学术海报2: Modeling multimodal transportation network emergency evacuation considering evacuees’ cooperative behavior
Dr. Xia (Sarah) Yang is currently an Assistant Professor of Civil Engineering at SUNY Polytechnic Institute. She received her B.S. in Railway Transportation Engineering and M.S. in Traffic and Transportation Planning and Management from Central South University in China, and her Ph.D. in Transportation Engineering from Rensselaer Polytechnic Institute in US.
Dr. Xia (Sarah) Yang’s primary research interests include transportation network modeling and simulation, evacuation modeling and planning, machine learning and statistical modeling, freight demand modeling and economics, and railway timetable optimization. She worked around 10 research projects funded by NSF, USDOT, UTRC2, and World Bank during her doctoral and postdoctoral research at Rensselaer Polytechnic Institute (RPI). She was the recipient for the 2017 Franz Edelman Finalist Award for her efforts on GPS data analysis and urban freight performance evaluation in the “Off-Hours Delivery (OHD) Project in New York City”. Her PhD dissertation on evacuation modeling and planning was presented at the most distinguished conference in traffic engineering ISTTT22. She is also a reviewer for around 10 international research journals.
Modeling emergency evacuation could help reduce losses and damages from disasters. In this paper, based on the system optimum principle, we develop a multimodal evacuation model that considers multiple transportation modes and their interactions, and captures the proper traffic dynamics including the congestion effects, the cooperative behavior of evacuees, and the capacities of the transportation system and the shelters. We further develop a Method of Successive Average (MSA)-based sequential optimization algorithm for large-scale evacuations. Both the proposed model and the solution algorithm are tested and validated through a set of numerical tests on a small network, and a detailed case study on the Lower Manhattan network. The results of the paper can provide insight on modeling flow interactions of different transportation modes and useful guidance on developing evacuation strategies to reduce the system evacuation time and losses from disasters.