Optimization-based Collision Avoidance Algorithm for Urban Air Mobility through Dynamic Programming

초록

In this study, we propose a collision avoidance algorithm for Urban Air Mobility (UAM). The proposed algorithm uses Dynamic Programming (DP) techniques to optimize trajectory planning and collision avoidance strategies. The algorithm includes a dynamic and adaptive framework that can effectively manage a variety of unpredictable urban airspace scenarios. Through a comprehensive analysis of the surrounding environment, the algorithm formulates collision avoidance decisions by considering the state of the aerial vehicle. By utilizing DP, the algorithm optimally balances the trade-off between minimizing collision risk and ensuring efficient path planning. The effectiveness of the proposed algorithm is tested in various environments at urban areas. These tests demonstrate its ability to manage complex airspace scenarios. The results show a significant reduction in collision risk while maintaining acceptable path efficiency, compared to other collision avoidance algorithms. © 2024 Institute of Navigation.