Modeling of Incident-Induced Capacity Loss for Hurricane Evacuation Simulation

Yuan Zhu1, Kaan Ozbay2, Kun Xie3, Hong Yang4

  • 1Inner Mongolia University
  • 2NYU
  • 3University of Canterbury
  • 4Old Dominion University

Details

14:00 - 14:15 | Mon 28 Oct | Crystal Room I | MoE-T5.1

Session: Special Session on Big Data and Emerging Technologies for Traffic Safety Improvement (III)

Abstract

Modeling and simulation of hurricane evacuation is an important task in emergency planning and management. One typically ignored factor that affects the development of a reliable evacuation model is the uncertainty caused by the incident-induced capacity loss. Lately, the impact of incidents on evacuation has drawn increasingly attention among researchers and practitioners, but few of them thoroughly investigated it using the real data in the modeling and simulation context. This study aims to investigate the impact of various types of incidents on modeling and simulation of hurricane evacuation. Particularly, the incidents that occurred under actual hurricane conditions are examined and their impact on the capacity loss is modeled. The developed incident frequency and duration models are incorporated into the network assignment model to study traffic conditions under hurricane Sandy in New York. Results show that the consideration of incident-induced capacity loss can greatly change the outcome of the evacuation model. Our findings suggest the need to include a well calibrated and validated traffic incident generation module for modeling and simulating hurricane evacuation.