Active obstacle avoidance based on an improved dynamic window approach for off-axis full trailer vehicles

Full trailers are at a significant risk of collision since the local planning algorithm for regular passenger cars does not completely account for the entire trailer system. To address this issue, a refined dynamic window approach (DWA) is proposed specifically for off-axis full trailer systems to enable proactive obstacle avoidance for unmanned full trailer systems on unstructured roads. Initially, the sampling of the towing vehicle’s speed constructs a velocity vector space. The motion paths of both vehicles are then forecasted using the kinematic model of the system and the data that were sampled. Subsequently, introducing sub-cost functions related to the target point’s position, an evaluation function tailored to the trailer system is proposed. Finally, the optimal velocity is selected based on the evaluation function to ensure the system safely reaches the target point. Experimental results demonstrate the method’s reliable safety in obstacle avoidance tasks, with a minimum distance of 0.83 meters between the towing vehicle and obstacle boundaries in real vehicle experiments, and 0.89 meters for the full trailer from obstacle boundaries.