A real-time trajectory planning approach for dynamic environments with dense obstacles

This study introduces an enhanced trajectory planning method for navigating dense environments containing both dynamic and static obstacles. A key innovation of the proposed approach is the improved calculation of the closest point of approach between two moving vehicles, which serves as a fundamental component of the suggested trajectory planning algorithm. One major advantage of this method is its ability to identify the shortest feasible path or to determine when no safe path exists under given constraints (e.g., minimum approach distance, vehicle speed). In addition, the algorithm effectively avoids local minima and operates with significantly lower computational requirements than machine learning–based methods, making it well suited for real-time applications.