Exploring Urban Air Mobility Adoption Potential in San Francisco Bay Area Region: A Systems of Systems Level Case Study on Passenger Waiting Times and Travel Efficiency

TL;DR

This study evaluates the potential of Urban Air Mobility in the San Francisco Bay Area, showing that UAM can significantly reduce travel times and highlighting operational factors crucial for its adoption.

Contribution

It presents a systems-of-systems simulation model to assess UAM adoption, focusing on operational factors affecting efficiency and passenger experience.

Findings

UAM can reduce regional travel times by up to 80%.

Fleet size and turnaround time significantly impact waiting times.

Operational optimization is key for UAM acceptance.

Abstract

Urban Air mobility has gained momentum with recent advancements in the electric vertical take-off and landing (eVTOL) vehicles, offering faster point-to-point air taxi services that could help relieve traffic congestion in chronically overburdened cities. The research assesses the feasibility and systems-of-systems level adoption potential of UAM operations in the San Francisco Bay Area by comparing passenger departure, waiting, travel, and arrival times across key regional nodes, including San Francisco, Oakland, San Jose, and Palo Alto airports, with conventional ground transportation. A multi-agent simulation was developed in MATLAB to evaluate the fleet operations and to model demand arrival using a Poisson process under stochastic passenger flows and turnaround constraints. Results indicate that utilizing UAM during peak demand could reduce total travel times up to eighty percent across the region. The findings of this paper highlight the critical operational factors for fleet schedule optimization. Especially how the fleet size, passengers' request volumes, and turnaround time directly influence waiting time, operating cost, and overall user acceptance.