Fleet Size and Spill for UAM Operation under Uncertain Demand

TL;DR

This paper investigates how demand variability impacts fleet sizing and operational spill in Urban Air Mobility, proposing stochastic demand modeling and optimization methods to improve fleet management under uncertainty.

Contribution

It introduces a stochastic demand model based on real data and two integer programming approaches for fleet sizing and scheduling to minimize spill in UAM operations.

Findings

Spill is relatively insensitive to fleet size.

Demand imbalance is the main driver of spill.

Proposed models help optimize fleet and schedule under demand uncertainty.

Abstract

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 and that the driving factor behind spill is the imbalance in demand.