Passenger-Centric Urban Air Mobility: Fairness Trade-Offs and Operational Efficiency

TL;DR

This paper introduces novel algorithms for urban air-taxi operations that optimize efficiency, safety, and passenger satisfaction while addressing fairness issues and resource sharing in urban air mobility.

Contribution

It presents the first scalable methods for air-taxi operation, incorporating passenger-centric service differentiation and energy-efficient routing to improve performance and fairness.

Findings

Algorithms outperform state-of-the-art commercial solvers.

Passenger-centric approach enhances service quality.

Identifies fairness issues in air-taxi operations.

Abstract

Urban Air Mobility (UAM) has the potential to revolutionize transportation. It will exploit the third dimension to help smooth ground traffic in densely populated areas. To be successful, it will require an integrated approach able to balance efficiency and safety while harnessing common resources and information. In this work we focus on future urban air-taxi services, and present the first methods and algorithms to efficiently operate air-taxi at scale. Our approach is twofold. First, we use a passenger-centric perspective which introduces traveling classes, and information sharing between transport modes to differentiate quality of services. This helps smooth multimodal journeys and increase passenger satisfaction. Second, we provide a flight routing and recharging solution which minimizes direct operational costs while preserving long term battery life through reduced energy-intense recharging. Our methods, which surpass the performance of a general state-of-the-art commercial solver, are also used to gain meaningful insights on the design space of the air-taxi problem, including solutions to hidden fairness issues.