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A Two-level Agent-Based Model for Hurricane Evacuation in New Orleans.

Authors :
Wei Liang
Nina S.-N. Lam
Xiaojun Qin
Wenxue Ju
Source :
Journal of Homeland Security & Emergency Management; Jun2015, Vol. 12 Issue 2, p407-435, 29p, 1 Diagram, 2 Charts, 4 Graphs, 5 Maps
Publication Year :
2015

Abstract

Mass evacuation of urban areas due to hurricanes is a critical problem in emergency management that requires extensive basic and applied research. Previous research uses agent-based models to simulate individual vehicle and driver behavior, and is limited mostly to a small study area due to the complexity of the models and the computational time needed. To better understand evacuation behavior, simulating the evacuation traffic in a larger region is needed. This paper develops a two-level regional disaster evacuation model by coupling two agent-based models. The first model uses each census block centroid, weighted with its corresponding number of vehicles, as an agent to simulate the local road network traffic. The second model, developed on the platform of a commercial software program called VISSIM, treats each vehicle as an agent to simulate the interstate highway traffic. This two-level agent-based model was used to simulate hurricane evacuation traffic in New Orleans. Validation results with the real Hurricane Katrina's evacuation data confirm that the proposed model performs well in terms of high model accuracy (i.e., close agreement between the real and simulated traffic patterns) and short model running time. The modeling results show that the average root-mean-square error (RMSE) for the three major evacuation directions was 347.58. Under a simultaneous evacuation strategy, and with 240,251 vehicles in 17,744 agents (census blocks), it would take at least 46.3 hours to evacuate all residents from the New Orleans metropolitan area. This two-level modeling approach could serve as a practical tool for evaluating mass evacuation strategies in New Orleans and other similar urban areas. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15477355
Volume :
12
Issue :
2
Database :
Complementary Index
Journal :
Journal of Homeland Security & Emergency Management
Publication Type :
Academic Journal
Accession number :
109223564
Full Text :
https://doi.org/10.1515/jhsem-2014-0057