![]() ![]() Transportation Research Part B: Methodological, Elsevier, vol. " Modeling hurricane evacuation behavior using a dynamic discrete choice framework," Quality & Quantity: International Journal of Methodology, Springer, vol. " Earthquake triggered networked risk and response: based on relevant literature," Networks and Spatial Economics, Springer, vol. " Heterogeneity Within and Across Households in Hurricane Evacuation Response," " Joint modeling of evacuation departure and travel times in hurricanes," " A model evaluating effect of disaster warning issuance conditions on “cry wolf syndrome” in the case of a landslide,"Įuropean Journal of Operational Research, Elsevier, vol. ![]() Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer International Society for the Prevention and Mitigation of Natural Hazards, vol. " Highway congestion during evacuation: examining the household’s choice of number of vehicles to evacuate," Praveen Maghelal & Xiangyu Li & Walter Gillis Peacock, 2017." Analyzing Evacuation Versus Shelter‐in‐Place Strategies After a Terrorist Nuclear Detonation," Wein & Youngsoo Choi & Sylvie Denuit, 2010. " A Method for Formulizing Disaster Evacuation Demand Curves Based on SI Model," These are the items that most often cite the same works as this one and are cited by the same works as this one. Additionally, communities with stronger ties improve evacuation performance. ![]() Results indicate that significant improvement in evacuation performance can be achieved in scenarios where evacuee social networks have short average path lengths and topologically influential evacuees do not belong to the high risk regions. A detailed experimental analysis of various inhibitor selection strategies and their effectiveness on different social network topologies and risk distribution is performed. We derive closed form expressions for average travel time for ER random network. The performance of an evacuation is measured by both average travel time of the population and total evacuation time of the high risk evacuees. We find that the performance of an evacuation process can be improved by forcing a small subset of evacuees (inhibitors) in the low risk area to delay their departure. We propose a probabilistic evacuee departure time model incorporating both evacuee individual characteristics and the underlying evacuee social network. In this work, we study an evacuation scenario consisting of a high risk region and a surrounding low risk area. One of the reasons for correlated evacuee departures is higher perceived risk of threat spread through social contacts. We are especially interested in cases when evacuees subject to little or no risk of exposure evacuate along with evacuees subject to higher risk of threat (also known as shadow evacuation). Simultaneous departures of evacuees can lead to overloading of road networks causing congestion. One of the important factors affecting evacuation performance is the departure time choices made by evacuees. ![]()
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