Vertiport Planning for Urban Aerial Mobility: An Adaptive Discretization Approach

Abstract

Electric vertical-takeoff-and-landing (eVTOL) vehicles enable Urban Aerial Mobility (UAM). This paper optimizes the number, locations and capacities of vertiports in UAM systems, while capturing interdependencies between strategic vertiport deployment, tactical operations and passenger demand. The model includes a “tractable part” (based on mixed-integer second-order conic optimization) but also a non-convex demand function We develop an exact algorithm that approximates non-convex functions with piece-wise constant segments, iterating between a conservative model (which yields a feasible solution) and a relaxed model (which yields a solution guarantee). We propose an adaptive discretization scheme that converges to a global optimum—thanks to the relaxed model. Our algorithm converges to a 1% optimality gap, dominating static discretization benchmarks in terms of solution quality, runtimes and solution guarantee. We find that the most attractive structure for UAM is one that uses a few high-capacity vertiports, consolidating operations primarily to serve long-distance trips. Moreover, UAM profitability is highly sensitive to network planning optimization and to customer expectations, perhaps even more so than to vehicle specifications. Therefore, the success of UAM operations requires not only mature eVTOL technologies, but also tailored analytics-based capabilities to optimize strategic planning and market-based efforts to drive customer demand.

Speaker

Dr Kai WANG is currently an Assistant Professor at the School of Vehicle and Mobility at Tsinghua University. He was a Research Scientist at Heinz College, Carnegie Mellon University, and a Postdoctoral Associate at Sloan School of Management, Massachusetts Institute of Technology. Dr Wang’s research spans large-scale, stochastic, and data-driven optimization, with primary applications in smart transportation and logistics systems. His research has tackled a wide range of real-world problems, spanning vehicle routing, shared mobility, urban logistics, aerial mobility, and smart cities. His research has appeared in top-tier journals such as Operations Research, Management Science, Manufacturing & Service Operations Management, Transportation Science, Transportation Research Part B, etc. It has been recognized with several academic distinctions, e.g. INFORMS 2021 TSL (Transportation Science & Logistics) Society Best Paper Award, INFORMS 2021 AAS (Aviation Applications Section) Best Paper Award, Best Paper Award in the Applied Track from the 15th INFORMS Workshop on Data Mining and Decision Analytics (2020), etc.