Paper
6 February 2022 Research on path planning of vehicle dynamic obstacle avoidance based on improved RRT algorithm
Jinhong Ma, Jie Luo, Hao Li, Jinmin Hu
Author Affiliations +
Proceedings Volume 12081, Sixth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2021); 120812Q (2022) https://doi.org/10.1117/12.2624006
Event: Sixth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2021), 2021, Chongqing, China
Abstract
In view of the situation that the traditional path planning algorithms have the disadvantages of local optimal solution or the generated path is not smooth, on the one hand, this paper combines Artificial Potential Field with Rapidly Randomexploring Trees to improve the efficiency of path planning and solve the problem of local optimal solution; on the other hand, in order to ensure that the algorithm can be used in vehicle obstacle avoidance, the calculation formula of safe distance to obstacles is modified to make the obstacle avoidance process conform to vehicle driving behavior. At the meanwhile, in the exploring rules of RRT algorithm, vehicle dynamics constraints are added to make the path smooth and meet the maximum steering limit. In addition, driving distance information is added to each node of the path to deal with dynamic obstacles. Finally, the simulation results show that the path planned by this method can guide the vehicle to avoid dynamic obstacles smoothly.
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Jinhong Ma, Jie Luo, Hao Li, and Jinmin Hu "Research on path planning of vehicle dynamic obstacle avoidance based on improved RRT algorithm", Proc. SPIE 12081, Sixth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2021), 120812Q (6 February 2022); https://doi.org/10.1117/12.2624006
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KEYWORDS
Detection and tracking algorithms

Computer simulations

Roads

Unmanned aerial vehicles

Mobile robots

Algorithms

Genetic algorithms

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