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Research on Path Planning Algorithm for Driverless Vehicles

Author

Listed:
  • Hao Ma

    (School of Information Science and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China)

  • Wenhui Pei

    (School of Information Science and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China)

  • Qi Zhang

    (School of Control Science and Engineering, Shandong University, Jinan 250061, China
    State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China)

Abstract

In a complex environment, although the artificial potential field (APF) method of improving the repulsion function solves the defect of local minimum, the planned path has an oscillation phenomenon which cannot meet the vehicle motion. In order to improve the efficiency of path planning and solve the oscillation phenomenon existing in the improved artificial potential field method planning path. This paper proposes to combine the improved artificial potential field method with the rapidly exploring random tree (RRT) algorithm to plan the path. First, the improved artificial potential field method is combined with the RRT algorithm, and the obstacle avoidance method of the RRT algorithm is used to solve the path oscillation; The vehicle kinematics model is then established, and under the premise of ensuring the safety of the vehicle, a model predictive control (MPC) trajectory tracking controller with constraints is designed to verify whether the path planned by the combination of the two algorithms is optimal and conforms to the vehicle motion. Finally, the feasibility of the method is verified in simulation. The simulation results show that the method can effectively solve the problem of path oscillation and can plan the optimal path according to different environments and vehicle motion.

Suggested Citation

  • Hao Ma & Wenhui Pei & Qi Zhang, 2022. "Research on Path Planning Algorithm for Driverless Vehicles," Mathematics, MDPI, vol. 10(15), pages 1-14, July.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:15:p:2555-:d:869226
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    References listed on IDEAS

    as
    1. Qingying Ge & Aijuan Li & Shaohua Li & Haiping Du & Xin Huang & Chuanhu Niu & Yuanchang Liu, 2021. "Improved Bidirectional RRT ∗ Path Planning Method for Smart Vehicle," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-14, May.
    2. Jia, Yanfeng & Qu, Dayi & Song, Hui & Wang, Tao & Zhao, Zixu, 2022. "Car-following characteristics and model of connected autonomous vehicles based on safe potential field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
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    Cited by:

    1. Yujie Li & Longzhao Huang & Jiahui Chen & Xiwen Wang & Benying Tan, 2023. "Appearance-Based Gaze Estimation Method Using Static Transformer Temporal Differential Network," Mathematics, MDPI, vol. 11(3), pages 1-18, January.

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