Risk-bounded and fairness-aware path planning for urban air mobility operations under uncertainty
Risk-bounded and fairness-aware path planning for urban air mobility operations under uncertainty
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DOI：
10.1016/j.ast.2022.107738
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发表时间：
2022-07
影响因子：
5.6
通讯作者：
Pengcheng Wu;Junfei Xie;Yanchao Liu;Jun Chen
中科院分区：
文献类型：
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作者：
Pengcheng Wu;Junfei Xie;Yanchao Liu;Jun Chen
避碰是飞行器在动态不确定城市环境下自主飞行的一个重要问题。针对多架电动垂直起降（eVTOL）飞机在这种环境下的飞行情况，提出了一种风险有界且具有公平性意识的路径规划算法。该算法将基于采样的路径规划方法与风险域公式相结合，针对多架垂直起降飞机生成对飞行器和环境不确定性都具有鲁棒性的随机安全保证无碰撞路径。为了解决自由飞行空域中不同eVTOLs之间的飞行公平性问题，引入了许可分配策略。本文提出的算法将风险域公式引入到基于采样的路径规划中，采用许可分配策略，既继承了基于采样方法的计算优势，又保证了每个时间步都有一个随机可行的飞行区域。仿真研究证明了该算法的良好性能。
Collision avoidance is an important issue in the field of the autonomous operations of aerial vehicles in dynamic and uncertain urban environments. This paper introduces a risk-bounded and fairness-aware path planning algorithm for multiple electrical vertical take-off and landing (eVTOL) aircraft operating in such environments. This algorithm advances the sampling-based path planning with the risk domain formulation to generate stochastically safety assured collision-free paths that are robust to both vehicle and environmental obstacle uncertainties for multiple eVTOL aircraft. To address the concern of flight fairness between different eVTOLs in the free flight airspace, the strategy of permit assignment is introduced. By incorporating the risk domain formulation into the sampling-based path planning with the strategy of permit assignment, the algorithm proposed in this paper not only inherits the computational advantage of the sampling-based methods, but also guarantees a stochastically feasible flying zone at every time step. Simulation studies demonstrate the promising performance of the proposed algorithm.