CN117270518A - Path planning method, path planning device, vehicle, equipment and computer readable storage medium - Google Patents

Abstract

The present disclosure relates to a path planning method, apparatus, vehicle, device, and computer-readable storage medium, the method comprising: road network information and vehicle track data in a preset area are acquired; determining a plurality of path points in the preset area based on the road network information; and planning the plurality of path points according to the vehicle track data, and determining at least one test path in the preset area. The method and the device for planning the path in the automatic driving simulation test based on the road network information and the vehicle track data rapidly and accurately plan the path in the preset area to support the task of the automatic driving simulation test, and can plan all possible driving paths in the preset area.

Description

Path planning method, path planning device, vehicle, equipment and computer readable storage medium

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a path planning method, apparatus, vehicle, device, and computer readable storage medium.

Background

The automatic driving simulation test is to digitize an application scene of automatic driving in a mathematical modeling mode, establish a system model which is as close to the real world as possible, and further simulate the running process of the vehicle on a pre-planned good test route, thereby carrying out test verification on the automatic driving system of the vehicle.

In the prior art, a test route in an automatic driving simulation test task is mainly planned manually according to the existing map information, and the problems of low efficiency, unreasonable route planning and the like exist.

Disclosure of Invention

In order to solve the technical problems, the present disclosure provides a path planning method, a device, a vehicle, a device and a computer readable storage medium, so as to improve the efficiency and quality of path planning in an automatic driving simulation test task.

In a first aspect, an embodiment of the present disclosure provides a path planning method, including:

road network information and vehicle track data in a preset area are acquired;

determining a plurality of path points in the preset area based on the road network information;

and planning the plurality of path points according to the vehicle track data, and determining at least one test path in the preset area.

In some embodiments, the determining, based on the road network information, a plurality of path points within the preset area includes:

determining a plurality of road network points in the preset area based on the road network information;

and removing repeated road points at the road junction to obtain a plurality of path points in the preset area.

In some embodiments, the planning the plurality of path points according to the vehicle track data, determining at least one test path in the preset area includes:

sorting the plurality of path points, and determining the starting point of the test path based on the sorting result;

determining any one of the plurality of path points except the starting point as an end point of the test path;

and planning at least one test path in the preset area according to the vehicle track data based on the starting point and the ending point.

In some embodiments, the sorting the plurality of waypoints, determining the start point of the test path based on the sorting result comprises:

determining a datum point on the preset area boundary, and calculating distances between the plurality of path points and the datum point respectively;

and determining a path point closest to the datum point as a starting point of the test path.

In some embodiments, the planning at least one test path within the preset area according to the vehicle track data based on the start point and the end point includes:

planning a plurality of paths in the preset area according to the vehicle track data based on the starting point, the ending point and the plurality of path points;

and determining at least one path with the shortest length in the paths as the test path.

In some embodiments, the method further comprises:

removing other path points in the at least one test path from the plurality of path points, the other path points being path points in the at least one test path other than the start point and the end point;

sequencing the rest path points, and re-determining a starting point and an ending point;

and planning at least one test path in the preset area based on the redetermined starting point and the redetermined ending point.

In a second aspect, an embodiment of the present disclosure provides a path planning apparatus, including:

the acquisition module is used for acquiring road network information and vehicle track data in a preset area;

the determining module is used for determining a plurality of path points in the preset area based on the road network information;

and the planning module is used for planning the plurality of path points according to the vehicle track data and determining at least one test path in the preset area.

In a third aspect, embodiments of the present disclosure provide a vehicle comprising a path planning apparatus as described above.

In a fourth aspect, an embodiment of the present disclosure provides an electronic device, including:

a memory;

a processor; and

a computer program;

wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method according to the first aspect.

In a fifth aspect, embodiments of the present disclosure provide a computer-readable storage medium having stored thereon a computer program for execution by a processor to implement the method of the first aspect.

In a sixth aspect, the disclosed embodiments also provide a computer program product comprising a computer program or instructions which, when executed by a processor, implement a path planning method as described above.

The path planning method, the device, the vehicle, the equipment and the computer readable storage medium provided by the embodiment of the disclosure can rapidly and accurately plan the path in the preset area based on the road network information and the vehicle track data to support the task of the automatic driving simulation test, can automatically plan all possible driving paths in the preset area, and have higher speed and more reasonable planning compared with the manual path planning, and improve the efficiency and quality of path planning in the automatic driving simulation test task.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.

In order to more clearly illustrate the embodiments of the present disclosure or the solutions in the prior art, the drawings that are required for the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.

Fig. 1 is a flowchart of a path planning method provided in an embodiment of the present disclosure;

fig. 2 is a schematic diagram of a preset area network according to an embodiment of the present disclosure;

FIG. 3 is a flow chart of a path planning method according to another embodiment of the present disclosure;

FIG. 4 is a flow chart of a path planning method according to another embodiment of the present disclosure;

fig. 5 is a schematic structural diagram of a path planning apparatus according to an embodiment of the present disclosure;

fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.

Detailed Description

In order that the above objects, features and advantages of the present disclosure may be more clearly understood, a further description of aspects of the present disclosure will be provided below. It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced otherwise than as described herein; it will be apparent that the embodiments in the specification are only some, but not all, embodiments of the disclosure.

The embodiments of the present disclosure provide a path planning method, which is described below with reference to specific embodiments.

Fig. 1 is a flowchart of a path planning method according to an embodiment of the present disclosure. The method can be applied to terminal equipment, and the terminal equipment can be any equipment with a data processing function, such as a smart phone, a palm computer, a tablet personal computer, a notebook computer, an integrated machine and the like. As shown in fig. 1, the path planning method includes the following specific steps:

s101, road network information and vehicle track data in a preset area are acquired.

The road network refers to a road system which is formed by various roads and mutually connected and interweaved into a net-shaped distribution in a certain area, and the road network information can reflect the conditions of the roads in the road network from various aspects, such as the trend, the distribution condition and the like of the roads. The terminal equipment firstly selects a corresponding preset area from the map according to the appointed longitude and latitude data, and acquires road network information in the preset area. Specifically, a plurality of position points corresponding to the longitude and latitude data can be determined according to the plurality of groups of longitude and latitude data, and a space polygon is established according to the plurality of position points, wherein an area surrounded by the space polygon is a preset area. The vehicle trajectory data includes at least a plurality of trajectories along which the vehicle travels, a speed of the vehicle at each trajectory point, and a traveling direction of the vehicle.

S102, determining a plurality of path points in the preset area based on the road network information.

Fig. 2 is a schematic diagram of a preset area network according to an embodiment of the present disclosure. The road network information of the preset area comprises the relevant information of all roads in the preset area, wherein the road network information of each road respectively comprises a plurality of continuous points forming the road. As shown in fig. 2, there are multiple intricate roads in the preset area, each road is composed of multiple continuous points, i.e. the preset area includes a plurality of points, part of the points meeting the preset rule are selected as path points in the preset area, and one or more test paths are formed by the path points.

S103, planning the plurality of path points according to the vehicle track data, and determining at least one test path in the preset area.

And building a navigation engine based on Dijkstra algorithm according to the road network information and the selected multiple path points. The Dijkstra algorithm was proposed by the hollander computer scientist dierstla in 1959 and is therefore also called dierstla algorithm. The shortest path algorithm from one vertex to the rest vertices solves the shortest path problem in the weighted graph. The dijkstra algorithm is mainly characterized by starting from a starting point, adopting a greedy algorithm strategy, traversing each time to the adjacent nodes of the vertex which is nearest to the starting point and is not visited until the vertex is extended to the end point. The navigation engine is used as a piece of software and service, supports multiple applications such as hybrid navigation, big data intelligent dynamic path planning, high-precision hybrid positioning based on multiple sensors, natural guiding voice broadcasting, voice control and voice intelligent searching based on artificial intelligence technology, navigation data increment updating and daily updating, and the like, and is important for the existing manual driving or automatic auxiliary driving.

The terminal equipment can acquire all paths conforming to the passing direction of the road network and the length of each path which can pass between any two path points in a preset area according to vehicle track data through a navigation engine built based on a Dijkstra algorithm, and further screen out at least one path conforming to preset conditions from all paths which can pass as a test path, wherein the preset conditions can be that the path length is shortest. For example, as shown in fig. 2, when planning a path between points 21 and 23, one possible path is from point 21 to point 22 to point 23, i.e. a possible test path is determined according to all the path points on the path.

The method comprises the steps of obtaining road network information and vehicle track data in a preset area; determining a plurality of path points in the preset area based on the road network information; and planning the plurality of path points according to the vehicle track data, determining at least one test path in the preset area, rapidly and accurately planning the path in the preset area based on road network information and the vehicle track data to support the task of the automatic driving simulation test, and planning all possible driving paths in the preset area.

Fig. 3 is a flowchart of a path planning method according to another embodiment of the present disclosure. As shown in fig. 3, the method comprises the following steps:

s301, road network information and vehicle track data in a preset area are acquired.

Specifically, the implementation process and principle of S301 and S101 are identical, and will not be described herein.

S302, determining a plurality of road network points in the preset area based on the road network information.

S303, removing repeated road points at the road junction to obtain a plurality of path points in the preset area.

The road network comprises a plurality of roads, and each road consists of a plurality of road points. At the junction of different roads, there may be two overlapped road network points, where the two road network points respectively belong to two different roads that are intersected with each other, but the positions of the two road network points are the same, and if there are multiple repeated points at the same position during path planning, the subsequent path planning may be affected, for example, two identical paths may be planned based on the two road network points that are repeated at the junction of the roads. Therefore, the duplicate road points in the same position in all the road points in the preset area are removed, namely the duplicate road points at the road junction are removed, and the rest of the road points are used as the path points in the preset area. As shown in fig. 2, at the junction of different roads, such as the positions of the points 21, 22 and 23, at least two road points respectively belonging to different roads exist at the same time, and the repeated road points are removed, so that only one point at the same position is ensured to be used as a path point.

Alternatively, a plurality of path points within the preset area may also be determined from the vehicle track data. According to the vehicle track data in the preset area, determining the speed of the vehicle at each track point, and selecting track points with zero vehicle speed in all track points. And selecting a preset number of track points in a preset radius range of each track point with zero vehicle speed for density clustering to obtain a plurality of cluster clusters in a preset area, and taking the mass center of a track point set in each cluster as a path point.

S304, sorting the plurality of path points, and determining the starting point of the test path based on the sorting result.

Specifically, determining a datum point on the boundary of the preset area, and calculating distances between the plurality of path points and the datum point respectively; and determining a path point closest to the datum point as a starting point of the test path.

A point on the boundary of the preset area is selected as a reference point, for example, a point with the smallest longitude and latitude on the boundary of the preset area (i.e. the southeast angle of the preset area) is selected as a reference point, and the actual distance between each path point and the reference point is calculated. And sorting the plurality of path points according to the actual distances from small to large, and selecting the path point with the smallest actual distance from the reference point in the plurality of path points as the starting point of the test path planning. The actual distance between the path point and the reference point is the geographic distance between the path point and the reference point, and is not the euclidean distance. It may be understood that, in the embodiment of the present disclosure, a point with the smallest longitude and latitude on the boundary of the preset area (i.e. the southeast angle of the preset area) is selected as the reference point, and a path point with the smallest actual distance from the reference point is selected as the starting point of the test path planning, which is only an example, and in actual situations, different reference points may be selected according to different specific requirements, and corresponding ranking rules may be determined.

S305, determining any one of the path points except the starting point as the end point of the test path.

S306, planning at least one test path in the preset area according to the vehicle track data based on the starting point and the ending point.

Specifically, a plurality of paths in the preset area are planned according to the vehicle track data based on the starting point, the ending point and the plurality of path points; and determining at least one path with the shortest length in the paths as the test path.

And constructing a navigation engine by using a Dijkstra algorithm based on the road network information of the preset area and a plurality of path points in the preset area. And randomly selecting any path point except the starting point from a plurality of path points as an end point of the test path planning. Based on the determined starting point and the determined end point, a navigation engine can be used for planning all trafficable paths between the starting point and the end point in a preset area. A path data set is created in the memory for storing data of path points included in the planned path. According to the running direction of the vehicle in the vehicle track data, searching the subsequent path points of the starting point in the rest path points, wherein the subsequent path points are positioned in any path network between the starting point and the end point, and in the vehicle running track, the vehicle passes through the starting point first and then passes through the subsequent path points of the path points. Inserting the data of the subsequent path points into the path data group, taking the subsequent path points as reference path points, continuously searching the subsequent path points of the reference path points, and repeating the operation until all the path points are traversed. If a plurality of subsequent path points are searched for the same reference path point, the plurality of subsequent path points are respectively stored as different path data sets, and finally a plurality of path data sets are obtained, wherein each path data set corresponds to one path between a starting point and an end point. In the paths corresponding to the path data sets, the starting point and the end point of each path are the same, but the roads in the road network of the path are different, namely the path points of the path are different, and the distance of each path may also be different. And acquiring the length of each passable path by combining the road network information, finally selecting at least one path with the shortest length as a test path, and storing the path points and the related road network information contained in the determined test path into a test path data set for use in automatic driving simulation test.

The method comprises the steps of obtaining road network information and vehicle track data in a preset area; determining a plurality of road network points in the preset area based on the road network information; removing repeated road points at the road junction to obtain a plurality of path points in the preset area; sorting the plurality of path points, and determining the starting point of the test path based on the sorting result; determining any one of the plurality of path points except the starting point as an end point of the test path; based on the starting point and the ending point, at least one test path in the preset area is planned according to the vehicle track data, the test path which meets the requirements best in the preset area can be planned quickly and accurately according to the preset effect, and a corresponding test path data set is acquired, such as the shortest path between every two path points in the preset area is planned, so that the path planning efficiency is improved greatly, and efficient data support is provided for the automatic driving simulation test task.

On the basis of the above embodiment, the method further includes: removing other path points in the at least one test path from the plurality of path points, the other path points being path points in the at least one test path other than the start point and the end point; sequencing the rest path points, and re-determining a starting point and an ending point; and planning at least one test path in the preset area based on the redetermined starting point and the redetermined ending point.

After determining at least one test path, removing the path points except the two path points of the starting point and the end point from the plurality of path points so as to avoid repeated planning of the same path. And re-ordering the rest path points, and re-determining the starting point and the end point according to the re-ordering result. Optionally, in the step, a path point closest to the reference point is determined as a first start point, another path point is randomly selected as a first end point, after at least one corresponding first test path is determined, all path points except the first start point and the end point included in one or more first test paths are removed from the plurality of path points obtained initially, and the next start point is continuously selected according to the distance between the path point and the reference point, namely, the path point closest to the reference point is determined as a second start point. If the path point that is the second closest to the reference point has been removed, then the path point that is the third closest to the reference point is continued to be selected as the second starting point, and so on, until a point that has not been removed is determined as the second starting point. And repeatedly executing the steps until all the path points in the plurality of path points are traversed, and finally obtaining a test path data set corresponding to the preset area. For example, as shown in fig. 2, if the start point is determined to be the point 21 and the end point is determined to be the point 22 in the process of one path planning, the test path is finally determined to be the path 24, the path points and the related road network information included in the path 24 are stored in the test path data set, and then the path points except the start point 21 and the end point 22 in the path points included in the path 24 are removed from the plurality of path points, and the start point and the end point are reselected to perform the corresponding path planning.

Embodiments of the present disclosure provide for removing other path points in the at least one test path from the plurality of path points, the other path points being path points in the at least one test path other than the start point and the end point; sequencing the rest path points, and re-determining a starting point and an ending point; on the basis of the redetermined starting point and the redetermined end point, at least one test path in the preset area is planned, on one hand, path points of the planned path are eliminated, repeated planning of the same path is avoided, operation resources are saved, and path planning efficiency is further improved; the other party traverses all the path points to ensure that all possible paths in the preset area can be planned, and further selects the test path which meets the requirements best, thereby ensuring the comprehensiveness and accuracy of path planning.

Fig. 4 is a flowchart of a path planning method according to another embodiment of the present disclosure. As shown in fig. 4, the method comprises the following steps:

s401, acquiring road network information in a preset area.

S402, determining a plurality of road network points in the preset area based on the road network information.

S403, removing repeated road points at the road junction to obtain a path point set in the preset area.

The road network comprises a plurality of roads, and each road consists of a plurality of road points. At the junction of different roads, there may be two overlapped road network points, where the two road network points respectively belong to two different roads that are intersected with each other, but the positions of the two road network points are the same, and if there are multiple repeated points at the same position during path planning, the subsequent path planning may be affected, for example, two identical paths may be planned based on the two road network points that are repeated at the junction of the roads. And the rest road points are taken as the path points in the preset area, and the path points form a path point set.

S404, determining a starting point and an ending point based on the path point set.

Selecting a path point which accords with a preset rule from the path point set as a starting point, and selecting any point except the starting point as an end point. Wherein, a point on the boundary of the preset area can be selected as a reference point, and the actual distance between each path point and the reference point is calculated. And sorting the plurality of path points according to the actual distances from small to large, and selecting the path point with the smallest actual distance from the reference point in the plurality of path points as the starting point of the test path planning.

S405, planning at least one test path in the preset area based on the starting point and the ending point.

And constructing a navigation engine by using a Dijkstra algorithm based on the road network information of the preset area and a plurality of path points in the preset area. And randomly selecting any path point except the starting point from a plurality of path points as an end point of the test path planning. Based on the determined starting point and the determined end point, a navigation engine can be used for planning all trafficable paths between the starting point and the end point in a preset area. And further selecting at least one path meeting preset requirements from all paths capable of passing as a test path, for example, selecting at least one path with the shortest passing distance as the test path.

S406, removing other path points in the at least one test path from a path point set, wherein the other path points are path points except the starting point and the ending point in the at least one test path.

S407, judging whether the number of the path points in the path point set is larger than a preset value. If yes, executing S404; if not, S408 is performed.

Repeating the steps S404-S406 until the number of the rest path points in the path point set is less than or equal to a preset threshold. In some embodiments, the preset value may be 2, and when the number of the path points in the path point set is not greater than two, it represents that all the path points in the path point set have been traversed, and at this time, all the test paths in the preset area have been planned, and the remaining two path points in the path point set are the start point and the end point of the test path when the last path is planned.

S408, ending.

According to the embodiment of the disclosure, the tasks of automatic driving simulation test are supported by rapidly and accurately planning the path in the preset area according to the path planning algorithm based on the road network information, compared with the manual path planning speed, the path planning is faster and more reasonable, meanwhile, the path points of the planned path are eliminated, the repeated planning of the same path is avoided, the test path which meets the requirements best in the preset area can be rapidly and accurately planned according to the preset effect, the corresponding test path data set is obtained, the rationality of path planning is ensured, and meanwhile, the efficiency and flexibility of path planning are improved.

Fig. 5 is a schematic structural diagram of a path planning apparatus according to an embodiment of the present disclosure. The path planning device may be a terminal device as described in the above embodiments, or the path planning device may be a part or component in the terminal device. The path planning apparatus provided in the embodiment of the present disclosure may execute the processing flow provided in the embodiment of the path planning method, as shown in fig. 5, where the path planning apparatus 50 includes: an acquisition module 51, a determination module 52, a planning module 53; the acquiring module 51 is configured to acquire road network information and vehicle track data in a preset area; the determining module 52 is configured to determine a plurality of path points in the preset area based on the road network information; the planning module 53 is configured to plan the plurality of path points according to the vehicle track data, and determine at least one test path in the preset area.

Optionally, the determining module 52 is further configured to determine a plurality of road network points in the preset area based on the road network information; and removing repeated road points at the road junction to obtain a plurality of path points in the preset area.

Optionally, the planning module 53 includes a start point determining unit 531, an end point determining unit 532, and a planning unit 533; the starting point determining unit 531 is configured to sort the plurality of path points, and determine a starting point of the test path based on the sorting result; an end point determination unit 532 for determining any one of the plurality of path points other than the start point as an end point of the test path; the planning unit 533 is configured to plan at least one test path in the preset area according to the vehicle track data based on the start point and the end point.

Optionally, the starting point determining unit 531 is further configured to determine a reference point on the preset region boundary, and calculate distances between the plurality of path points and the reference point respectively; and determining a path point closest to the datum point as a starting point of the test path.

Optionally, the planning unit 533 is further configured to plan a plurality of paths in the preset area according to the vehicle track data based on the start point, the end point and the plurality of path points; and determining at least one path with the shortest length in the paths as the test path.

Optionally, the planning unit 533 is further configured to remove other path points in the at least one test path from the plurality of path points, where the other path points are path points in the at least one test path except the start point and the end point; the starting point determining unit 531 is further configured to sort the remaining path points, and redetermine a starting point; the end point determination unit 532 is also configured to redetermine the start point; the planning unit 533 is further configured to plan at least one test path in the preset area based on the redetermined start point and the determined end point.

The path planning apparatus of the embodiment shown in fig. 5 may be used to implement the technical solution of the above-mentioned method embodiment, and its implementation principle and technical effects are similar, and are not described herein again.

In addition, the embodiment of the disclosure also provides a vehicle, which comprises the path planning device.

Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure. The electronic device may be a terminal device as described in the above embodiments. The electronic device provided in the embodiment of the present disclosure may execute the processing flow provided in the embodiment of the path planning method, as shown in fig. 6, the electronic device 60 includes: a memory 61, a processor 62, computer programs and a communication interface 63; wherein the computer program is stored in the memory 61 and configured to be executed by the processor 62 for performing the path planning method as described above.

The memory 61 is a non-transitory computer readable storage medium that may be used to store software programs, computer executable programs, and modules, such as program instructions/modules corresponding to the path planning method in the embodiments of the present disclosure. The processor 62 executes various functional applications of the server and data processing, i.e., implements the path planning method of the above-described method embodiment, by running software programs, instructions, and modules stored in the memory 61.

The memory 61 may include a storage program area that may store an operating system, at least one application program required for functions, and a storage data area; the storage data area may store data created according to the use of the vehicle, etc. In addition, the memory 61 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 61 may optionally include memory located remotely from processor 62, which may be connected to the terminal device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

In addition, the embodiment of the present disclosure also provides a computer-readable storage medium having stored thereon a computer program that is executed by a processor to implement the path planning method described in the above embodiment.

Furthermore, the disclosed embodiments also provide a computer program product comprising a computer program or instructions which, when executed by a processor, implements a path planning method as described above.

Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including, but not limited to, an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The foregoing is merely a specific embodiment of the disclosure to enable one skilled in the art to understand or practice the disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown and described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. A method of path planning, the method comprising:

road network information and vehicle track data in a preset area are acquired;

determining a plurality of path points in the preset area based on the road network information;

and planning the plurality of path points according to the vehicle track data, and determining at least one test path in the preset area.

2. The method of claim 1, wherein the determining a plurality of waypoints within the preset area based on the road network information comprises:

determining a plurality of road network points in the preset area based on the road network information;

and removing repeated road points at the road junction to obtain a plurality of path points in the preset area.

3. The method of claim 1, wherein planning the plurality of waypoints according to the vehicle trajectory data, determining at least one test path within the preset area, comprises:

sorting the plurality of path points, and determining the starting point of the test path based on the sorting result;

determining any one of the plurality of path points except the starting point as an end point of the test path;

and planning at least one test path in the preset area according to the vehicle track data based on the starting point and the ending point.

4. A method according to claim 3, wherein said sorting the plurality of path points, determining the start of the test path based on the sorting result, comprises:

determining a datum point on the preset area boundary, and calculating distances between the plurality of path points and the datum point respectively;

and determining a path point closest to the datum point as a starting point of the test path.

5. The method of claim 3, the planning at least one test path within the preset zone from the vehicle trajectory data based on the start point and the end point comprising:

planning a plurality of paths in the preset area according to the vehicle track data based on the starting point, the ending point and the plurality of path points;

and determining at least one path with the shortest length in the paths as the test path.

6. A method according to claim 3, characterized in that the method further comprises:

removing other path points in the at least one test path from the plurality of path points, the other path points being path points in the at least one test path other than the start point and the end point;

sequencing the rest path points, and re-determining a starting point and an ending point;

and planning at least one test path in the preset area based on the redetermined starting point and the redetermined ending point.

7. A path planning apparatus, the apparatus comprising:

the acquisition module is used for acquiring road network information and vehicle track data in a preset area;

the determining module is used for determining a plurality of path points in the preset area based on the road network information;

and the planning module is used for planning the plurality of path points according to the vehicle track data and determining at least one test path in the preset area.

8. A vehicle comprising a path planning apparatus according to claim 7.

9. An electronic device, comprising:

a memory;

a processor; and

a computer program;

wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method of any one of claims 1-6.

10. A computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the method according to any of claims 1-6.