Research on Obstacle Avoidance Strategy for Intelligent Electric-driven Heavy-duty Vehicle Considering Dynamic Characteristics

With the improvement of advanced sensing technologies and intelligent control methods, autonomous vehicles are considered as the preferred solution to reduce the operating burden of drivers and the occurrence of traffic accidents. The intelligence of heavy-duty vehicles is necessary due to operation complexity and accident impact range. We investigate the motion control of intelligent electric-driven heavy-duty vehicles in the obstacle avoidance process under complex scenes. Then, an obstacle avoidance strategy architecture integrating path planning and trajectory tracking control is proposed, based on the improved artificial potential field (APF) and adaptive model predictive control (AMPC)-incremental PID algorithm. A co-simulation platform based on Prescan and Simulink is constructed to demonstrate that the strategy can provide a safe obstacle avoidance trajectory and achieve stable tracking.