Modeling of Incident-Induced Capacity Loss for Hurricane Evacuation Simulation

Yuan Zhu, Kaan Ozbay, Kun Xie, Hong Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publication2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages613-618
Number of pages6
ISBN (Electronic)9781538670248
DOIs
StatePublished - Oct 2019
Event2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 - Auckland, New Zealand
Duration: Oct 27 2019Oct 30 2019

Publication series

Name2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019

Conference

Conference2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
Country/TerritoryNew Zealand
CityAuckland
Period10/27/1910/30/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Management Science and Operations Research
  • Instrumentation
  • Transportation

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