Unmanned local path planning method based on equal-step sampling A* algorithm

A technology for local path planning and unmanned driving. It is applied in the directions of road network navigators, measuring devices, instruments, etc. It can solve the problems that the algorithm does not meet the constraints of vehicle kinematics and cannot be directly used for vehicle control, so as to reduce the mechanical wear and tear of vehicles. The effect of reducing computational complexity and smoothing the path

Active Publication Date: 2018-08-24
TIANJIN UNIV
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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 no...

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  • Unmanned local path planning method based on equal-step sampling A* algorithm
  • Unmanned local path planning method based on equal-step sampling A* algorithm
  • Unmanned local path planning method 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 invention belongs to the field of unmanned path planning, and discloses an unmanned local path planning method based on equal-step sampling A* algorithm in order to meet the kinematic constraintsand actual traffic restrictions of automobiles. The method concretely comprises the following steps: 1, defining a search step size and a search security domain; 2, determining the starting point andthe target point of path search in a local grid map; 3, creating an Open list and a Closed list; 4, solving the cost functions of grid points in the Open list; 5, selecting the grid point with the lowest cost function value from the Open list; 6, respectively investing all security neighbor nodes of current nodes; 7, performing no sub-node processing on the current nodes in the search process; and8, repeating step 5 to step 7 until conditions are met, and returning to a feasible path or to search fail. The method is mainly applied to unmanned roads.

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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IPC IPC(8): G01C21/34
CPCG01C21/3446
Inventor 王一晶刘正璇左志强
Owner TIANJIN UNIV
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