Moving Horizon path planning for intelligent vehicle oriented to dynamic obstacle avoidance

• Published in: 2022 6th CAA International Conference on Vehicular Control and Intelligence (CVCI) pp. 1 - 6
• Main Authors: Han, Jiaqi, Cui, Maoyuan, Lv, Ying, Liu, Kewang, Dai, Qikun, Guo, Hongyan
• Format: Conference Proceeding
• Language: English
• Published: IEEE 28.10.2022
• Subjects: Autonomous Vehicle; Dynamics; Dynamics Obstacle Avoidance; Intelligent vehicles; Path planning; Predictive models; Stability analysis; Turning; Wheels
• DOI: 10.1109/CVCI56766.2022.9965184

In urban conditions, the road environment is very complex and the vehicle itself has strong nonlinearity, which makes the decision and control of obstacle avoidance path planning very challenging. To solve the problem of difficult vehicle path planning, this paper proposes a method for path planning that combines artificial potential fields with model predictive control. Drawing on the concept of virtual force field, the virtual force field and model prediction are organically combined by abstracting the force field function as the optimization objective, which can realize the modeling of dynamic environment through virtual force field and consider the multi-task and multi-objective problems in path planning through model prediction. At the same time, the state changes of both the obstacle vehicle and the main vehicle are predicted, and a good path planning effect can be achieved in the low-speed dynamic environment. The simulation results indicate that the method can complete the path planning for static and dynamic obstacles and ensure the safety and stability of the vehicle.