TY - JOUR
T1 - A decision-support framework for emergency evacuation planning during extreme storm events
AU - Fahad, Md Golam Rabbani
AU - Nazari, Rouzbeh
AU - Bhavsar, Parth
AU - Jalayer, Mohammad
AU - Karimi, Maryam
N1 - Funding Information:
This publication was supported by a grant from the U.S. Department of Transportation, Office of the Secretary of Transportation (OST), Office of the Assistant Secretary for Research and Technology; a grant from the New Jersey Department of Community Affairs (NJDCA) from the Superstorm Sandy Community Development Block Grant Disaster Recovery (CDBG-DR); and a grant from the National Science Foundation through IUSE Grant no. DUE 1610911. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the USDOT, OST, NJDCA, CDBG-DR, and/or NSF.
Funding Information:
This publication was supported by a grant from the U.S. Department of Transportation, Office of the Secretary of Transportation (OST), Office of the Assistant Secretary for Research and Technology; a grant from the New Jersey Department of Community Affairs (NJDCA) from the Superstorm Sandy Community Development Block Grant Disaster Recovery (CDBG-DR); and a grant from the National Science Foundation through IUSE Grant no. DUE 1610911. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the USDOT, OST, NJDCA, CDBG-DR, and/or NSF.
PY - 2019/12
Y1 - 2019/12
N2 - 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.
AB - 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.
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U2 - 10.1016/j.trd.2019.09.024
DO - 10.1016/j.trd.2019.09.024
M3 - Article
AN - SCOPUS:85073562783
VL - 77
SP - 589
EP - 605
JO - Transportation Research, Part D: Transport and Environment
JF - Transportation Research, Part D: Transport and Environment
SN - 1361-9209
ER -