Citation

Alam MDJ, Habib MA. Transp. Res. Rec. 2019; 2673(10): 225-238.

Copyright

(Copyright © 2019, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/0361198119848409

PMID

unavailable

Abstract

This study develops an integrated microsimulation-based evacuation model that performs a vulnerability assessment of the Halifax Peninsula, Canada during an evacuation. The proposed framework of vulnerability assessment accounts for long-term changes in neighborhood composition in relation to socio-demographic characteristics, residential locations, and vehicle ownership. The results of a large-scale urban systems model and a flood risk model are used to inform the vulnerability assessment. The urban systems model encapsulates long-term household decisions and life stage transitions in measuring social vulnerability. The flood risk model provides information on flood severity and finer network disruptions. In addition, a dynamic traffic assignment-based microsimulation model is developed to assess mobility vulnerability during an evacuation. One of the key contributions of this study is that it utilizes a Bayesian Belief Network modeling approach for vulnerability assessment, while addressing uncertainty and causal relationships between different elements of vulnerability. The results suggest that the Peninsula zones are at a relatively higher risk from a mobility point of view. A sensitivity analysis reveals that clearance time has been found to be the key determinant of the mobility vulnerability during an evacuation. "Presence of female" and "presence of seniors" are found as the two most significant contributors of social vulnerability. Several peripheral zones are at a higher risk because of their proximity to the flood source. The proposed research will help emergency professionals and engineers to develop effective evacuation plans in relation to vulnerable areas.

Language: en