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An Obstacle Avoidance Path Planning and Evaluation Method for Intelligent Vehicles Based on the B-Spline Algorithm.
Zhang, Yulong; Wang, Pengwei; Cui, Kaichen; Zhou, Hengheng; Yang, Jinshan; Kong, Xiangcun.
Afiliação
  • Zhang Y; School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255022, China.
  • Wang P; School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255022, China.
  • Cui K; School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255022, China.
  • Zhou H; School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255022, China.
  • Yang J; School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255022, China.
  • Kong X; School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255022, China.
Sensors (Basel) ; 23(19)2023 Sep 28.
Article em En | MEDLINE | ID: mdl-37836981
ABSTRACT
To meet the real-time path planning requirements of intelligent vehicles in dynamic traffic scenarios, a path planning and evaluation method is proposed in this paper. Firstly, based on the B-spline algorithm and four-stage lane-changing theory, an obstacle avoidance path planning algorithm framework is constructed. Then, to obtain the optimal real-time path, a comprehensive real-time path evaluation mechanism that includes path safety, smoothness, and comfort is established. Finally, to verify the proposed approach, co-simulation and real vehicle testing are conducted. In the dynamic obstacle avoidance scenario simulation, the lateral acceleration, yaw angle, yaw rate, and roll angle fluctuation ranges of the ego-vehicle are ±2.39 m/s2, ±13.31°, ±13.26°/s, and ±0.938°, respectively. The results show that the proposed algorithm can generate real-time, available obstacle avoidance paths. And the proposed evaluation mechanism can find the optimal path for the current scenario.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article