关键词: 城市空中交通, 电动垂直起降飞机, 碰撞规避, 机会约束, 运动规划

Abstract:

In the context of urban air traffic， there is currently no mature solution for real-time avoidance of electric Vertical Take-Off and Landing （eVTOL） aircraft in dynamic and uncertain environments. To address this challenge， we propose a risk-aware and efficient motion planning method for real-time eVTOL avoidance. The problem is formulated as a Model Predictive Control （MPC） framework with Chance Constraints MPC （CC-MPC）， incorporating both collision avoidance and geo-fencing constraints. To efficiently handle the chance constraints， we reformulate them using Big-M and confidence ellipsoids， transforming the CC-MPC problem into a Mixed-Integer Programming （MIP） problem. To efficiently solve the MIP， we employ an iterative convexification-based optimization method， complemented by a global search algorithm that serves as a front-end warm-start mechanism. Finally， all components are integrated within a receding horizon control framework to enable fast and dynamic trajectory generation for eVTOLs. Simulation experiments across various flight scenarios demonstrate the effectiveness of the proposed approach.

Key words: urban air traffic, eVTOL, collision avoidance, chance constraints, motion planning