Urban Air Mobility

We present Vertiport-informed Surrogate-Based Optimization with Machine Learning Surrogates (VinS), a novel framework for solving the vertiport location problem for urban air mobility operations. The primary focus of this work is on the optimization of vertiport locations to facilitate efficient urban air transportation. Our framework helps choose not only the optimal vertiport locations but also the optimal number of vertiports. We develop a simulation model to analyze the impacts of various vertiport location configurations on the efficiency of the transportation network. To expedite the...

Variation and imbalance in demand poses significant challenges to Urban Air Mobility (UAM) operations, affecting strategic decisions such as fleet sizing. To study the implications of demand variation on UAM fleet operations, we propose a stochastic passenger arrival time generation model that uses real-world data to infer demand distributions, and two integer programs that compute the zero-spill fleet size and the spill-minimizing flight schedules and charging policies, respectively. Our numerical experiment on a two-vertiport network shows that spill in relatively inelastic to fleet size...

Most Level 3 airports around the world suffer severe congestion and flight delays. Airlines have to obtain airport slots in order to schedule flights at such airports. The main way for airlines to acquire slots is primary slot allocation, in which a slot coordinator distributes slots to airlines according to certain rules and regulations. Due to excessive demand for slots and restrictions on allocation rules, it is difficult for some airlines to obtain the desired slots in this manner. Another way for airlines to obtain slots is through secondary slot trading, in which slots can be...

Ground Delay Programs (GDPs) have been widely used to resolve excessive demand-capacity imbalances at arrival airports by shifting foreseen airborne delay to pre-departure ground delay. While offering clear safety and efficiency benefits, GDPs may also create additional delay because of imperfect execution and uncertainty in predicting arrival airport capacity. This paper presents a methodology for measuring excess delay resulting from individual GDPs and investigates factors that influence excess delay using regularized regression models. We measured excess delay for 1210 GDPs from 33 U.S...