A decision-support framework for emergency evacuation planning during extreme storm events

Md Golam Rabbani Fahad, Rouzbeh Nazari, Parth Bhavsar, Mohammad Jalayer, Maryam Karimi

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Developing an effective real-time evacuation strategy during extreme storm events such as hurricanes has been a topic of critical significance to the emergency planning and response community. The spatial and temporal variabilities of inland flooding during hurricanes present significant challenges for robust evacuation planning. In this study, a framework for real-time evacuation planning was developed that combines the results obtained from hydrodynamic modeling and traffic microsimulation. First, a fine-scale hydrodynamic model was developed based on depth-averaged 2D shallow-water equations (SWE) to obtain information pertaining to flood depth and velocity for planning evacuation routes during a storm event. Next, a traffic microsimulation was conducted using time-dependent information from the hydrodynamic model regarding the traffic velocities along evacuation routes during an event. An optimization technique was also implemented to reduce the overall travel time by about 6% from that of the base model. The last component of the framework involves combining the results from both models to generate a time-lapse animation of emergency evacuation based on a geographic information system (GIS). The results obtained using this framework could be easily accessed by the general public and decision-makers to enable efficient evacuation planning during extreme storm events.

Original languageEnglish (US)
Pages (from-to)589-605
Number of pages17
JournalTransportation Research Part D: Transport and Environment
StatePublished - Dec 2019

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Transportation
  • Environmental Science(all)


Dive into the research topics of 'A decision-support framework for emergency evacuation planning during extreme storm events'. Together they form a unique fingerprint.

Cite this