Event Details

PhD candidate Hao Wu will present a seminar to the Management Science Department

Abstract: This research presents a multi-objective optimization framework for incremental siting of capacitated vertiports that integrates real land use data and aims to maximize generalized cost savings while minimizing infrastructure costs and emissions. The multi-phased siting framework uniquely facilitates the gradual evolution of UAM operations from initial electric vertical takeoff and landing vehicles (eVTOLs) to more advanced modular flying vehicles (MFVs). This phased technological progression provides a practical pathway toward fully operational flying cars while ensuring feasible infrastructure adaptability across these transitions. Applied to the Munich metropolitan area, the framework demonstrates that multi-phased siting, particularly a 4-phased strategy, yielding about 131.5 thousand euros higher daily net profits. Specifically, compared to base single-phased approach, the 4-phased strategy delivers substantial marginal improvements across key metrics for an exemplary operating day: 13 thousand euros in generalized travel cost savings, 15 tons in emissions reductions, and a 0.9% increase in UAM mode share. Beyond four phases, the benefits diminish relative to increased complexity. A full factorial analysis examining capacity constraints and infrastructure costs reveals that ignoring either factor leads to impractical outcomes - unconstrained capacity results in demand exceeding 60-fold capacity, while disregarding infrastructure costs generates negative net profits due to overinvestment. The analysis identifies an optimal infrastructure cost subsidy range of 20–40%, balancing performance gains with economic sustainability. These findings enable integrated planning that effectively balances operational efficiency, system-wide environmental externalities, and economic viability through optimized cost allocation and phased investment strategies.

Bio: Hao Wu received the dual B.Sc. degrees in Software Engineering and Transportation Engineering in China in 2018, and the M.Sc. degree in Transportation Planning and Operation from Technical University of Berlin in 2022. He is currently pursuing his Ph.D. in Transportation Systems Engineering at Technical University of Munich (TUM), Germany, under the supervision of Prof. Dr. Constantinos Antoniou. His research interests include UAM infrastructure optimization, demand-responsive transport systems, agent-based simulation, travel behavior modeling, and sustainable transportation.