Citation

Feng K, Lin N. Transp. Res. D Trans. Environ. 2022; 110: e103412.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.trd.2022.103412

PMID

unavailable

Abstract

Hurricane evacuation modeling is challenging due to a scarcity of evacuation data and the complexity of human decision-making and travel behavior. We build a system for rapidly predicting the hurricane evacuation traffic flow based on hurricane forecasting, evacuation orders, the road network, and population information. The system integrates an evacuation demand model, an origin-destination model, and a route choice model into a link flow-based mean-field traffic model. We evaluate and calibrate the model with traffic observations from Hurricane Irma (2017), which induced a massive evacuation and traffic congestions throughout Florida State. The model skillfully captures the spatial and temporal evacuation features, including peak traffic flows and daily traffic fluctuations. The model can be applied to support evacuation management. Our analysis shows that a minor adjustment to the evacuation order could considerably alleviate the traffic congestion during Hurricane Irma.

Language: en