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.