Coordination of IVI and transit signal priority on transit evacuations.
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Coordination of IVI and transit signal priority on transit evacuations.

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      During an emergency evacuation, execution time is always critical to the evacuees who are transit dependent. Transit Signal Priority (TSP) can speed up the transit services by prioritizing the approaching bus at a signalized intersection. With the emergence of IntelliDrive (formerly known as IVI), which is a wireless communication technology used to transfer data among vehicles and infrastructures, a TSP system can obtain more accurate traffic data and react to the approaching bus in a wider area. This report proposes an adaptive TSP system to facilitate the transit-based emergency evacuation on the basis of the U.S. Department of Transportation (DOT)’s IntelliDrive initiative. The objective of this project is to study the TSP and IntelliDrive coordination and to evaluate the impacts of the proposed TSP strategies on the transit-based emergency evacuation. The emergency evacuation model consists of two optimization models: a TSP optimization model and a bus routing optimization model. The TSP optimization model includes bus travel time prediction and traffic signal optimization. The bus travel time prediction is used to estimate the bus arrival time at the intersection. The traffic signal optimization considers both the bus delay and the network-wide vehicle delay. It determines when and which TSP strategy will be applied. The principal inputs for the TSP optimization model are: bus speed, position, busload, queue length, and traffic signal status. The bus routing optimization model is proposed to optimize the transit vehicles allocation and routing. The Dijkstra Algorithm has been modified to find out the shortest paths among the pickup points and the shelters in the network. Additionally, a hybrid intelligence algorithm consisting of a Genetic Algorithm and a Hill Climbing Algorithm, which was developed under the sponsorship of a previous project, has been applied to solve the transit vehicle routing and allocation problem.
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