Hierarchical Path Planning for Urban On-Demand Air Mobility

On-demand air mobility has gained attention in the recent years as a promising future transportation mode for daily commutes. In this paper, we propose a hierarchical motion planning system for on-demand passenger-carrying air vehicles. Specifically, we consider a path planning problem with requirements for flight efficiency, system safety, and passenger comfort. Prior to the execution of the mission, we simplify a given city map into a grid world and estimate the transfer time among the cells in the presence of no-fly zones and air traffic congestion. Then, we consider system reachability and apply A∗ search to find a time-optimal path in the map. To ensure that the system follows a feasible trajectory consistent with the off-line plan after take-off, we use model predictive control to track the waypoints on the path and minimize the energy consumption during flight. In order to account for collisions unforeseen in off-line planning, we further adopt a collision avoidance module in the system, which optimizes a new waypoint near the predicted collision point and generates an avoidance trajectory through model predictive control. At last, we demonstrate the effectiveness of the hierarchical planning system under different flight scenarios in a simulated urban environment.