Graduation Year

2023

Document Type

Dissertation

Degree

Ph.D.

Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Civil and Environmental Engineering

Major Professor

Yu Zhang, Ph.D.

Committee Member

Robert Bertini, Ph.D.

Committee Member

Hadi Gard, Ph.D.

Committee Member

Xiaopeng Li, Ph.D.

Committee Member

Seckin Ozkul, Ph.D.

Keywords

Advanced Air Mobility, EVTOL, Mathematical Modeling, GIS Tool, Simulation Tool

Abstract

Urban air mobility (UAM) is an emerging concept proposed in recent years that uses electric vertical take-off and landing vehicles (eVTOLs). UAM is expected to offer an alternative way of transporting passengers and goods in urban areas with significantly improved mobility by making use of low-altitude airspace. Considering the high capital investment of eVTOLs and relative high fee of using UAM passenger service, a viable UAM format is shared passenger service. Such a service is usually station-based, i.e., with vertiport located in popular sites where potential passengers can access. To understand the viability of such use cases, the vertiport owners and shared UAM service providers would like to know the possible optimal locations of siting the vertiports and how much traffic the service could attract. For stakeholders from public sector, they would like to know the impacts of the shared UAM service, e.g., change of system-wide generalized travel cost, benefit distribution of the service.

This study aims to answer these questions. It first examines the network design of a shared UAM service and diverted demand from existing ground transportation, with a particular focus on the use of integer programming and a solution algorithm to determine the optimal locations of vertiports, user allocation to vertiports, and vertiport access- and egress-mode choices while considering the interactions between vertiport locations and travels’ mode choice decisions. A case study based on simulated disaggregate travel demand data of the Tampa Bay area in Florida, USA was conducted to demonstrate the operability and effectiveness of the proposed model.

The outcomes of the case study reveal that although the percentage of trips that switched from ground mode to multimodal UAM was small, users choosing the UAM service benefited from significant time saving. In addition, sensitivity analysis is conducted to measure the impact of different parameters on the diverted demand of UAM service and system performance. The parameters tested include the number of vertiports, intermodal connection effectiveness (transfer time between ground and air modes), and different pricing strategies. The combined effects of the number of vertiports and pricing strategies are also analyzed.

Then, we develop an agent-based simulation tool to simulate the operations of a shared UAM service system. The three agents simulated are vertiport, eVTOL, and passenger. The operating rules of eVTOLs and the interactions between different agents are pre-established, but can be adjusted according to the interests of stakeholders. The inputs of the simulation tool include vertiport network, eVTOL features, passenger arrival process to vertiports. and demand OD matrix. The simulation tool can be used to evaluate the performance of the system, e.g., the passenger load factor of eVTOLs, travel time and waiting time of passengers, vertiport utilization etc. The simulation tool can also identify potential bottlenecks of the system where lacks of eVTOls, take-off-and-landing pads, or charging pads.

Shared UAM services operate from stations (i.e., vertiports), involve pooling, and require charging to ensure uninterrupted operations. It is more complicated than existing sharing mobilities, such as bike sharing, e-scooter sharing, one-way car sharing. Also, rebalancing eVTOLs could be more costly than rebalancing bikes/e-scooters, or cars. Thus, the last part of the dissertation is to improve the simulation tool to explore how to configure the UAM network (i.e., aircraft fleet size and vertiport capacity) or to change the level of service requirement to serve more passenger demand. Scenario analysis is performed to understand the impacts of different parameters to the performance of the system.

In summary, the dissertation research explores the future shared UAM service from vertiport network design, demand estimation, as well as system configuration by adopting mathematical modeling and simulation approaches. The findings from this study offer in-depth planning, operational and managerial insights for governmental decision-makers, original equipment manufacturers (OEMs) and service providers of UAM operations.

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