Transportation System Modeling and Simulation Lab (TranSMS Lab)

Highlighted Research in Advanced Air Mobility
Urban Air Mobility (UAM) is an emerging concept proposed in recent years by utilizing electric vertical take-off and landing vehicles (eVTOLs), which 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. Advanced Air Mobility (AAM) moves people and cargo between places previously not served or underserved by aviation – local, regional, intraregional, urban – using revolutionary new aircraft, information technologies, and CNSI in low altitude airspace.

This study examines the network design of UAM on-demand service, 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 (demand estimation), and vertiport access- and egress-mode choices while considering the interactions between vertiport locations and potential UAM travel demand. https://doi.org/10.1016/j.eng.2020.11.007.

We propose an Automated Flight Planning System (AFPS) that could be employed by PSUs. In the AFPS, a Low-Altitude Airspace Management System (LAMS) is proposed to automatically generate a route network with the capability of avoiding obstacles and obstructions in low-altitude airspace. Given the requests of flight operations, i.e., origin, destination, departure time, the Low-Altitude Traffic Management System (LTMS) will design pre-departure conflict-free 4D trajectories and provide flexibilities of en-route maneuvering by taking system cost and equity among operators into consideration. https://doi.org/10.1016/j.trc.2021.103324.

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Other Highlights

Dr. Yu Zhang's study "Design of Automated Advanced Air Mobility Flight Planning System" (co-PI: Hualong Tang) received Amazon Research Awards 2020. https://www.amazon.science/research-awards/program-updates/2020-amazon-research-awards-recipients-announced.

Congratulations to Tingting Zhao, PhD, and Yu Zhang, PhD, for the US Patent 11,321,648 issued on May 3rd, 2022 about a comprehensive method to categorize and plan restoration of key transportation infrastructure after natural disaster.