Fair-CoPlan: Negotiated Flight Planning with Fair Deconfliction for Urban Air Mobility

Abstract

Urban Air Mobility (UAM) is an emerging transportation paradigm in which Uncrewed Aerial Systems (UAS) autonomously transport passengers and goods in cities. The UAS have different operators with different, sometimes competing goals, yet must share the airspace. We propose a negotiated, semi-distributed flight planner that optimizes UAS' flight lengths {\em in a fair manner}. Current flight planners might result in some UAS being given disproportionately shorter flight paths at the expense of others. We introduce Fair-CoPlan, a planner in which operators and a Provider of Service to the UAM (PSU) together compute \emph{fair} flight paths. Fair-CoPlan has three steps: First, the PSU constrains take-off and landing choices for flights based on capacity at and around vertiports. Then, operators plan independently under these constraints. Finally, the PSU resolves any conflicting paths, optimizing for path length fairness. By fairly spreading the cost of deconfliction Fair-CoPlan encourages wider participation in UAM, ensures safety of the airspace and the areas below it, and promotes greater operator flexibility. We demonstrate Fair-CoPlan through simulation experiments and find fairer outcomes than a non-fair planner with minor delays as a trade-off.