Date of Graduation

7-2021

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Engineering (PhD)

Degree Level

Graduate

Department

Electrical Engineering

Advisor/Mentor

Samir M. El-Ghazaly

Committee Member

James M. Rankin

Second Committee Member

Jingxian Wu

Third Committee Member

Cynthia Sides

Fourth Committee Member

Jeff Dix

Keywords

Air Traffic Management, Civil Aviation, Flying Cars, Monte Carlo, On-Demand Mobility, Urban Air Mobility

Abstract

The research conducted in this dissertation is focused on developing a simulation tool that can predict the traffic flow patterns of the Urban Air Mobility vehicles to alleviate some of the challenges related to their traffic management. First, an introduction to the concept of Urban Air Mobility is given, the usage of Automatic Dependent Surveillance-Broadcast systems for Urban Air Mobility vehicles is suggested and dynamic addressing concept is introduced as an answer to a part of air traffic management and address scarcity challenge for Urban air Mobility vehicles. Next, in order to simulate the traffic flow patterns of the Urban Air Mobility vehicles, a Monte-Carlo-based simulation tool is developed, and the simulation results are analyzed for two different cases. These results lead to the proper observation window for the simulations and a solution to determine the approximate number of addresses needed to accommodate the desired number of Urban Air Mobility vehicles, which would be a solution for the address scarcity problem of the Urban Air Mobility vehicles.

Furthermore, multiple scenarios of different policies, flexibilities, and their impact on the distribution of the number of active Urban Air Mobility vehicles throughout the day are observed. Results show that decreasing the maximum allowed flight duration in the busy periods of the day is proved to reduce the number of active Urban Air Mobility vehicles. Also, the effect of static and dynamic denials is observed and concluded that the static-denial approach alleviates the traffic faster, but the dynamic denial alternative is more fair, equitable, and adaptable as it offers the clients the option to be waitlisted. Overall, the dynamic-denial approach offers better customer service compared to the static one, and the price adjustment case is the most effective and flexible approach. Moreover, three different scenarios are introduced to observe the cases where the Urban Air Mobility vehicles are able to make both inter-city and intra-city trips. The three scenarios are focused on inter-city cases and consist of cases where the inter-city travelers (1) release their address at the border, (2) keep their addresses while crossing the border, and (3) use a shared address pool. The developed analysis tool using the Monte-Carlo simulation technique predicts the results and the outcomes of the three scenarios are compared using the introduced figures of merit. According to the observations, each scenario has its own advantages and possible limitations. Based on the situation, the air traffic management can examine the options and develop the most suitable policy.

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