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Local path planning method for unmanned driving based on equal-step sampling a* algorithm

A technology for local path planning and unmanned driving, which is applied in the directions of road network navigators, navigation, instruments, etc., and can solve the problems that the algorithm does not meet the constraints of vehicle kinematics and cannot be directly controlled by vehicles.

Active Publication Date: 2021-09-28
TIANJIN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Although the predecessors have proposed a variety of unmanned driving path planning algorithms, most of them do not satisfy the vehicle kinematics constraints and cannot be directly used for vehicle control, requiring a lot of processing work

Method used

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  • Local path planning method for unmanned driving based on equal-step sampling a* algorithm
  • Local path planning method for unmanned driving based on equal-step sampling a* algorithm
  • Local path planning method for unmanned driving based on equal-step sampling a* algorithm

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Embodiment Construction

[0056] The present invention adds the idea of ​​equal-step sampling into the local path planning strategy, and proposes a new cost function. The specific implementation steps are as follows:

[0057] Step 1: Define the search step size and search security domain;

[0058] The search step is defined as the distance the vehicle advances within a control period, so the calculation formula for the search step is:

[0059]

[0060] Among them, Step represents the search step size, l represents the accuracy of the raster image, v represents the current driving speed of the vehicle, and T represents the update time of the local path.

[0061] Due to the possibility of changing the direction of the vehicle, in order to ensure that every node in the path is safe, the circular safety domain is used to judge, and the radius of the circular domain is:

[0062]

[0063] Here L vehicle is the body length, and max( ) is the maximum value function. When the parent node of the current ...

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Abstract

The present invention belongs to the field of unmanned driving path planning. In order to meet the kinematic constraints and actual traffic restrictions of the car, the present invention, based on the equal-step sampling A* algorithm, the unmanned driving local path planning method, the specific steps are as follows: Step 1: Definition search Step size and search security area; Step 2: Determine the starting point and target point of path search in the local grid graph; Step 3: Establish the Open list and Closed list; Step 4: Solve the cost function of the grid points in the Open list; Step 5: Select the grid point with the smallest cost function value from the Open list; Step 6: Investigate all safe adjacent nodes of the current node; Step 7: Process that the current node has no child nodes during the search process; Step 8: Repeat Step 5 ‑7 process, until the condition is met, a feasible path is returned, or a search failure is returned. The present invention is mainly applied to unmanned driving road occasions.

Description

technical field [0001] The invention belongs to the field of unmanned driving path planning, and specifically relates to a path search algorithm using equal-step sampling and A* algorithm principles to perform local path planning for unmanned vehicles. Background technique [0002] With the development of society, people's requirements for quality of life are getting higher and higher, and cars have become an indispensable means of transportation for human life. However, the increase in the number of cars and the weak safety awareness of drivers themselves have led to a sharp increase in the incidence of global traffic accidents. Facing the increasingly serious traffic safety and traffic congestion problems, the task of building an intelligent transportation system has become more urgent. As a key part of building an intelligent transportation system, unmanned vehicles have attracted attention from all parties in recent years. Unmanned vehicles integrate multiple functions ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C21/34
CPCG01C21/3446
Inventor 王一晶刘正璇左志强
Owner TIANJIN UNIV
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