Patent Application
20250224244
The subject matter herein generally relates to vehicle automatic driver field.
With a development of automatic driver field, more and more special vehicles are appearing on the market, the special vehicle has special functions. The special vehicles may be autonomous vehicles, trucks, road clearing vehicles and so on.
While the technology development of the special vehicles is still being developed, items or goods carried by the special vehicles may be dangerous. Some special vehicles and consumer vehicles sharing the same traffic lanes, these special vehicles may cause road accidents and injuries to the consumer vehicles.
Implementations of the present disclosure will now be described, by way of embodiments, with reference to the attached figures.
It will be appreciated that for simplicity and clarity of illustration, where appropriate, reference numerals have been repeated among the different figures to indicate corresponding or analogous elements. In addition, numerous specific details are set forth in order to provide a thorough understanding of the embodiments described herein. However, it will be understood by those of ordinary skill in the art that the embodiments described herein can be practiced without these specific details. In other instances, methods, procedures, and components have not been described in detail so as not to obscure the related relevant feature being described. Also, the description is not to be considered as limiting the scope of the embodiments described herein. The drawings are not necessarily to scale, and the proportions of certain parts may be exaggerated to better illustrate details and features of the present disclosure. It should be noted that references to “an” or “one” embodiment in this disclosure are not necessarily to the same embodiment, and such references mean “at least one”.
Several definitions that apply throughout this disclosure will now be presented.
The connection can be such that the objects are permanently connected or releasably connected. The term “comprising,” when utilized, means “including, but not necessarily limited to;” it specifically indicates open-ended inclusion or membership in the so-described combination, group, series, and the like.
The path planning method is used for a path planning system. The path planning system can be installed in a vehicle. For example, the vehicle can be a household vehicle, a commercial vehicle, or an engineering vehicle.
In block S100, a current location of the vehicle is obtained in real time.
The vehicle can be a vehicle equipped with the path planning system.
In one embodiment, the vehicle is installed a data collection device. The data collection device can be an in-vehicle sensor, a radar, a camera, or a global locating system (GPS) and so on. The in-vehicle sensor detects close-range obstacles around the vehicle, such as distance perception data when the vehicle is parking. The radar detects locations and speeds of surrounding objects by emitting radio waves and measuring the radio waves' reflections. The camera captures some videos to identify other vehicles, pedestrians, road signs and traffic signals. The GPS obtains real-time locating information of vehicles and plans driving paths for vehicles.
In the embodiment, the path planning system obtains the current location of the current based on the data collection device, the data collection device is installed in the vehicle.
In block S200, road data and traffic flow data matched with the current location of the vehicle are determined, the road data and the traffic flow data are changed with the current location of the vehicle, the road data includes one or more lanes and a lane location corresponding to each lane, and the traffic flow data includes vehicle identify information and vehicle locations corresponding to vehicles in each lane.
In one embodiment, the path planning system obtains the road data and the traffic flow data in a circle centered on the current location of the vehicle and radiused by a preset distance. Refer to
Further, the path planning system obtains environment images in the circle centered on the current location of the vehicle and radiused by the preset distance, the environment images include road images and traffic flow images based on a camera installed in the vehicle. For example, the road images are some first images showing road condition in the circle centered on the current location of the vehicle and radiused by the preset distance, the first images can be photos or videos. The traffic flow images are some second images showing driving conditions of vehicles in the circle centered on the current location of the vehicle and radiused by the preset distance. Then, the path planning system extracts the road data from the road images and extracts the traffic flow data from the traffic flow images. In the embodiment, the environment images are analyzed using image recognition technology, and are extracted to obtain the road images and the traffic flow images.
The image recognition technology extracts and classifies the road images and the traffic flow images by constructing deep neural network model, based on deep learning algorithm. Firstly, a large amount of image data is input into a neural network for training, the neural network can accurately recognize different categories of images by constantly adjusting the network parameters. Then, the image to be recognized is input into the trained neural network, and the network will output category labels of the image to realize the automatic recognition of the image.
In one embodiment, the path planning system also needs to clean original data obtained by the data collection device, the data collection device includes the road data and the traffic flow data. The path planning system converts the original data into analyzable data by cleaning, correcting, formatting and organizing the road data and the traffic flow data. For example, the original data can be cleaned by missing value processing, noise data clearing and consistency checking. Redundant data or useless data in the road data and the traffic flow data is eliminated. A format of the traffic flow data and the road data is converted to a unified format. In the embodiment, the road data includes one or more lanes and lane location of each lane, the traffic flow data includes the vehicle identify information and the vehicle location corresponding to vehicles in each lane.
Specifically, the vehicle identify information matching with the current location O of the vehicle is determined based on the traffic flow images, the vehicle identify information includes first license plate information. Objective license plate information matching with second license plate information is determined from the first license plate information, the vehicle corresponding to the second license plate information includes a first function, the first function illustrates the vehicle with an automatic driving function, a cargo function, or an engineering function. In other embodiments, the first function can also be a road clearing function, a traction function, an engineering function, and other functions. In the embodiment, a vehicle with the autonomous driving function is an autonomous vehicle, a vehicle with the cargo function is a truck, the truck can be a dump truck or a traction truck, a vehicle with the engineering function is an excavator, a bulldozer, a road roller, a loader, or an engineering rescue vehicle.
Refer to
Further, the path planning system determines that a first license plate information of the first vehicle identity information corresponding to the first vehicle C1 is C11, determines that a first license plate information of the second vehicle identity information corresponding to the second vehicle C2 is C21, determines that a first license plate information of the third vehicle identity information corresponding to the third vehicle C3 is C31, and determines that a first license plate information of the fourth vehicle identity information corresponding to the fourth vehicle C4 is C41.
For example, in the embodiment, a database of the path planning system stores a second license plate information. The second license plate information includes C11, C41, C61, and C91. In order to facilitate understanding, the first function is token as the automatic driving function as an example. The vehicles with the second license plate information (C11, C41, C61 and C91) have automatic driving functions. The objective license plate information matching with the second license plate information (C11, C41, C61 and C91) is determined from the first license plate information (C11, C21, C31 and C41). The objective license plate information is C11 and C41.
In block S300, an objective vehicle is determined according to the vehicle identify information and a vehicle location of the objective vehicle is obtained.
In one embodiment, the path planning system marks the vehicle matching with the objective license plate information as the objective vehicle. For example, in block S200, the objective 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 objective vehicle, and the fourth vehicle C4 with the first license plate information C41 as the objective vehicle.
In one embodiment, the path planning system stores the current location of the vehicle, the road data and the vehicle location of the objective vehicle to a database of the vehicle. The path planning system plans a path of the vehicle based on the data in the database of the vehicle.
In block S400, an objective driving location of the vehicle and a planned driving path of the vehicle are determined based on the vehicle location of the objective vehicle, the current location and the objective driving location of the vehicle.
In some embodiments, the path planning system obtains the objective driving location of the vehicle and plans an initial driving path based on the current location and the objective driving location. The path planning system adjusts the initial driving path in real time to obtain the planned driving path of the vehicle based on the vehicle location matching the objective vehicle. In the embodiment, the path planning system plans the initial driving path from the current location O of the vehicle to the objective driving location. Then, as the vehicle travels, traffic flow status between the current location O and the objective driving location is constantly changing. The path planning system adjusts the initial driving path in real time to obtain the planned driving path of the vehicle based on the vehicle location matching with the objective vehicle. The path planning system can adapt to the changing traffic flow status and plan a path with fewer objective vehicles.
In some embodiments, firstly, the path planning method obtains the road video and the traffic flow video in real time from the current location O to the objective driving location based on the data collection device. Secondly, the path planning method can obtain the road data and the traffic flow data after processing and analyzing the road images and the traffic flow images by the image recognition technology. Then, the path planning method extracts the location of the objective vehicle with the first function from the traffic flow data. The path planning method obtains the objective vehicle with the first function on the road centered on the current location O and radiused by the preset distance. Finally, the planned driving path of the vehicle can be obtained to avoid the road containing more vehicles with the first function, the safety of the driving process is improved.
Please refer to
As shown in
In one embodiment, a non-transitory storage medium recording instructions is disclosed. When the recorded computer instructions are executed by a processor of an electronic device 20, the electronic device 20 can perform the method.
The embodiments shown and described above are only examples. Many details known in the field are neither shown nor described. Even though numerous characteristics and advantages of the present technology have been set forth in the foregoing description, together with details of the structure and function of the present disclosure, the disclosure is illustrative only, and changes may be made in the detail, including in matters of shape, size, and arrangement of the parts within the principles of the present disclosure, up to and including the full extent established by the broad general meaning of the terms used in the claims. It will therefore be appreciated that the embodiments described above may be modified within the scope of the claims.
| Number | Date | Country | Kind |
|---|---|---|---|
| 202410032959.7 | Jan 2024 | CN | national |
