A Multi-Commodity Network Flow Approach for Optimal Flight Schedules for an Airport Shuttle Air Taxi Service

Abstract

A multi-commodity network flow framework for optimal flight scheduling of vehicles for an envisioned UAM airport shuttle air taxi service is presented. The framework includes a trip generation model that produces requests from individuals who are known to travel to and from the airport and are expected to benefit from a UAM airport shuttle service from a value of time perspective. Results demonstrate how the implemented framework can help to identify the fleet-size needed to meet a given user demand. The results also showcase strong couplings between population density, income distribution, location and number of ports of operations, number of the vehicles in the network, ticket price, and the cost of operations on operator profitability, suggesting that a holistic approach is necessary to establish a viable business case for an airport shuttle air taxi service.