Network Modeling of Hurricane Evacuation Using Data Driven Demand and Incident Induced Capacity Loss Models

Modeling and simulation of hurricane evacuation is an important task in emergency planning and management. There are two major issues that affect development of a reliable evacuation model. The first one is how to estimate evacuation demand based on socio-economic characteristics, and the second one is how to deal with the uncertainty due to the roadway capacity loss as a result of highway incidents. Either of these factors can affect the planning of optimal evacuation routes due to their spatial-temporal impact on evacuation demand and the roadway network capacity. This study constructs a scenario-based hurricane evacuation methodology for New York City (NYC) Metropolitan area. In the model, hourly travel demand is generated and distributed to hours following a response curve estimated using empirical data obtained from observed traffic flows prior to landfall of Hurricane Sandy. The study also 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 were examined and their impact on the capacity loss was modeled. The developed incident frequency and duration models were incorporated into the evacuation model used to study traffic conditions under hurricane Sandy in New York City. The results are shown to be consistent with the predictions of the developed evacuation model and observed sensor based travel times as well as zone to zone trip times of NYC taxi data.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ABR30 Standing Committee on Emergency Evacuations. Alternate title: Network Modeling of Hurricane Evacuation Using Data-Driven Demand and Incident-Induced Capacity Loss Models
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Zhu, Yuan
    • Ozbay, Kaan
    • Xie, Kun
    • Yang, Hong
    • Morgul, Ender Faruk
  • Conference:
  • Date: 2016

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Maps; References; Tables;
  • Pagination: 21p
  • Monograph Title: TRB 95th Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01590050
  • Record Type: Publication
  • Report/Paper Numbers: 16-3138
  • Files: TRIS, TRB, ATRI
  • Created Date: Feb 9 2016 9:19AM