Solution of Active Safety for Virtual Track Train Based on RRT* and MPC

Obstacle avoidance for Virtual Track Train (VTT) is a prominent focus in current research. This paper proposes a modular active safety solution for VTT, combining a path planning algorithm based on the Rapidly-exploring Random Tree Star (RRT*) with the Artificial Potential Field Method, a trajectory optimization algorithm using Bezier curves and a hierarchical path-tracking control algorithm based on model predictive control. The proposed solutions are validated using a real-time hardware-in-the-loop simulation platform. The results show that the proposed path planning algorithm reduces computation time by 23.97% and decreases path gradient by 13.56% compared to traditional RRT*. During simulation testing, the solution successfully plans and optimizes the obstacle avoidance path in 139 ms, achieving high tracking accuracy.