Abstract
One of the most challenging tasks for truck drivers is maneuvering the truck-trailer system in different parking scenarios. This article presents a novel path planning approach for truck-trailer parking, where a realistic and deterministic parking behavior model, Iterative Analytical Method (IAM), is proposed and combined with Closed-Loop Rapidly Exploring Random Tree (CL-RRT) approach in a cascade path planning. Cascade path planning approach combining CL-RRT with the iterative analytical method (IAM) mimicking real-world parking practice enables the generation of both kinematically feasible and deterministic parking maneuvers with obstacle avoidance. For evaluation, different parking scenarios are generated and selected through a developed case generation tool. The performance of the proposed path planning approach is evaluated through MATLAB simulations. The results achieved a noticeable success with a high rate of generated feasible maneuvers for parking.
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