Citation

Feng K, Lin N. Transp. Res. D Trans. Environ. 2021; 94: 102788.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.trd.2021.102788

PMID

unavailable

Abstract

Hurricane evacuation has long been a difficult problem perplexing local government. Hurricane Irma in 2017 created the most extensive scale of evacuation in Florida's history, involving about 6.5 million people in a mandatory evacuation order and an estimated 4 million evacuation vehicles. Traffic jams emerged in mid-Florida and rapidly spread to involve the entire state. To understand the hurricane evacuation process, the spatial and temporal evolution of the traffic flow is a critical piece of information, but it is usually not fully observed. Based on game theory, this paper employs the available traffic observation of main highways to reconstruct the traffic flow on all highways in Florida during Irma. The reconstructed traffic conditions compare well with those simulated by dynamic models while the reconstruction model is computationally much cheaper to use. Validation with smartphone data further confirms that the reconstruction model captures the traffic conditions for real evacuation processes. The reconstructed data show that the evacuation rates for 5 representative cities -- Key West, Miami, Tampa, Orlando, and Jacksonville-- in Florida were about 90.1%, 38.7%, 52.6%, 22.1%, and 7%, respectively. The peak evacuation traffic flows from Tampa and Miami arrived in the Orlando region at almost the same time, triggering the catastrophic congestion through the entire state. Also, the evacuation for Hurricane Irma was greater than that predicted by an evacuation demand model developed based on previous event and survey data. The detailed evacuation traffic flow reanalysis accomplished in this article lays a foundation for studying evacuation demand as well as developing evacuation management policies.

Language: en

Keywords

Hurricane evacuation; Large scale congestion; Traffic demand model