Mission Planner Algorithm for Urban Air Mobility – Initial Performance Characterization

In this paper, an initial characterization was performed of the Mission Planner algorithm developed by NASA for Urban Air Mobility (UAM) operations research. The algorithm plans conflict-free trajectories for flights to support a given set of UAM passenger trips. The UAM trips are planned in an on-demand, first-come, first-served manner, such that any given trip is subject to the constraints imposed by previously planned trips. For this analysis, the mission planning algorithm considered only the trajectory constraints from previously-planned trips in one test condition and added vertiport constraints for the second test condition. The conflict and constraint resolution strategies used by the Mission Planner were characterized by their percentage contribution to planning iterations, their percentage effectiveness in those iterations, and their contributions to the departure delay applied to each UAM trip’s flight. With the exception of the climb and descent vertical speed strategies, most strategies showed reasonable or good performance in all test scenarios. In the test condition with vertipad constraints enabled, both the total number of iterations executed, and the number of flights that required planning iterations, was reduced for all scenarios. This was the result of the natural conditioning of the traffic achieved with scheduling and the additional information available to the Mission Planner from the vertiport scheduler. The next steps for this work will include improvements to the mission planning strategies and analyses with additional constraints and under other demand scenarios.