Abstract
Efficient traffic management during disaster evacuations is an essential component of intelligent transport systems in smart cities. In a natural disaster, a surge of vehicles from dense residential areas may simultaneously move towards the same nearest safe shelter following a shortest path for each individual vehicle, thereby often leading to congestion and resulting in increased evacuation time. In this paper, we consider time-optimal traffic distribution in such disastrous situations considering a Manhattan grid network of roads. Several research results on optimal-time traffic distribution in such a network exist in the literature, all of which consider a restricted scenario of a single safe destination at a corner point of the grid. In contrast, we describe a technique for minimizing average travel time of the vehicles assuming a general situation as experienced in real-life, where the destination node can be anywhere on a rectangular \(m \times n\) grid network with multiple sources of traffic injection. Simulation results using SUMO on a road network of Manhattan borough of New York city show that our proposed technique outperforms the existing techniques on dynamic traffic assignment in terms of average travel time.
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Sarma, S.S., Sinha, B.P., Sinha, K. (2022). Efficient Traffic Routing in Smart Cities to Minimize Evacuation Time During Disasters. In: Bapi, R., Kulkarni, S., Mohalik, S., Peri, S. (eds) Distributed Computing and Intelligent Technology. ICDCIT 2022. Lecture Notes in Computer Science(), vol 13145. Springer, Cham. https://doi.org/10.1007/978-3-030-94876-4_13
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DOI: https://doi.org/10.1007/978-3-030-94876-4_13
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