TWI875424B - Path planning method for evading object vehicle,device,electronic equipment and storage media - Google Patents

Abstract

This application provides a path planning method for evading object vehicle, device, electornic equipment and storage medium. The method includes : obtaining a current location of a current vehicle in real time, determining road data and traffic flow data for matching the current location, determining an object vehicle and a location of the object vehicle from vehicle identiti information, obtaining an object location of the current vehicle, and obtaining a planned driving path of the current vehicle based on the location of the object vehicle, the current location and the object location. This application can advoid the object vehicle to improve safety during driving.

Description

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

This application relates to the field of autonomous driving technology, and in particular to a path planning method, device, equipment and medium for avoiding target vehicles.

With the continuous development 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 functions, vehicles with road cleaning functions, vehicles with natural gas carrying functions, etc.

When these vehicles with special functions are driving on the road, the technology of these vehicles may not be mature enough, or the items or cargo they carry may be dangerous. If you are driving on the same road with a large number of these vehicles with special functions, there is a high possibility of a driving accident.

In view of this, this application proposes a path planning method, device, equipment and medium for avoiding target vehicles, which can improve driving safety.

In a first aspect, an embodiment of the present application provides a path planning method for avoiding a target vehicle, which is applied to a current vehicle. The path planning method for avoiding a target vehicle comprises: obtaining a current position of the current vehicle in real time; determining road data and traffic data matching the current position, wherein the road data and the traffic data change with the change of the current position, and the road data at least includes one or more lanes and each lane; The lane position corresponding to the lane, the traffic data at least includes the vehicle identity information and vehicle position corresponding to each vehicle on the lane; the target vehicle is determined according to the vehicle identity information, and the vehicle position matching the target vehicle is obtained; the target position of the current vehicle is obtained, and the planned driving path of the current vehicle is obtained based on the vehicle position matching the target vehicle, the current position and the target position.

In one embodiment, determining the road data and traffic data that match the current location includes: obtaining the road data and traffic data within a circular range with the current location as the center and a preset distance as the radius.

In one embodiment, the step of obtaining road data and traffic data within a circular range with the current position as the center and a preset distance as the radius includes: obtaining an environmental image within a circular range with the current position as the center and a preset distance as the radius, wherein the environmental image includes a road image and a traffic image; extracting road data from the road image, and extracting traffic data from the traffic image.

In one embodiment, extracting traffic data from the traffic image includes: determining vehicle identity information matching the current position according to the traffic image, wherein the vehicle identity information includes first license plate information; determining target license plate information matching the 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 indicate that the vehicle has an automatic driving function, a cargo function, or an engineering function; determining the target vehicle from the vehicle identity information includes: marking the vehicle matching the target license plate information as the target vehicle.

In one embodiment, 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 in the database of the current vehicle.

In one embodiment, the obtaining of 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, includes: obtaining the target position of the current vehicle, and planning an initial driving path based on the current position and the target position; and adjusting the initial driving path in real time based on the vehicle position matching the target vehicle to obtain the planned driving path of the current vehicle.

In a second aspect, an embodiment of the present application provides a route planning device, comprising an acquisition module for acquiring the current position of the current vehicle in real time; a first determination module for determining road data and traffic data that match the current position, wherein the road data and the traffic data change with the change of the current position, the road data at least includes one or more lanes and the lane position corresponding to each lane, and the traffic data at least includes a lane position corresponding to each lane. The vehicle identity information and vehicle position corresponding to the vehicle on the lane, each vehicle identity information corresponds to each vehicle position one by one; the second determination module is used to determine the target vehicle and the vehicle position matching the target vehicle from the vehicle identity information; the planning module is used to obtain the target position of the current vehicle, and based on the vehicle position matching the target vehicle, the current position and the target position, obtain the planned driving path of the current vehicle.

In one embodiment, the route planning device further includes: a storage module for storing the current position, the road data and the vehicle position matching the target vehicle in the database of the current vehicle.

In a third aspect, an embodiment of the present application provides an electronic device, the electronic device comprising a processor and a memory, 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 the target vehicle as described in the first aspect.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium for storing a computer program. When the computer program is run on an electronic device, the electronic device executes the path planning method for avoiding a target vehicle as described in the first aspect.

Compared with the prior art, the above-mentioned path planning method, system, electronic device and computer-readable storage medium for avoiding target vehicles can obtain road images and traffic images within a preset range with the current position as the center in real time. Road data is extracted from the road image. Based on the traffic image, the vehicle identity information matching the current position is determined. Then, the target license plate information matching the second license plate information is determined from the vehicle identity information. The target vehicle with the first function in the road within the preset range with the current position as the center is obtained in real time. Based on this, the planned driving path is obtained. Try to avoid roads with many target vehicles with the first function, because the target vehicles themselves may not be mature enough in technology development, or the items or cargo carried by the target vehicles are dangerous. If you drive on the same road with many target vehicles, there is a high possibility of a driving accident.

100: Electronic equipment

20: Memory

30: Processor

40: Computer Programs

200: Path planning device

210: Get module

220: First confirmation module

230: Second confirmation module

240: Planning module

250: Storage module

O: Current location

D1: First lane

D2: Second lane

D3: The third lane

D4: Lane 4

C1: The first vehicle

C2: Second vehicle

C3: The third vehicle

C4: The fourth vehicle

S100, S200, S300, S400: Steps

Figure 1 is a schematic diagram of the steps of a path planning method for avoiding a target vehicle in an embodiment of the present application.

Figure 2 is a schematic diagram of the structure of the environmental image of an embodiment of this application.

Figure 3 is a schematic diagram of the structure of a path planning device of an embodiment of the present application.

Figure 4 is a schematic diagram of the structure of an electronic device of an embodiment of this application.

The following will combine the attached figures in the implementation method of this application to clearly and completely describe the technical solution in the implementation method of this application. Obviously, the implementation method described is only a part of the implementation method of this application, not the entire implementation method.

It should be noted that in the embodiments of this application, "at least one" refers to one or more, and "more" refers to two or more. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of this application. The terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application.

It should be noted that in the embodiments of the present application, the terms "first" and "second" are only used for the purpose of distinguishing descriptions, and cannot be understood as indicating or implying relative importance, nor can they be understood as indicating or implying order. Features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present application, the terms "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete way.

Please refer to Figure 1, which is a schematic diagram of the step flow of a path planning method for avoiding a target vehicle provided in an embodiment of the present application. According to different requirements, the order of the steps in the flow chart 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 vehicle.

Referring to FIG. 1 , a path planning method for avoiding a target vehicle is applied to a current vehicle. The path planning method for avoiding a target vehicle may include the following steps:

Step S100, obtaining the current position of the current vehicle in real time.

In some embodiments, data collection equipment is installed in the autonomous vehicle. The data collection equipment may be a vehicle-mounted sensor, radar, camera, global positioning system (GPS), etc. The vehicle-mounted sensor is only used to detect close-range obstacles around the vehicle, such as distance perception when parking. Radar mainly detects the position and speed of surrounding objects by emitting radio waves and measuring their reflection. Cameras are used to capture images on the road, such as identifying other vehicles, pedestrians, road signs, and traffic signals. GPS mainly obtains real-time positioning information of the vehicle and plans the driving route for the vehicle. In other embodiments, the autonomous vehicle may also include other types of data collection devices, and this application does not limit the types of data collection devices.

Specifically, in some embodiments, the route planning system obtains the current location of the current vehicle based on a data acquisition device installed in the current vehicle.

Step S200, determining the road data and traffic data that match the current position, wherein the road data and the traffic data change with the change of the current position, the road data at least includes one or more lanes and the lane position corresponding to each lane, and the traffic data at least includes the vehicle identity information and vehicle position corresponding to the vehicle on each lane.

In some embodiments, the path planning system takes the current position as the center and obtains road data and traffic data within a preset range. In this embodiment, as shown in FIG2, assuming that the current position of the current vehicle is O and the preset range is 1km, the path planning system obtains road data and traffic data within a radius of 1km with the current position O as the center. Among them, the road data may also include the extension direction of each lane, the width of each lane, etc. The traffic data may also include the driving speed of each vehicle, etc. In other embodiments, the vehicle data and road data may also include other data types, and this application does not limit the data types included in the vehicle data and road data.

Furthermore, in this embodiment, based on the camera installed in the current vehicle, the path planning system first obtains the environment image within the circular range with the current position O as the center and the preset distance as the radius, wherein the environment image includes the road image and the traffic image. For example, the road image is an image showing the road conditions within the circular range with the current position O as the center and the preset distance as the radius, wherein the image can be a photo or a video; the traffic image is an image showing the driving conditions of the vehicle within the circular range with the current position O as the center and the preset distance as the radius. Then, the road data is extracted from the road image, and the traffic data is extracted from the traffic image. In this embodiment, after using image recognition technology to analyze the environmental image, the environmental image is extracted to obtain the road image and the traffic image.

The principle of image recognition technology is based on deep learning algorithms. By building a deep neural network model, features of road images and traffic images are extracted and classified. 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 images of different categories. Then, the image to be identified is input into the trained neural network, and the network will output the category label of the image, thereby realizing automatic image recognition.

In this embodiment, the route planning system also needs to clean the road data and traffic data. 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, the original data can be cleaned by processing missing values, removing noise data, and checking consistency. In this way, redundant data or useless data in the road data and traffic data are removed. And the cleaned vehicle data and road data are formatted to ensure that the format of each traffic data is unified, and the format of each road data is unified. For example, in this embodiment, the road data includes one or more lanes and the lane position corresponding to each lane. The traffic data can include the vehicle identity information and vehicle position corresponding to the vehicle on each lane.

Specifically, according to the traffic image, the vehicle identity information matching the current position O is determined, wherein 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, wherein the vehicle corresponding to the second license plate information has a first function, and the first function is used to indicate that the vehicle has an automatic driving function, a cargo function, or an engineering function. In other embodiments, the first function may also be other functions such as a road clearing function and a towing function, and the application does not limit the specific type of the first function. In this embodiment, the vehicle with the automatic driving function is also called an autonomous vehicle. In the present application embodiment, the self-driving vehicle can also be called an unmanned car, a computer-driven car, or a wheeled mobile robot. It is a smart car that realizes unmanned driving through a computer device. In actual applications, the self-driving vehicle relies on artificial intelligence, visual computing, radar, monitoring devices, and global positioning devices to cooperate, so that the computer equipment can automatically and safely operate the motor vehicle without any active human operation. Vehicles with cargo-carrying functions are cargo trucks, including dump trucks, tractor trucks, etc., which are mainly used to transport goods. Vehicles with engineering functions include excavators, bulldozers, road rollers, loaders, engineering rescue vehicles, etc.

In this embodiment, as shown in FIG2 , it is assumed that based on the current position O of the current vehicle, the path planning system obtains a road image and a traffic flow image within a circular range with the current position O as the center and a preset distance as the radius. The road data extracted from the road image includes the first lane D1, the second lane D2, the third lane D3, and the fourth lane D4, and the lane positions corresponding to the four lanes. The traffic flow data extracted from the traffic flow image 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.

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.

For example, in this embodiment, the database of the route planning system stores the second license plate information. The second license plate information includes C11, C41, C61 and C91. For ease of understanding, the first function is the automatic driving function as an example for explanation. That is, the vehicle corresponding to the second license plate information (C11, C41, C61 and C91) has the automatic driving function. The target license plate information matching the second license plate information (C11, C41, C61 and C91) is determined from the first license plate information (C11, C21, C31 and C41). The target license plate information is C11 and C41.

S300, determining the target vehicle according to the vehicle identity information, and obtaining the vehicle position matching the target vehicle.

In some embodiments, the routing system marks the vehicle that matches the target license plate information as the target vehicle. As described in step S200, the target license plate information is C11 and C41. The routing 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.

In this embodiment, the path planning system also stores the current position O, road data, and the vehicle position matching the target vehicle in the database of the current vehicle. Based on the data in the database, the path planning system subsequently performs path planning for the current vehicle.

Step S400, 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 O and the target position.

In some embodiments, the target position of the current vehicle is obtained, and an initial driving path is planned based on the current position O and the target position. Based on the vehicle position matching the target vehicle, the initial driving path is adjusted 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 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 real-time acquisition of the vehicle position matching the target vehicle, and obtain the planned driving path of the current vehicle to adapt to the ever-changing traffic conditions and plan a driving path with fewer target vehicles.

The path planning method for avoiding target vehicles of this application can obtain road images and traffic images from the current position O to the target position in real time based on the data acquisition device. After the road images and traffic images are processed and analyzed by image recognition technology, road data and traffic data can be obtained. Then the position of the target vehicle with the first function is extracted from the traffic data. The target vehicle with the first function is obtained in real time on the road within the preset range with the current position O as the center. Based on this, the planned driving path of the current vehicle is obtained. The road with more first-function vehicles is avoided as much as possible, thereby improving the safety of the driving process.

In some embodiments, the present application also discloses a path planning device 200 for avoiding a target vehicle. As shown in FIG3 , 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 used to acquire the current position O of the current vehicle in real time; the first determination module 220 is used to determine the road data and traffic data that match the current position O, wherein the road data and traffic data change with the change of the current position O, the road data at least includes one or more lanes and the lane position corresponding to each lane, and the traffic data at least includes the position of each lane. The vehicle identity information and vehicle position corresponding to the vehicle on the lane; the second determination module 230 is used to determine the target vehicle according to the vehicle identity information and obtain the vehicle position matching the target vehicle; the planning module 240 is used to obtain the target position of the current vehicle, and based on the vehicle position matching 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 used to store the current position O, road data and the vehicle position matching the target vehicle to the database of the current vehicle.

Please refer to Figure 4, which is a schematic diagram of the structure of the electronic device 100 provided in an embodiment of this application.

Specifically, the electronic device 100 includes a memory 20 and a processor 30, the memory 20 is used to store computer instructions, and the processor 30 is used to call the computer instructions in the memory 20, so that the electronic device 100 executes the steps of the path planning method for avoiding the target vehicle as described in the above embodiment.

Exemplarily, the computer instructions may be divided into one or more modules/units, one or more modules/units are stored in the memory 20, and executed by the processor 30. One or more modules/units may be a series of computer instruction segments capable of completing a specific function, and the instruction segments are used to describe the execution process of the computer instructions in the electronic device 100.

The electronic device 100 may be a computing device such as a desktop computer, a notebook, a handheld computer, an industrial computer, a tablet computer, a server, etc. A person skilled in the art may 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. The electronic device 100 may include more or fewer components than shown in the diagram, or may combine certain components, or may include different components. For example, the electronic device 100 may also include input and output devices, network access devices, buses, etc.

The processor 30 may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices 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.

The memory 20 can be used to store computer programs 40 and/or modules/units. The processor 30 implements various functions of the electronic device 100 by running or executing the computer programs 40 and/or modules/units stored in the memory 20 and calling the data stored in the memory 20. The memory 20 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data (such as audio data) created according to the use of the electronic device 100, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a 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 memory card (Flash Card), at least one disk memory device, a flash memory device, or other non-volatile solid-state memory devices.

This application also discloses a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed on the electronic device 100, the electronic device 100 executes the steps of the path planning method for avoiding the target vehicle as described in the above embodiment. The storage medium can be a U disk, a mobile hard disk, a read-only memory ROM, a random access memory RAM, a disk or an optical disk, and other media that can store program codes.

Ordinary technicians in this technical field should recognize that the specific embodiments described in this specification may have different names, and the above contents described in this specification are only examples of the structure of this application. All equivalent changes or simple changes made based on the structure, features and principles conceived in this application are included in the protection scope of this application. Technicians in the technical field to which this application belongs can make various modifications or supplements to the specific examples described or adopt similar methods, as long as they do not deviate from the structure of this application or exceed the scope defined by the claims of this application, they should all fall within the protection scope of this application.

S100, S200, S300, S400: Steps

Claims (10)

A path planning method for avoiding a target vehicle is applied to a current vehicle, which includes: obtaining the current position of the current vehicle in real time; determining road data and traffic data matching the current position, wherein the road data and the traffic data change with the change of the current position, the road data at least includes one or more lanes and the lane position corresponding to each lane, and the traffic data at least includes The 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; when the target vehicle is in front of the driving direction of the current 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. A path planning method for avoiding a target vehicle as described in claim 1, wherein determining the road data and traffic data that match the current position includes: obtaining the road data and traffic data within a circular range with the current position as the center and a preset distance as the radius. The path planning method for avoiding a target vehicle as described in claim 2, wherein the obtaining of road data and traffic data within a circular range with the current position as the center and a preset distance as the radius includes: obtaining an environmental image within a circular range with the current position as the center and a preset distance as the radius, wherein the environmental image includes a road image and a traffic image; extracting road data from the road image, and extracting traffic data from the traffic image. A path planning method for avoiding target vehicles as described in claim 3, wherein the extracting of traffic data from the traffic image comprises: Determining vehicle identity information matching the current position according to the traffic image, wherein the vehicle identity information comprises first license plate information; determining target license plate information matching the 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 indicate that the vehicle has an automatic driving function, a cargo function or an engineering function; determining the target vehicle from the vehicle identity information comprises: marking the vehicle matching the target license plate information as the target vehicle. A path planning method for avoiding a target vehicle as described in claim 1, wherein 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 in the database of the current vehicle. The path planning method for avoiding a target vehicle as described in claim 1, wherein the obtaining of 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, comprises: obtaining the target position of the current vehicle and planning an initial driving path based on the current position and the target position; adjusting the initial driving path in real time based on the vehicle position matching the target vehicle to obtain the planned driving path of the current vehicle. A route planning device, comprising: an acquisition module for acquiring the current position of the current vehicle in real time; a first determination module for determining road data and traffic data matching the current position, wherein the road data and the traffic data change with the change of the current position, the road data at least includes one or more lanes and the lane position corresponding to each lane, and the traffic data at least includes the vehicle identity information corresponding to the vehicle on each lane. and vehicle position, each of the vehicle identity information corresponds to each of the vehicle positions one by one; a second determination module is used to determine the target vehicle and the vehicle position matching the target vehicle from the vehicle identity information; a planning module is used to obtain the target position of the current vehicle when the target vehicle is ahead of the driving direction of the current vehicle, and obtain the planned driving path of the current vehicle based on the vehicle position matching the target vehicle, the current position and the target position. The route planning device as described in claim 7, further comprising: a storage module for storing the current position, the road data and the vehicle position matching the target vehicle in the database of the current vehicle. An electronic device, wherein the electronic device includes a processor and a memory, 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 as described in any one of claim 1 to claim 6. A computer-readable storage medium for storing a computer program, which, when executed on an electronic device, enables the electronic device to execute a path planning method for avoiding a target vehicle as described in any one of claim 1 to claim 6.

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