Intelligent Decision-Making and Trajectory Planning of Semi-Trailer Trains Under Multi-Vehicle Interference

Semi-trailer trains are the main force of highway freight. In a complex environment with multiple vehicles, accidents are easily caused by complex structures and driver operation problems. Intelligent technology is urgently needed to improve safety. In view of the shortcomings of existing research on its dedicated models and algorithms, this paper studies the intelligent decision-making and trajectory planning of semi-trailer trains under multiple vehicles. A local trajectory planning method based on global path planning and Frenet coordinate decoupling based on the improved A* algorithm is proposed. The smooth weight transition function and B-spline curve are introduced to optimize the global path. The polynomial function is combined with the acceleration rate to optimize the local trajectory. TruckSim, Prescan and Simulink are used to build a joint simulation platform for multi-condition verification. The simulation results show that the search efficiency of the improved A* algorithm is improved by 12.2%, and the local path planning meets the real-time and safety requirements. The algorithm in the joint simulation can enable the semi-trailer train to perform operations correctly under multiple vehicles, providing theoretical and technical support for improving its safety and traffic efficiency in complex traffic environments.