Papers by sreeja kamishetty
Events during an emergency unfold in an unpredictable fashion which makes management of traffic d... more Events during an emergency unfold in an unpredictable fashion which makes management of traffic during emergencies pretty challenging. Furthermore, some vehicles would need to be evacuated faster than others e.g., emergency vehicles or large vehicles carrying a lot more people. The Prioritized Routing Assistant for Flow of Traffic (PRAFT) enables prioritized routing during emergencies. However, the PRAFT solution does not compute multiple plans that can help handle better dynamic nature of emergencies. PRAFT maps the prioritized routing problem to the Minimum-Cost Maximum-Flow (MCMF) problem, hence its solution can accommodate maximum flow while routing vehicles based on priority (maps higher priority vehicles to better quality routes (i.e., ones with minimum cost)). We build upon the PRAFT solution to make the following contributions: (a) Develop a Pareto Minimum-Cost Maximum-Flow (Pareto-MCMF) algorithm which can compute all the possible MCMF solutions. (b) Through a series of exp...
Traffic management during emergency evacuation throws up a different set of challenges than a reg... more Traffic management during emergency evacuation throws up a different set of challenges than a regular traffic management. We focus here on one particular challenge, namely prioritized routing. Prioritized routing may need to happen even during normal times but stands out during emergencies, since emergency vehicles, police vehicles and vehicles (such as buses) that carry a lot more people may need to have a higher priority in terms of evacuation. It is also reasonable to assume that traffic police may need to perform a centralized control of traffic since they typically have a global view of the emergency and possibly have accurate real-time updates. We therefore make the following contributions in this paper: (a) We map the prioritized routing problem to the minimum-cost maximum-flow problem, a standard problem formulation in network flow theory. (b) We then develop the Prioritized Routing Assistant for Flow of Traffic (PRAFT) that casts the prioritized routing problem which includ...
Towards a better management of urban traffic pollution using a Pareto max flow approach
Transportation Research Part D: Transport and Environment
Abstract Rising levels of air pollution is a major concern across many parts of the world. In thi... more Abstract Rising levels of air pollution is a major concern across many parts of the world. In this article, we develop a transportation policy to handle air pollution caused by the heavy flow of traffic in urban areas. In particular, we aim to distribute the traffic flow more evenly through a city, by developing a flow algorithm that computes multiple solutions, each of which accommodates the maximum flow. The paper makes the following contributions to build such a transportation policy: (a) Develops a Pareto-optimal Max Flow Algorithm (PMFA) to suggest multiple max flow solutions. (b) Introduces the notion of k-optimality into PMFA to ensure that the suggested pareto solutions are sufficiently distinct from each other – referred to as Pareto-k-optimal Max Flow Algorithm (k-PMFA). (c) Through a series of experiments performed using the well-known traffic simulator SUMO and by doing emission modeling on the New York map, we could show that our policy distributes the air pollution more uniformly across locations.
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Papers by sreeja kamishetty