A reconstruction of Florida Traffic Flow During Hurricane Irma (2017)

TL;DR

This paper reconstructs Florida's traffic flow during Hurricane Irma using game theory and observational data, providing detailed insights into evacuation demand and congestion patterns to improve future emergency planning.

Contribution

It introduces a novel traffic reconstruction model based on game theory that utilizes limited observational data and social media validation to analyze evacuation dynamics.

Findings

Estimated 4 million cars participated in evacuation.

Reconstructed congestion patterns align with news and Twitter data.

Traffic demand peaked during specific hours of the evacuation.

Abstract

Recent Hurricane Irma (2017) created the most extensive scale of evacuation in Florida's history, involving about 6.5 million people on mandatory evacuation order and 4 million evacuation vehicles. 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 the game theory, this paper employs the available traffic observation on main highways (20 cameras; including parts of Route 1, 27 and I-75, 95, 4,10) during Irma to reconstruct the traffic flow in Florida during Irma. The model is validated with self-reported twitters. The traffic reconstruction estimates the traffic demand (about 4 million cars in total) and the temporal and spatial distribution of congestion during the evacuation. The results compare well with available information from news reports and Twitter records. The reconstructed data can be used to analyze hurricane evacuation decisions and travel behavior.