A simulation modeling framework for community-wide evacuation planning
ABSTRACT Simulation is a useful and cost effective tool for evacuation planning. However, extensive data collection and preparation
is necessary to build a traffic evacuation simulation model that can closely replicate real life conditions. In a community-wide
evacuation process during an emergency, which covers hundreds of miles, input data related to simulation of traffic evacuations
include (1) Traffic and roadway geometry, (2) Geographic distribution of the affected area, (3) Travel demand modeling, and
(4) Behavioral analysis of potential evacuees. This paper presents a framework for preparing simulation inputs and ultimately
developing a simulation model. Brief excerpts from a case study on the evacuation of Charleston, South Carolina are also included.
An accurate input analysis is very important to the success of a simulation project since without correct input data, the
output of a simulation cannot contribute to more effective decision making. This paper presents a simple and efficient methodology
for data preparation regarding a large scale city evacuation simulation involving long distance trips.
KeywordsLong distance evacuation–Arrival rate–Data input–Simulation–Evacuation–At-risk population
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ABSTRACT: This paper presents a new framework for managing congestion during emergency evacuations. The algorithm allows a long link of the network to be used as a buffer to keep the traffic flow moving in. Concurrently, a detour trigger time is estimated to keep the traffic under-saturated in the buffer zone and minimize the total travel time. The integration algorithm presented in this paper is an efficient mathematical solution for travel time cost calculation. A case study is presented to demonstrate the efficacy of the traffic demand buffering strategy developed in this research for managing the evacuation flow.Transportation Research Part E Logistics and Transportation Review 05/2012; 48(3-3):684-700. DOI:10.1016/j.tre.2011.12.002 · 2.27 Impact Factor