Path planning method and device and storage medium

Abstract

The invention discloses a path planning method and device and a storage medium, and belongs to the technical field of vehicle control. The method comprises the following steps: acquiring environment information in a first preset range around a vehicle, wherein the environment information in the first preset range comprises a starting point and an ending point of each road section, speed limit information, lane line information, signal lamp information, road condition information and the position of an obstacle; acquiring a starting point and an ending point of the travel of the vehicle; generating an initial path based on the position of the obstacle and the starting point and the ending point of the travel, wherein the initial path is a passable path with the shortest path length; crossing and mutating road sections included in the initial path to obtain a preset number of to-be-selected paths; calculating a priority coefficient of the to-be-selected path based on the environment information; and determining a to-be-driven path based on the priority coefficient. Path planning is carried out under the consideration of multiple targets, so that the accuracy and safety of path planning are improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of vehicle control technology, and in particular to a path planning method, device, and storage medium. Background Art

[0002] To improve driving safety and intelligence, more and more vehicles are incorporating path planning capabilities. Related technologies typically plan paths based on the length of the route the vehicle needs to travel. However, in complex lane environments, considering only the path length is one-sided and lacks sufficient response to unexpected situations. Therefore, the challenge of comprehensively considering multiple factors to improve the accuracy and safety of path planning remains unresolved. Summary of the Invention

[0003] The present invention provides a path planning method, device, and storage medium that can be used to improve the accuracy and safety of path planning. The technical solution is as follows:

[0004] In one aspect, an embodiment of the present application provides a path planning method, the method comprising:

[0005] Acquiring environmental information within a first preset range around the vehicle, the environmental information within the first preset range including the start and end points of each road section, speed limit information, lane information, traffic light information, road condition information, and the location of obstacles;

[0006] Obtaining the starting point and end point of the vehicle's trip;

[0007] generating an initial path based on the location of the obstacle, the starting point and the end point of the trip, wherein the initial path is a passable path with the shortest path length;

[0008] Crossing and mutating the road segments included in the initial path to obtain a preset number of paths to be selected;

[0009] Calculating a priority coefficient of the path to be selected based on the environmental information;

[0010] A path to be traveled is determined based on the priority coefficient.

[0011] In another aspect, a path planning device is provided, the device comprising:

[0012] a first acquisition module, configured to acquire environmental information within a first preset range around the vehicle, the environmental information within the first preset range including the start and end points of each road section, speed limit information, lane information, traffic light information, road condition information, and the location of obstacles;

[0013] A second acquisition module is used to obtain the starting point and end point of the vehicle's journey;

[0014] a generating module, configured to generate an initial path based on the location of the obstacle, the starting point and the end point of the trip, wherein the initial path is a passable path with the shortest path length;

[0015] A crossover and mutation module, configured to crossover and mutate the road segments included in the initial path to obtain a preset number of paths to be selected;

[0016] A calculation module, configured to calculate the priority coefficient of the path to be selected based on the environmental information;

[0017] A determination module is used to determine a path to be traveled based on the priority coefficient.

[0018] On the other hand, a non-temporary computer-readable storage medium is also provided, characterized in that a computer program is stored in the computer-readable storage medium, and the computer program is loaded and executed by a processor to implement any of the path planning methods described above.

[0019] On the other hand, a computer program product is provided, which includes computer instructions, and when the computer instructions are executed by a processor, the steps of any of the above-mentioned path planning methods are implemented.

[0020] The technical solution provided by this application brings at least the following beneficial effects:

[0021] The present application obtains environmental information within a first preset range around the vehicle and the starting and ending points of the vehicle's journey, and generates an initial path based on the location of obstacles, the starting and ending points of the journey, wherein the initial path is a passable path with the shortest path length, which is convenient for providing a preliminary basis for multi-objective path planning; then the road sections included in the initial path are crossed and mutated to obtain a preset number of paths to be selected; the priority coefficients of the paths to be selected are calculated based on the environmental information and the paths to be traveled are determined based on the priority coefficients, so as to realize path planning under multi-objective considerations, thereby improving the accuracy and safety of path planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0023] Figure 1 This is a schematic diagram of an implementation environment provided by an embodiment of the present application;

[0024] Figure 2This is a flow chart of a path planning method provided in an embodiment of the present application;

[0025] Figure 3 It is a structural diagram of a path planning device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0027] This application embodiment provides a path planning method, please refer to Figure 1 , which shows a schematic diagram of the implementation environment of the method provided in the embodiment of the present application. The implementation environment may include: an autonomous driving domain controller 11, a camera 12, a video recognition device 13, a lidar or millimeter-wave radar 14, an ECU (Electronic Control Unit) 15, and a center console display 16.

[0028] Optionally, the lidar or millimeter-wave radar 14 is used to collect the locations of obstacles within a first preset range around the vehicle and upload them to the autonomous driving domain controller 11. The camera 12 is used to collect video images within the first preset range around the vehicle and upload them to the video recognition device 13. The video recognition device 13 is used to analyze the video images collected by the camera 12 and upload them to the autonomous driving domain controller 11, so that the autonomous driving domain controller 11 can determine the type of each obstacle based on its location.

[0029] For example, ECU 15 reads the vehicle's driving mode and transmits it to autonomous driving domain controller 11. Display screen 16 on the center console receives the start and end points of a trip set by the driver, transmits them to autonomous driving domain controller 11, and displays the route to be traveled. Autonomous driving domain controller 11, camera 12, video recognition device 13, lidar or millimeter-wave radar 14, ECU 15, and center console display screen 16 establish a communication connection via a wired or wireless network.

[0030] Based on the above Figure 1 In the implementation environment shown, the present application embodiment provides a path planning method such as Figure 2 As shown, taking the method applied to an autonomous driving domain controller as an example, the method includes steps 201 to 206.

[0031] In step 201, the autonomous driving domain controller obtains environmental information within a first preset range around the vehicle. The environmental information within the first preset range includes the starting and ending points of each road section, speed limit information, lane line information, traffic light information, road condition information, and the location of obstacles.

[0032] Optionally, the environmental information within the first preset range includes the starting point and end point of each road section, speed limit information, lane line information, traffic light information, road condition information and the location of obstacles, wherein the first preset range can be set based on experience.

[0033] In one possible implementation, the autonomous driving domain controller obtains environmental information within a first preset range around the vehicle, including: obtaining the start and end points of each road section within the first preset range, speed limit information, lane information, traffic light information, and road condition information through the vehicle's onboard navigation device; collecting the location of obstacles through lidar or millimeter-wave radar; and determining the type of obstacles through a combination of cameras and video recognition equipment. Obstacles include, but are not limited to, other vehicles, pedestrians, and objects that impede the vehicle's travel.

[0034] In step 202, the autonomous driving domain controller obtains the starting point and the end point of the vehicle's trip.

[0035] For example, after obtaining environmental information within a first preset range around the vehicle, the autonomous driving domain controller can read the starting and ending points of the vehicle's trip from the vehicle's center console or the in-vehicle voice recognition device, wherein the people in the vehicle can set the starting and ending points of the vehicle's trip by clicking on the location on the map on the center console's display screen, entering the starting and ending points through the display screen, and issuing voice commands to set the starting and ending points.

[0036] In step 203, the autonomous driving domain controller generates an initial path based on the location of the obstacle, the starting point and the end point of the journey. The initial path is a passable path with the shortest path length.

[0037] Optionally, after determining the environmental information within the first preset range and the starting point and end point of the vehicle's trip, the autonomous driving domain controller generates an initial path based on the location of the obstacle, the starting point and end point of the trip, wherein the initial path is a passable path with the shortest path length.

[0038] In one possible implementation, the autonomous driving domain controller generates an initial path based on the location of the obstacle and the starting and ending points of the journey, including: discretizing the collected environmental information within a first preset range around the vehicle and the starting and ending points of the vehicle's journey into a grid map; determining the traversable road sections based on the location of the obstacle; marking the traversable road sections as edges in the grid map; calculating the length of each edge; gradually exploring each path to the end point starting from the starting point of the vehicle's journey through the Dijkstra algorithm, and calculating the length of the edges contained in each path; and selecting the path with the shortest path length as the initial path.

[0039] In step 204, the autonomous driving domain controller crosses and mutates the road sections included in the initial path to obtain a preset number of paths to be selected.

[0040] For example, in addition to the traversable and shortest path, the initial path may also include other paths that avoid obstacles through random sampling to obtain a population of initial paths. Optionally, after obtaining the population of initial paths, the autonomous driving domain controller uses NSGA-II (a multi-objective evolutionary algorithm) to perform crossover and mutation on the road segments included in the initial paths to obtain a preset number of paths to be selected.

[0041] Optionally, crossover and mutation are performed on the road segments included in the initial path, including: the autonomous driving domain controller reorganizes the road segments by simulating binary crossover to generate child paths; randomly adjusts the road segments included in the child paths; and iterates the child paths using the same method until a preset number of iterations is reached, outputting a preset number of paths to be selected. The preset number and the preset number of iterations can be set based on experience.

[0042] In step 205, the autonomous driving domain controller calculates the priority coefficient of the path to be selected based on the environmental information.

[0043] In one possible implementation, after obtaining a preset number of paths to be selected, the autonomous driving domain controller calculates priority coefficients for the paths to be selected based on environmental information. This includes: calculating the minimum path length, minimum travel time, and driving safety coefficient for the paths to be selected based on the environmental information; and calculating the priority coefficient for the paths to be selected based on the minimum path length, minimum travel time, and driving safety coefficient.

[0044] Exemplarily, the minimum path length, minimum driving time and driving safety factor of the path to be selected are calculated based on the environmental information, including: calculating the minimum section length of each section based on the starting point and end point of each section; calculating the minimum driving time of each section based on the speed limit information, road condition information and minimum section length of each section; evaluating the driving safety factor of each section based on the lane line information, speed limit information, traffic light information and road condition information of each section; calculating the minimum path length, minimum driving time and driving safety factor of the path to be selected based on the minimum driving time of each section, the driving safety factor of each section and the minimum section length of each section.

[0045] In one possible implementation, the shortest section length between the starting point and the end point of each section is calculated as the minimum section length of each section; the maximum speed limit of each section is calculated based on the speed limit information and road condition information of each section, and then the minimum section length of each section is divided by the corresponding maximum speed limit of each section to serve as the minimum driving time of each section; based on the lane line information, speed limit information, traffic light information and road condition information of each section, the driving safety factor of each section is evaluated according to a preset driving safety factor evaluation table.

[0046] Optionally, the method for calculating the maximum speed limit based on the speed limit information and the road condition information includes, but is not limited to, determining a first maximum speed limit based on the speed limit information, evaluating a second maximum speed limit based on the road condition information, comparing the first maximum speed limit and the second maximum speed limit, and selecting the lower of the first and second maximum speed limits as the final maximum speed limit. The preset driving safety factor evaluation table may be set based on experience.

[0047] Exemplarily, after determining the minimum driving time, driving safety factor and minimum section length of each section, the minimum path length, minimum driving time and driving safety factor of the path to be selected are calculated based on the minimum driving time of each section, the driving safety factor of each section and the minimum section length of each section, including: calculating the sum of the minimum driving time of each section of the path to be selected as the minimum driving time of the path to be selected; calculating the sum of the minimum section length of each section of the path to be selected as the minimum section length of the path to be selected; calculating the sum of the driving safety factor of each section of the path to be selected as the driving safety factor of the path to be selected.

[0048] In one possible implementation, after completing the calculation of the minimum path length, minimum driving time and driving safety factor of the path to be selected, the priority coefficient of the path to be selected is calculated based on the minimum path length, minimum driving time and driving safety factor, including: obtaining the driving mode of the vehicle; determining the first preset weight, the second preset weight and the third preset weight based on the driving mode; calculating the priority coefficient of the path to be selected based on the first preset weight, the second preset weight, the third preset weight, the minimum path length, the minimum driving time and the driving safety factor.

[0049] Optionally, the autonomous driving domain controller reads the vehicle's driving mode through the ECU. The vehicle's driving mode includes, but is not limited to, a driving time priority mode, a driving distance priority mode, or a safe driving priority mode. After determining the vehicle's driving mode, a first preset weight, a second preset weight, and a third preset weight are determined based on the driving mode and the corresponding relationship between the driving mode and the weight coefficient. The first preset weight is the weight coefficient corresponding to the minimum path length in the priority coefficient calculation; the second preset weight is the weight coefficient corresponding to the minimum driving time in the priority coefficient calculation; and the third preset weight is the weight coefficient corresponding to the driving safety factor in the priority coefficient calculation.

[0050] Exemplarily, after determining the first preset weight, the second preset weight and the third preset weight, the priority coefficient of the path to be selected is calculated based on the first preset weight, the second preset weight, the third preset weight, the minimum path length, the minimum driving time and the driving safety factor, including: calculating the sum of the first preset weight multiplied by the minimum path length, the second preset weight multiplied by the minimum driving time, and the third preset weight multiplied by the driving safety factor as the priority coefficient of the path to be selected.

[0051] In step 206 , the autonomous driving domain controller determines a path to be driven based on the priority coefficient.

[0052] In one possible implementation, after calculating the priority coefficients, the autonomous driving domain controller determines a path to be traveled based on the priority coefficients, including selecting the path with the highest priority coefficient as the path to be traveled. Alternatively, after calculating the priority coefficients, the autonomous driving domain controller compares the priority coefficients of the paths to be selected, determines the highest priority coefficient, and selects the path corresponding to the highest priority coefficient as the path to be traveled. After determining the path to be traveled, the path to be traveled is displayed on the center console display screen to prompt the driver to follow the path to be traveled.

[0053] Optionally, while the vehicle is traveling along the path to be traveled, environmental information within a second preset range around the vehicle is obtained during the driving process. The environmental information within the second preset range includes real-time road condition information of the remaining sections of the path and the locations of new obstacles. The second preset range is smaller than the first preset range. The path to be traveled of the vehicle is adjusted in combination with the environmental information within the first preset range and the environmental information within the second preset range.

[0054] Exemplarily, during vehicle driving, the autonomous driving domain controller introduces the local obstacle avoidance algorithm Teb (Time Elastic Band) to obtain environmental information within a second preset range around the vehicle, and combines the environmental information within the first preset range and the environmental information within the second preset range to determine the real-time position of obstacles in the remaining sections of the vehicle's path. Based on the real-time position of the obstacles, a new path to be driven is generated through DWA (Dynamic Window Approach) or MPC (Model Predictive Control).

[0055] In one possible implementation, after determining the new path to be traveled, the autonomous driving domain controller adjusts the vehicle's remaining path to be traveled according to the new path to be traveled, ensuring that the remaining path to be traveled is passable while meeting the path requirements corresponding to the vehicle's current driving mode and minimizing the deviation between the remaining road section and the global path to be traveled.

[0056] Optionally, the environmental information within the second preset range includes real-time traffic information of the remaining sections of the path and the location of new obstacles. The second preset range can be set based on experience and must be smaller than the first preset range. For example, the second preset range can be a smaller range around the vehicle.

[0057] The embodiment of the present application obtains environmental information within a first preset range around the vehicle and the starting and ending points of the vehicle's journey, and generates an initial path based on the location of obstacles, the starting and ending points of the journey, wherein the initial path is a passable path with the shortest path length, which is convenient for providing a preliminary basis for multi-objective path planning; then, the road sections included in the initial path are crossed and mutated to obtain a preset number of paths to be selected; the priority coefficients of the paths to be selected are calculated based on the environmental information, and the paths to be traveled are determined based on the priority coefficients, so as to realize path planning under multi-objective considerations, thereby improving the accuracy and safety of path planning.

[0058] See also Figure 3 , an embodiment of the present application provides a path planning device, the device comprising:

[0059] A first acquisition module 301 is configured to acquire environmental information within a first preset range around the vehicle, where the environmental information within the first preset range includes the start and end points of each road section, speed limit information, lane information, traffic light information, road condition information, and the location of obstacles;

[0060] The second acquisition module 302 is used to obtain the starting point and end point of the vehicle's journey;

[0061] A generation module 303 is used to generate an initial path based on the location of the obstacle, the starting point and the end point of the journey, where the initial path is a passable path with the shortest path length;

[0062] The crossover and mutation module 304 is used to crossover and mutate the road segments included in the initial path to obtain a preset number of paths to be selected;

[0063] A calculation module 305 is used to calculate the priority coefficient of the path to be selected based on the environmental information;

[0064] The determination module 306 is configured to determine the path to be traveled based on the priority coefficient.

[0065] In one possible implementation, the calculation module 305 is used to calculate the minimum path length, minimum driving time and driving safety factor of the path to be selected based on environmental information; and calculate the priority coefficient of the path to be selected based on the minimum path length, minimum driving time and driving safety factor.

[0066] In one possible implementation, the calculation module 305 is used to calculate the minimum section length of each section based on the starting point and end point of each section; calculate the minimum driving time of each section based on the speed limit information, road condition information and minimum section length of each section; evaluate the driving safety factor of each section based on the lane line information, speed limit information, traffic light information and road condition information of each section; calculate the minimum path length, minimum driving time and driving safety factor of the path to be selected based on the minimum driving time of each section, the driving safety factor of each section and the minimum section length of each section.

[0067] In one possible implementation, the calculation module 305 is used to obtain the driving mode of the vehicle; determine the first preset weight, the second preset weight and the third preset weight based on the driving mode; and calculate the priority coefficient of the path to be selected based on the first preset weight, the second preset weight, the third preset weight, the minimum path length, the minimum driving time and the driving safety factor.

[0068] In one possible implementation, the device also includes: a third acquisition module, used to obtain environmental information within a second preset range around the vehicle during the vehicle's driving process, the environmental information within the second preset range includes real-time road condition information of the remaining sections of the path and the location of new obstacles, and the second preset range is smaller than the first preset range; an adjustment module, used to adjust the vehicle's future driving path in combination with the environmental information within the first preset range and the environmental information within the second preset range.

[0069] In a possible implementation, the determination module 306 is configured to select a path with the highest priority coefficient as the path to be traveled.

[0070] This device obtains environmental information within a first preset range around the vehicle and the starting and ending points of the vehicle's journey, and generates an initial path based on the locations of obstacles, the starting and ending points of the journey. The initial path is a passable path with the shortest path length, which is convenient for providing a preliminary basis for multi-objective path planning; then, the road sections included in the initial path are crossed and mutated to obtain a preset number of paths to be selected; the priority coefficients of the paths to be selected are calculated based on the environmental information, and the paths to be traveled are determined based on the priority coefficients, thereby realizing path planning under multi-objective considerations, thereby improving the accuracy and safety of path planning.

[0071] It should be noted that the apparatus provided in the above embodiments is merely illustrated by the division of the above functional modules when implementing its functions. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0072] In an exemplary embodiment, a computer-readable storage medium is further provided, in which at least one computer program is stored. The at least one computer program is loaded and executed by a processor of a computer device to enable the computer to implement any of the above-mentioned path planning methods.

[0073] In one possible implementation, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0074] In an exemplary embodiment, a computer program product or computer program is also provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform any of the above-described path planning methods.

[0075] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions. For example, the environmental information within the first preset range around the vehicle, the starting and end points of the vehicle's journey, the path to be selected and the path to be traveled involved in this application are all obtained with full authorization.

[0076] It should be understood that the term "plurality" used herein refers to two or more. "And / or" describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, or B exists alone. The character " / " generally indicates an "or" relationship between the associated objects.

[0077] It should be noted that the terms "first," "second," etc. (if any) in the specification and claims of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the numbers used in this way are interchangeable where appropriate so that the embodiments of the application described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the application as detailed in the appended claims.

[0078] The above description is merely an exemplary embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A path planning method, characterized in that: The method comprises: Acquiring environmental information within a first preset range around the vehicle, the environmental information within the first preset range including the start and end points of each road section, speed limit information, lane information, traffic light information, road condition information, and the location of obstacles; Obtaining the starting point and end point of the vehicle's trip; generating an initial path based on the location of the obstacle, the starting point and the end point of the trip, wherein the initial path is a passable path with the shortest path length; Crossing and mutating the road segments included in the initial path to obtain a preset number of paths to be selected; Calculating a priority coefficient of the path to be selected based on the environmental information; A path to be traveled is determined based on the priority coefficient.

2. The method according to claim 1, characterized in that The calculating the priority coefficient of the path to be selected based on the environmental information includes: Calculating a minimum path length, a minimum driving time, and a driving safety factor of the path to be selected based on the environmental information; The priority coefficient of the path to be selected is calculated based on the minimum path length, the minimum driving time and the driving safety factor.

3. The method according to claim 2, characterized in that The calculating, based on the environmental information, the minimum path length, the minimum driving time, and the driving safety factor of the path to be selected includes: Calculating the minimum section length of each section based on the starting point and the end point of each section; Calculating the minimum driving time of each road section based on the speed limit information, road condition information and the minimum road section length of each road section; Evaluate the driving safety factor of each road section based on lane information, speed limit information, traffic light information, and road condition information of each road section; The minimum path length, minimum driving time and driving safety factor of the path to be selected are calculated based on the minimum driving time of each section, the driving safety factor of each section and the minimum section length of each section.

4. The method according to claim 2, characterized in that The calculating the priority coefficient of the to-be-selected path based on the minimum path length, the minimum driving time, and the driving safety factor includes: obtaining a driving mode of the vehicle; determining a first preset weight, a second preset weight, and a third preset weight based on the driving mode; The priority coefficient of the path to be selected is calculated based on the first preset weight, the second preset weight, the third preset weight, the minimum path length, the minimum driving time and the driving safety factor.

5. The method according to claim 1, wherein The method further comprises: acquiring environmental information within a second preset range around the vehicle during the vehicle's travel, the environmental information within the second preset range including real-time traffic information of the remaining sections of the route and locations of newly added obstacles, the second preset range being smaller than the first preset range; The future travel path of the vehicle is adjusted based on the environmental information within the first preset range and the environmental information within the second preset range.

6. The method according to claim 1, characterized in that The determining of the to-be-traveled path based on the priority coefficient includes: The path with the highest priority coefficient is selected as the path to be traveled.

7. A path planning device, characterized in that: The device comprises: a first acquisition module, configured to acquire environmental information within a first preset range around the vehicle, the environmental information within the first preset range including the start and end points of each road section, speed limit information, lane information, traffic light information, road condition information, and the location of obstacles; A second acquisition module is used to obtain the starting point and end point of the vehicle's journey; a generating module, configured to generate an initial path based on the location of the obstacle, the starting point and the end point of the trip, wherein the initial path is a passable path with the shortest path length; A crossover and mutation module, configured to crossover and mutate the road segments included in the initial path to obtain a preset number of paths to be selected; A calculation module, configured to calculate the priority coefficient of the path to be selected based on the environmental information; A determination module is used to determine a path to be traveled based on the priority coefficient.

8. The device according to claim 7, characterized in that The calculation module is used to calculate the minimum path length, minimum driving time and driving safety factor of the path to be selected based on the environmental information; and calculate the priority coefficient of the path to be selected based on the minimum path length, the minimum driving time and the driving safety factor.

9. A computer program product, comprising computer instructions, which, when executed by a processor, implement the steps of the path planning method according to any one of claims 1 to 6.

10. A non-transitory computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which is loaded and executed by a processor to implement the path planning method according to any one of claims 1 to 6.

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