Identification of vulnerable transportation infrastructure and household decision making under emergency evacuation conditions
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This dissertation combines two primary problems under general disaster considerations. First, a methodology is presented to identify vulnerable transportation infrastructure, which is defined as the set of network links, the damage of which results in the maximum disruption of the network’s origindestination connectivity. The disrupting agent is permitted a limited number of resources with which to damage the network. The measure of disruption, resulting from the damage, is based on a given set of traffic conditions, the availability of alternate paths, and roadway design characteristics. A bi-level mathematical programming model represents the interaction of the traffic assignment and the disruption measure. This bi-level model allows the problem to be viewed as a game between an evil entity, who seeks to disrupt the network, and a traffic management agency that routes vehicles so as to avoid vulnerable links to the greatest degree possible while meeting origin-destination demands. The second problem is to mathematically describe household decision making behavior in an emergency evacuation. Traditional transportation network evacuation models have omitted a commonly observed sociological phenomenon – that families gather together before evacuating an area. This omission can lead to overly optimistic evacuation times, and the evacuation models fail to capture underlying traffic patterns that only arise during times of crises. Two linear integer programs are developed to model the decision making behavior; the first describes a meeting location selection process and the second assigns trip chains for drivers to pick up family members who may not have access to a vehicle. The mathematical programs are combined with a traffic assignment-simulation package for evacuation analysis. Interactions between the two problems are also explored. Evacuation conditions are examined when the traffic management agency routes traffic around vulnerable links. The impact of the unusual traffic patterns, that arise using the household decision making behavior evacuation model, is evaluated in terms of shifts in the relative vulnerability of the transportation links. Finally, the routing strategies are evaluated for extensions in network evacuation times.