Title: Operations of Modular Transit Vehicles under Oversaturated Traffic

Abstract: Dynamic capacity design holds promise for reducing the energy consumption of urban mass transit systems, e.g., urban rail transits, bus rapid transits, shared autonomous vehicles. In this study, we investigate the joint design problem of dispatch headway and vehicle capacity for a transit system under oversaturated traffic. Two optimization models are proposed to solve a shuttle problem from both microscopic and macroscopic views, respectively. The first model is a mixed integer linear programming model that can yield exact solutions to the optimal design with a customized dynamic programming (DP) algorithm. The second model is a continuum approximation (CA) model that presents a macroscopic view of the system and yields simple analytical rules into the optimal design. It decomposes the original problem into unit-time revised unsaturated problems that can be analytically solved in each neighborhood across the operational horizon. With numerical experiments, we show that the discrete model can produce exact solutions with relatively expensive computation costs while the CA model offers near-optimum solutions with acceptable errors very efficiently. We also demonstrate that our proposed joint design strategy is effective in various shuttle systems (i.e. urban rail transits, shared autonomous vehicles) and conduct sensitivity analysis to reveal managerial insights into how the effectiveness of joint design strategy varies with input parameters. The discrete model is further extended to a multi-stop corridor system with dynamic multi-OD passenger demand. In this extended model, we propose a novel method of modeling complex multi-OD passenger queues in a parsimonious form and utilizes advanced parallel computing to solve the problem efficiently.

Bio: Dr. Xiaopeng Li is currently an associate professor and the Susan A. Bracken Faculty Fellow in the Department of Civil and Environmental Engineering at the University of South Florida (USF). His major research interests include network shared mobility, connected and autonomous traffic control, striving for integrating macroscopic time-space network modeling with microscopic vehicle trajectory control. Prior to joining USF, he worked at Mississippi State University as an assistant professor of transportation engineering. He is a recipient of a National Science Foundation (NSF) CAREER award. He has published 41 peer-reviewed journal papers. He has been the PI or a co-PI for multiple federal and state research projects, including four sponsored by NSF. He serves as a member on the Transportation Network Modeling Committee (ADB30) and the Traffic Flow Theory and Characteristics (AHB45) of the Transportation Research Board (TRB). He is on the editorial boards for Transportation Research Part B and Pat C and an Associate Department Editor for IIE Transactions Focused Issue on Operations Engineering and Analytics.