Path planning method and device for avoiding target vehicle, equipment and medium

Abstract

The invention provides a path planning method and device for avoiding a target vehicle, equipment and a medium. The method comprises the following steps: acquiring a current position of a current vehicle in real time; determining road data and traffic flow data matched with the current position; determining a target vehicle and a vehicle position matched with the target vehicle from the vehicle identity information; and obtaining a target position where the current vehicle runs, and obtaining a planned driving path of the current vehicle based on a vehicle position matched with the target vehicle, the current position and the target position. The target vehicle can be avoided as far as possible, so that the safety in the driving process is improved.

Description

Technical Field

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

[0002] With the continuous development of the field of vehicle technology, vehicles with special functions have also flooded into the market. For example, vehicles with special functions can be vehicles with automatic driving functions, vehicles with cargo carrying functions, vehicles with road cleaning functions, vehicles with natural gas carrying functions, etc.

[0003] When these vehicles with special functions are driving on the road, due to the fact that the technology of these vehicles may not be mature enough, or the items or goods they carry are dangerous, etc., if they are driving on the same road with many other vehicles with special functions, there is a high possibility of driving accidents. Summary of the invention

[0004] The present invention provides a path planning method, device, equipment and medium for avoiding a target vehicle, which can improve driving safety.

[0005] The technical solution of the present invention: a path planning method for avoiding a target vehicle, applied to a current vehicle, the path planning method for avoiding a target vehicle includes: obtaining the current position of the current vehicle; determining road data and traffic data matching the current position, wherein both the road data and the traffic data change with the change of the current position, the road data at least including one or more lanes and the lane position corresponding to each lane, and the traffic data at least including vehicle identity information and vehicle position corresponding to the vehicle on each lane; determining the target vehicle according to the vehicle identity information, and obtaining the vehicle position matching the target vehicle; obtaining the target position of the current vehicle, and obtaining the planned driving path of the current vehicle based on the vehicle position matching the target vehicle, the current position and the target position.

[0006] In some embodiments, determining the road data and traffic data that match the current position includes: acquiring the road data and traffic data within a circular range with the current position as the center and a preset distance as the radius.

[0007] In some embodiments, the obtaining of road data and traffic flow data within a circular range centered at the current position with a preset distance as the radius includes: obtaining environmental images within a circular range centered at the current position with a preset distance as the radius, where the environmental images include road images and traffic flow images; extracting road data from the road images and extracting traffic flow data from the traffic flow images.

[0008] In some embodiments, the extracting of traffic flow data from the traffic flow images includes: determining vehicle identity information matching the current position according to the traffic flow images, where the vehicle identity information includes first license plate information; determining target license plate information matching second license plate information in the first license plate information, where the vehicle corresponding to the second license plate information has a first function, and the first function is used to characterize that the vehicle has an autonomous driving function, a cargo-carrying function, or an engineering use function; the determining of the target vehicle from the vehicle identity information includes: marking the vehicle matching the target license plate information as the target vehicle.

[0009] In some embodiments, after determining the target vehicle and the vehicle position matching the target vehicle from the vehicle information, it includes: storing the current position, the road data, and the vehicle position matching the target vehicle into the database of the current vehicle.

[0010] In some embodiments, the obtaining of the target position where the current vehicle travels, and based on the vehicle position matching the target vehicle, the current position, and the target position, obtaining the planned driving route of the current vehicle includes: obtaining the target position where the current vehicle travels, planning an initial driving route based on the current position and the target position; and adjusting the initial driving route in real time based on the vehicle position matching the target vehicle to obtain the planned driving route of the current vehicle.

[0011] An embodiment of the present application further provides a path planning device, including: an acquisition module, configured to acquire the current position where the current vehicle is located in real time; a first determination module, configured to determine road data and traffic flow data that match the current position, where the road data and the traffic flow data both change with the change of the current position, the road data at least includes one or more lanes and the lane positions corresponding to each lane, and the traffic flow data at least includes the vehicle identity information and vehicle positions corresponding to the vehicles on each lane, and each vehicle identity information corresponds to each vehicle position one by one; a second determination module, configured to determine a target vehicle and a vehicle position matching the target vehicle from the vehicle identity information; a planning module, configured to acquire a target position for the current vehicle to travel, and obtain a planned driving path of the current vehicle based on the vehicle position matching the target vehicle, the current position, and the target position.

[0012] In some embodiments, the path planning device further includes: a storage module, configured to store the current position, the road data, and the vehicle position matching the target vehicle in the database of the current vehicle.

[0013] An embodiment of the present application further provides an electronic device, where the electronic device includes a processor and a memory, the memory is configured to store instructions, and the processor is configured to call the instructions in the memory so that the electronic device executes the above-mentioned path planning method for avoiding a target vehicle.

[0014] An embodiment of the present application further provides a computer-readable storage medium, where the computer-readable storage medium stores computer instructions, and when the computer instructions run on an electronic device, the electronic device is enabled to execute the above-mentioned path planning method for avoiding a target vehicle.

[0015] Compared with the prior art, the above-mentioned path planning method, device, electronic device, and computer-readable storage medium for avoiding a target vehicle can acquire road images and traffic flow images within a preset range centered on the current position in real time. Extract road data from the road images. Determine vehicle identity information matching the current position according to the traffic flow images. Then determine target license plate information matching the second license plate information from the vehicle identity information. To acquire in real time a target vehicle with a first function on the road within a preset range centered on the current position. Based on this, a planned driving path is obtained. To try to avoid roads with a relatively large number of target vehicles with a first function. Due to situations such as the technology development of the target vehicle itself may not be mature enough, or the items or goods carried by the target vehicle are dangerous. If, during the driving process, driving on the same road with a relatively large number of target vehicles, there is a relatively high possibility of a driving accident. Description of the Drawings

[0016] Figure 1 It is a flowchart of the steps of a path planning method for avoiding a target vehicle according to an embodiment of the present application.

[0017] Figure 2 It is a simple schematic diagram of an environmental image according to an embodiment of the present application.

[0018] Figure 3 It is a schematic structural diagram of a path planning device according to an embodiment of the present application.

[0019] Figure 4 It is a schematic structural diagram of an electronic device according to an embodiment of the present application.

[0020] Description of main component symbols

[0021] Electronic device 100

[0022] Memory 20

[0023] Processor 30

[0024] Computer program 40

[0025] Path planning device 200

[0026] Acquisition module 210

[0027] First determination module 220

[0028] Second determination module 230

[0029] Planning module 240

[0030] Storage module 250

[0031] Current position O

[0032] First lane D1

[0033] Second lane D2

[0034] Third lane D3

[0035] Fourth lane D4

[0036] First vehicle C1

[0037] Second vehicle C2

[0038] Third vehicle C3

[0039] Fourth vehicle C4 Detailed implementation manners

[0040] In order to more clearly understand the above-mentioned objects, features, and advantages of the present application, the present application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.

[0041] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application. The described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments.

[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs. The terms used in the description of this application herein are only for the purpose of describing specific embodiments, and are not intended to limit this application.

[0043] Furthermore, it should be noted that, in this document, the term "comprising", "including" or any other variant thereof is intended to cover a non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the presence of additional identical elements in the process, method, article or device comprising that element.

[0044] In the embodiments of the present application, the term "at least one" means one or more, and "a plurality" means two or more than two. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone, where A and B may be singular or plural. The terms "first", "second", "third", "fourth", etc. (if any) in the description, claims, and drawings of the present application are used to distinguish similar objects, rather than to describe a specific order or sequence.

[0045] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present relevant concepts in a specific manner.

[0046] The path planning method for avoiding a target vehicle of the present application can be applied to one or more electronic devices. The electronic device is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a processor, a microprogrammed control unit (MCU), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), an embedded device, etc. The electronic device can be a portable electronic device (such as a mobile phone, a tablet computer), a personal computer, a server, etc.

[0047] Figure 1 FIG. 1 is a flowchart of steps of an embodiment of the path planning method for avoiding a target vehicle of the present application. According to different requirements, the order of steps in the flowchart can be changed, and some steps can be omitted. The path planning method for avoiding a target vehicle is applied to a path planning system. The path planning system can be installed in a vehicle. The vehicle can be a household vehicle, a commercial vehicle, an engineering vehicle, etc., and the present application does not limit the type of the vehicle.

[0048] Refer to Figure 1 As shown in FIG. 1, the path planning method for avoiding a target vehicle is applied to the current vehicle. The path planning method for avoiding a target vehicle may include the following steps.

[0049] S100. Obtain the current position where the current vehicle is located in real time.

[0050] In some embodiments, a data acquisition device is installed in the vehicle. The data acquisition device can be an in-vehicle sensor, a radar, a camera, a global positioning system (GPS), etc. The in-vehicle sensor is mainly used to detect short-range obstacles around the vehicle, such as distance perception when parking. The radar mainly detects the position and speed of surrounding objects by emitting radio waves and measuring their reflections. The camera is used to capture images on the road to help identify other vehicles, pedestrians, road signs, traffic signals, etc. The GPS mainly obtains the real-time positioning information of the vehicle and plans a driving path for the vehicle. In other embodiments, the current vehicle may further include other types of data acquisition devices, and the present application does not limit the types included in the data acquisition device.

[0051] In some embodiments, the path planning system obtains the current position where the current vehicle is located based on the data acquisition device installed in the current vehicle.

[0052] S200. Determine the road data and traffic flow data that match the current position, where the road data and traffic flow data change with the change of the current position. The road data includes at least one or more lanes and the lane positions corresponding to each of the lanes. The traffic flow data includes at least the vehicle identity information and vehicle positions corresponding to the vehicles on each of the lanes.

[0053] In some embodiments, the path planning system takes the current position as the center and obtains the road data and traffic flow data within a preset range. In this embodiment, as Figure 2 shown, assume that the current position where the current vehicle is located is O, and the preset range is 1 km. The path planning system obtains the road data and traffic flow data within a radius of 1 km centered on the current position O. Among them, the road data may further include the extension direction of each lane, the width of each lane, etc. The traffic flow data may further include the driving speed of each vehicle, etc. In other embodiments, the vehicle data and road data may further include other data types, and the present application does not limit the data types included in the vehicle data and road data.

[0054] Further, in this embodiment, based on the camera installed in the current vehicle, the path planning system first obtains the environmental images within a circular range centered on the current position O with a preset distance as the radius. Among them, the environmental images include road images and traffic flow images. For example, the road image is an image showing the road conditions within a circular range centered on the current position O with a preset distance as the radius, where the image can be a photo or a video; the traffic flow image is an image showing the vehicle driving conditions within a circular range centered on the current position O with a preset distance as the radius. Then, the road data is extracted from the road image, and the traffic flow data is extracted from the traffic flow image. In this embodiment, after parsing the environmental images using image recognition technology, the environmental images are extracted to obtain the road images and traffic flow images.

[0055] The principle of the image recognition technology is based on the deep learning algorithm. By constructing a deep neural network model, feature extraction and classification are performed on the road images and traffic flow images. First, a large amount of image data is input into the neural network for training. By continuously adjusting the network parameters, the network can accurately identify different categories of images. Then, the image to be recognized is input into the trained neural network, and the network will output the category label of the image, thereby realizing the automatic recognition of the image.

[0056] In this embodiment, the path planning system also needs to perform data cleaning on road data and traffic flow data. Among them, data cleaning refers to cleaning, correcting, formatting, and organizing the original data to convert the original data into data that can be used for analysis. For example, data cleaning can be performed on the original data by means of missing value processing, noise data removal, and consistency checking. Thus, redundant data or useless data in the road data and traffic flow data are removed. And format conversion is performed on the cleaned vehicle data and road data to ensure that the format of each traffic flow data is unified, and to ensure that the format of each road data is unified. For example, in this embodiment, the road data includes one or more lanes and the lane positions corresponding to each lane. The traffic flow data may include the vehicle identity information and vehicle position corresponding to the vehicles on each lane.

[0057] Specifically, according to the traffic flow image, the vehicle identity information matching the current position O is determined, where the vehicle identity information includes the first license plate information. The target license plate information matching the second license plate information is determined in the first license plate information, where the vehicle corresponding to the second license plate information has a first function, and the first function is used to characterize that the vehicle has an autonomous driving function, a cargo-carrying function, or an engineering use function. In other embodiments, the first function may also be other functions such as a road cleaning function, a towing function, etc., and the specific type of the first function is not limited in this application. Among them, in this embodiment, a vehicle with an autonomous driving function is also referred to as an autonomous vehicle (Autonomous vehicles; Self-piloting automobile). In the embodiments of this application, an autonomous vehicle may also be referred to as a driverless car, a computer-driven car, or a wheeled mobile robot, which is an intelligent car that realizes driverless through a computer device. In practical applications, autonomous vehicles rely on the collaborative cooperation of artificial intelligence, visual computing, radar, monitoring devices, and global positioning devices, so that computer devices can automatically and safely operate motor vehicles without any active operation by humans. A vehicle with a cargo-carrying function is a cargo truck, including dump trucks, tractor trucks, etc., which are mainly used to transport goods. Vehicles with engineering use functions include excavators, bulldozers, rollers, loaders, engineering rescue vehicles, etc.

[0058] In this embodiment, as Figure 2As shown, assuming based on the current position O of the current vehicle, the path planning system acquires road images and traffic flow images within a circular range centered at the current position O with a preset distance as the radius. The road data extracted from the road images includes the first lane D1, the second lane D2, the third lane D3, and the fourth lane D4, as well as the lane positions corresponding to the four lanes. The traffic flow data extracted from the traffic flow images includes the vehicle identity information corresponding to the first vehicle C1 on the first lane D1, the vehicle identity information corresponding to the second vehicle C2 on the second lane D2, the vehicle identity information corresponding to the third vehicle C3 also on the second lane D2, the vehicle identity information corresponding to the fourth vehicle C4 on the fourth lane D4, and the vehicle positions of the four vehicles.

[0059] Furthermore, the path planning system determines that the first license plate information in the vehicle identity information corresponding to the first vehicle C1 is C11, the first license plate information in the vehicle identity information corresponding to the second vehicle C2 is C21, the first license plate information in the vehicle identity information corresponding to the third vehicle C3 is C31, and the first license plate information in the vehicle identity information corresponding to the fourth vehicle C4 is C41.

[0060] For example, in this embodiment, the second license plate information is stored in the database of the path planning system. The second license plate information includes C11, C41, C61, and C91. For the sake of easy understanding, the first function is taken as an example of the autonomous driving function for illustration. That is, the vehicles corresponding to the second license plate information (C11, C41, C61, and C91) have the autonomous driving function. Determine the target license plate information that matches the second license plate information from the first license plate information (C11, C21, C31, and C41). The target license plate information is C11 and C41.

[0061] S300. Determine the target vehicle according to the vehicle identity information, and obtain the vehicle position that matches the target vehicle.

[0062] In some embodiments, the path planning system marks the vehicles that match the target license plate information as target vehicles. As described in step S200, the target license plate information is C11 and C41. The path planning system marks the first vehicle C1 with the first license plate information C11 as the target vehicle, and the fourth vehicle C4 with the first license plate information C41 as the target vehicle.

[0063] In this embodiment, the path planning system also stores the current position O, the road data, and the vehicle positions that match the target vehicles in the database of the current vehicle. Facilitate subsequent path planning for the current vehicle by the path planning system based on the data in the database.

[0064] S400. Obtain the target position of the current vehicle traveling, and based on the vehicle position, current position, and target position that match the target vehicle, obtain the planned driving path of the current vehicle.

[0065] In some embodiments, obtain the target position of the current vehicle, and based on the current position O and the target position, plan an initial driving path. Based on the vehicle position that matches the target vehicle, adjust the initial driving path in real time to obtain the planned driving path of the current vehicle. In this embodiment, based on the current position O and the target position of the current vehicle, the path planning system plans an initial driving path from the current position O to the target position. Then, as the current vehicle travels, the traffic flow conditions between the current position O and the target position are constantly changing. The path planning system can adjust the initial driving path in real time based on the vehicle position that matches the target vehicle obtained in real time, to obtain the planned driving path of the current vehicle, so as to adapt to the constantly changing traffic flow conditions and plan a driving path with fewer target vehicles.

[0066] The path planning method for avoiding target vehicles in this application is based on the data acquisition device that can obtain the road image and traffic flow image between the current position O and the target position in real time. After performing image recognition technology processing and analysis on the road image and traffic flow image, road data and traffic flow data can be obtained. Then, the position of the target vehicle with the first function is extracted from the traffic flow data. To obtain in real time the target vehicles with the first function on the road within the preset range centered on the current position O. Based on this, obtain the planned driving path of the current vehicle. To avoid as much as possible the roads with more vehicles having the first function, thereby improving the safety of the driving process.

[0067] In some embodiments, this application also discloses a path planning device 200 for avoiding target vehicles. As Figure 3As shown, the path planning device 200 for avoiding a target vehicle includes an acquisition module 210, a first determination module 220, a second determination module 230, a planning module 240, and a storage module 250. The acquisition module 210 is configured to acquire the current position O where the current vehicle is located in real time; the first determination module 220 is configured to determine road data and traffic flow data that match the current position O, where the road data and the traffic flow data both change with the change of the current position O, the road data at least includes one or more lanes and the lane positions corresponding to each lane, and the traffic flow data at least includes the vehicle identity information and vehicle positions corresponding to the vehicles on each lane; the second determination module 230 is configured to determine the target vehicle according to the vehicle identity information and obtain the vehicle position that matches the target vehicle; the planning module 240 is configured to acquire the target position where the current vehicle travels, and based on the vehicle position that matches the target vehicle, the current position O, and the target position, obtain the planned driving path of the current vehicle. The storage module 250 is configured to store the current position O, the road data, and the vehicle position that matches the target vehicle in the database of the current vehicle.

[0068] In some embodiments, the present application also discloses an electronic device 100, as Figure 4 shown, the electronic device 100 includes a memory 20, a processor 30, and a computer program 40 stored in the memory 20 and executable on the processor 30. When the processor 30 executes the computer program 40, the steps in the above-described embodiment of the path planning method for avoiding a target vehicle are implemented, for example Figure 1 the steps 100 to 400 shown.

[0069] Exemplarily, the computer program 40 can also be divided into one or more modules / units, and the one or more modules / units are stored in the memory 20 and executed by the processor 30. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program 40 in the electronic device 100.

[0070] Those skilled in the art can understand that the schematic diagram is only an example of the electronic device 100, and does not constitute a limitation on the electronic device 100. It may include more or fewer components than shown, or combine some components, or different components. For example, the electronic device 100 may further include input / output devices, network access devices, buses, etc.

[0071] The processor 30 may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, a single-chip microcomputer, or the processor 30 may also be any conventional processor, etc.

[0072] The memory 20 can be used to store the computer program 40 and / or modules / units. By running or executing the computer program and / or modules / units stored in the memory 20, and by invoking the data stored in the memory 20, the processor 30 realizes various functions of the electronic device 100. The memory 20 mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created according to the use of the electronic device 100 (such as audio data). In addition, the memory 20 may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices.

[0073] If the modules / units integrated in the electronic device 100 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-described embodiment methods of this application, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0074] In several embodiments provided in this application, it should be understood that the disclosed electronic device and method can be implemented in other ways. For example, the above-described electronic device embodiments are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation.

[0075] In addition, in each embodiment of this application, the functional units can be integrated in the same processing unit, or each unit can exist physically alone, or two or more units can be integrated in the same unit. The above-mentioned integrated units can be implemented in the form of hardware, or in the form of hardware plus software functional modules.

[0076] For those skilled in the art, it is obvious that this application is not limited to the details of the above-described exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or basic characteristics of this application. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. In addition, obviously, the word "including" does not exclude other units or steps, and the singular does not exclude the plural. The multiple units or electronic devices stated in the electronic device claims can also be implemented by the same unit or electronic device through software or hardware. The terms first, second, etc. are used to represent names and do not represent any specific order.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and not to limit them. Although the present application has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that the technical solutions of the present application can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A path planning method for avoiding a target vehicle, which is applied to a current vehicle, characterized in that The method includes: Obtaining the current position where the current vehicle is located in real time; Determining road data and traffic flow data that match the current position, wherein both the road data and the traffic flow data change with the change of the current position, the road data includes at least one or more lanes and the lane position corresponding to each lane, and the traffic flow data includes at least the vehicle identity information and vehicle position corresponding to the vehicles on each lane; Determining a target vehicle according to the vehicle identity information and obtaining the vehicle position that matches the target vehicle; Obtaining the target position where the current vehicle travels, and based on the vehicle position that matches the target vehicle, the current position and the target position, obtaining the planned driving path of the current vehicle.

2. The path planning method for avoiding a target vehicle according to claim 1, wherein The determining the road data and traffic flow data that match the current position includes: Obtaining the road data and traffic flow data within a circular range centered on the current position with a preset distance as the radius.

3. The path planning method for avoiding a target vehicle according to claim 2, wherein, The obtaining the road data and traffic flow data within a circular range centered on the current position with a preset distance as the radius includes: Obtaining an environmental image within a circular range centered on the current position with a preset distance as the radius, wherein the environmental image includes a road image and a traffic flow image; Extracting road data from the road image and extracting traffic flow data from the traffic flow image.

4. The path planning method for avoiding a target vehicle according to claim 3, wherein, The extracting the traffic flow data from the traffic flow image includes: Determining, according to the traffic flow image, the vehicle identity information that matches the current position, wherein the vehicle identity information includes first license plate information; Determining target license plate information that matches second license plate information in the first license plate information, wherein the vehicle corresponding to the second license plate information has a first function, and the first function is used to characterize that the vehicle has an autonomous driving function, a cargo-carrying function or an engineering use function; The determining the target vehicle from the vehicle identity information includes: Marking the vehicle that matches the target license plate information as the target vehicle.

5. The path planning method for avoiding a target vehicle according to claim 1, wherein After determining the target vehicle and the vehicle position that matches the target vehicle from the vehicle information, it includes: Storing the current position, the road data and the vehicle position that matches the target vehicle into the database of the current vehicle.

6. The path planning method for avoiding a target vehicle according to claim 1, characterized in that The obtaining the target position where the current vehicle travels, and based on the vehicle position that matches the target vehicle, the current position and the target position, obtaining the planned driving path of the current vehicle includes: Obtaining the target position where the current vehicle travels, and planning an initial driving path based on the current position and the target position; Based on the vehicle position that matches the target vehicle, adjusting the initial driving path in real time to obtain the planned driving path of the current vehicle.

7. A path planning device, characterized in that, It includes: An obtaining module, which is used to obtain the current position where the current vehicle is located in real time; A first determination module, configured to determine road data and traffic flow data that match the current position, where the road data and the traffic flow data both change with the change of the current position, the road data at least includes one or more lanes and the lane positions corresponding to each lane, and the traffic flow data at least includes vehicle identity information and vehicle positions corresponding to the vehicles on each lane; A second determination module, configured to determine a target vehicle according to the vehicle identity information and obtain the vehicle position that matches the target vehicle; A planning module, configured to obtain the target position of the current vehicle traveling, and obtain the planned driving path of the current vehicle based on the vehicle position that matches the target vehicle, the current position, and the target position.

8. The path planning device according to claim 7, wherein, It further includes: A storage module, configured to store the current position, the road data, and the vehicle position that matches the target vehicle into the database of the current vehicle.

9. An electronic device, the electronic device comprising a processor and a memory, characterized in that, The memory is used to store instructions, and the processor is used to call the instructions in the memory, so that the electronic device executes the path planning method for avoiding a target vehicle according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions, and when the computer instructions run on an electronic device, the electronic device is caused to execute the path planning method for avoiding a target vehicle according to any one of claims 1 to 6.

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