connecting line according to the local high-precision map data corresponding to the vehicle, obtain a second determination result, and determine the target lane set of the vehicle according to the second determination result and the local high-precision map data.

[0084] In one embodiment of the present application, the first determination unit 220 is specifically used to: if the termination trajectory point is located on a lane connection line, determine the associated lane according to the lane connection line where the termination trajectory point is located, obtain the corresponding lane of the same type from the local high-precision map data according to the lane type of the associated lane, and store the associated lane and the corresponding lane of the same type as target lanes in the target lane set; if the termination trajectory point is not located on a lane connection line, obtain the corresponding lane of the same type from the local high-precision map data according to the lane type of the lane where the termination trajectory point is located, and store the lane where the termination trajectory point is located and the corresponding lane of the same type as target lanes in the target lane set.

[0085] In one embodiment of the present application, the generation unit 230 is specifically used to: construct the directed graph and the corresponding matrix based on the local high-precision map data; sequentially extract the target lanes from the target lane set of the vehicle, and based on the directed graph and the corresponding matrix, generate a set of alternative paths for the vehicle using a graph search algorithm.

[0086] In one embodiment of the present application, the generation unit 230 is specifically used to: determine a lane set and a lane connection line set based on the local high-precision map data; construct a vertex set of the directed graph according to the lane set, and construct an edge set of the directed graph according to the lane connection line set to obtain a constructed directed graph; construct a matrix of a preset size based on the constructed directed graph, and the preset size is the size of the vertex set of the directed graph.

[0087] In one embodiment of the present application, the second determination unit 240 is specifically used to: filter the alternative path set using preset filtering rules to obtain a filtered alternative path set, wherein the preset filtering rules include loop path filtering rules; and determine the driving path of the vehicle based on the filtered alternative path set.

[0088] It can be understood that the above-mentioned vehicle path planning device can implement the various steps of the vehicle path planning method provided in the aforementioned embodiment. The relevant explanations about the vehicle path planning method are applicable to the vehicle path planning device and will not be repeated here.

[0089] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. Figure 3 At the hardware level, the electronic device includes a processor, and optionally also includes an internal bus, a network interface, and a memory. The memory may include a memory, such as a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. Of course, the electronic device may also include hardware required for other services.

[0090] The processor, network interface and memory can be interconnected through an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0091] The memory is used to store the program. Specifically, the program may include a program code, and the program code includes a computer operation instruction. The memory may include a memory and a non-volatile memory, and provides instructions and data to the processor.

[0092] The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it, forming a path planning device for the vehicle at the logical level. The processor executes the program stored in the memory and is specifically used to perform the following operations:

[0093] Acquire a reference trajectory of a vehicle and local high-precision map data corresponding to the vehicle, wherein the reference trajectory includes an end trajectory point of the reference trajectory;

[0094] Determining a target lane set for the vehicle according to the end trajectory point of the reference trajectory and the local high-precision map data corresponding to the vehicle;

[0095] Generating a set of candidate paths for the vehicle according to a set of target lanes for the vehicle and a preset graph algorithm;

[0096] A driving path of the vehicle is determined based on the set of candidate paths.

[0097] The above application Figure 1 The method performed by the vehicle path planning device disclosed in the illustrated embodiment can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0098] The electronic device may also perform Figure 1 A method for executing a path planning device of a vehicle in the vehicle, and realizing the path planning device of the vehicle in Figure 1 The functions of the illustrated embodiment will not be described in detail in the embodiments of the present application.

[0099] The present application also provides a computer-readable storage medium, which stores one or more programs, wherein the one or more programs include instructions, which, when executed by an electronic device including multiple application programs, enable the electronic device to execute Figure 1 The method performed by the vehicle path planning device in the illustrated embodiment is specifically used to perform:

[0100] Acquire a reference trajectory of a vehicle and local high-precision map data corresponding to the vehicle, wherein the reference trajectory includes an end trajectory point of the reference trajectory;

[0101] Determining a target lane set for the vehicle according to the end trajectory point of the reference trajectory and the local high-precision map data corresponding to the vehicle;

[0102] Generating a set of candidate paths for the vehicle according to a set of target lanes for the vehicle and a preset graph algorithm;

[0103] A driving path of the vehicle is determined based on the set of candidate paths.

[0104] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0105] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks 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 produce 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.

[0106] 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.

[0107] 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 The steps for the functions specified in one or more boxes.

[0108] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0109] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0110] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0111] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity 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, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0112] 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, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0113] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A vehicle path planning method, wherein: The method comprises: Acquire a reference trajectory of a vehicle and local high-precision map data corresponding to the vehicle, wherein the reference trajectory includes an end trajectory point of the reference trajectory; Determining a target lane set for the vehicle according to the end trajectory point of the reference trajectory and the local high-precision map data corresponding to the vehicle; Generating a set of candidate paths for the vehicle according to a set of target lanes for the vehicle and a preset graph algorithm; Determining a driving path of the vehicle based on the set of candidate paths; Determining the target lane set of the vehicle according to the end trajectory point of the reference trajectory and the local high-precision map data corresponding to the vehicle includes: Obtaining a destination of the vehicle; Determine whether the end track point of the reference track is the same as the destination point of the vehicle to obtain a first determination result; Determining a target lane set for the vehicle according to the first determination result and local high-precision map data corresponding to the vehicle; Determining the target lane set of the vehicle according to the first determination result and the local high-precision map data corresponding to the vehicle includes: If the end track point of the reference track is the same as the destination of the vehicle, the lane where the end track point is located is determined according to the local high-precision map data corresponding to the vehicle, and the lane where the end track point is located is stored as the target lane in the target lane set of the vehicle; If the terminal trajectory point of the reference trajectory is different from the destination location of the vehicle, determine whether the terminal trajectory point is located on the lane connection line based on the local high-precision map data corresponding to the vehicle, obtain a second determination result, and determine the target lane set of the vehicle based on the second determination result and the local high-precision map data.

2. The method of claim 1, wherein: Determining the target lane set of the vehicle according to the second determination result and the local high-precision map data includes: If the end track point is located on a lane connection line, an associated lane is determined according to the lane connection line where the end track point is located, a corresponding lane of the same type is obtained from the local high-precision map data according to the lane type of the associated lane, and the associated lane and the corresponding lane of the same type are stored as target lanes in the target lane set; If the termination trajectory point is not located on the lane connection line, the corresponding lane of the same type is obtained from the local high-precision map data according to the lane type of the lane where the termination trajectory point is located, and the lane where the termination trajectory point is located and the corresponding lane of the same type are stored as target lanes in the target lane set.

3. The method of claim 1, wherein: The step of generating a set of candidate paths for the vehicle according to the target lane set for the vehicle and a preset graph algorithm includes: Constructing a directed graph and a corresponding matrix based on the local high-precision map data; The target lanes are sequentially taken from the target lane set of the vehicle, and a set of candidate paths of the vehicle is generated by using a graph search algorithm based on the directed graph and the corresponding matrix.

4. The method of claim 3, wherein: The step of constructing the directed graph and the corresponding matrix based on the local high-precision map data includes: Determine a lane set and a lane connection line set based on the local high-precision map data; Constructing a vertex set of the directed graph according to the lane set, and constructing an edge set of the directed graph according to the lane connection line set, to obtain a constructed directed graph; A matrix of a preset size is constructed based on the constructed directed graph, where the preset size is the size of the vertex set of the directed graph.

5. The method of claim 1, wherein: The determining the driving path of the vehicle based on the set of candidate paths comprises: Filtering the candidate path set using a preset filtering rule to obtain a filtered candidate path set, wherein the preset filtering rule includes a loop path filtering rule; A driving path of the vehicle is determined based on the filtered set of candidate paths.

6. A vehicle path planning device, wherein: The device comprises: An acquisition unit, configured to acquire a reference trajectory of a vehicle and local high-precision map data corresponding to the vehicle, wherein the reference trajectory includes a terminal trajectory point of the reference trajectory; A first determining unit, configured to determine a target lane set of the vehicle according to a terminal trajectory point of the reference trajectory and local high-precision map data corresponding to the vehicle; A generating unit, configured to generate a set of candidate paths for the vehicle according to a set of target lanes for the vehicle and a preset graph algorithm; A second determining unit, configured to determine a driving path of the vehicle based on the set of candidate paths; The first determining unit is specifically configured to: Obtaining a destination of the vehicle; Determine whether the end track point of the reference track is the same as the destination point of the vehicle to obtain a first determination result; Determining a target lane set for the vehicle according to the first determination result and local high-precision map data corresponding to the vehicle; The first determining unit is specifically configured to: If the end track point of the reference track is the same as the destination of the vehicle, the lane where the end track point is located is determined according to the local high-precision map data corresponding to the vehicle, and the lane where the end track point is located is stored as the target lane in the target lane set of the vehicle; If the terminal trajectory point of the reference trajectory is different from the destination location of the vehicle, determine whether the terminal trajectory point is located on the lane connection line based on the local high-precision map data corresponding to the vehicle, obtain a second determination result, and determine the target lane set of the vehicle based on the second determination result and the local high-precision map data.

7. An electronic device comprising: processor; as well as A memory arranged to store computer executable instructions, which when executed cause the processor to perform the method of any one of claims 1 to 5.

8. A computer-readable storage medium storing one or more programs, which, when executed by an electronic device including a plurality of application programs, causes the electronic device to execute any one of the methods of claims 1 to 5.

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