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- W3129436161 abstract "Intelligent transport systems provide great possibilities to mitigate traffic congestion and intensify driving efficiency. The design of these systems requires a clear understanding of traffic dynamics. In this respect, this study focuses on describing and analysing traffic conditions at junctions in urban environments from a macroscopic level of description. As a first step, our method attempts to interpret the traffic scenario at intersections as a queuing system. Then, a Continuous Time Markov Chain to predict the future traffic condition at intersections is developed, and afterwards the pertaining steady-state probabilities are obtained. Given the equilibrium vector, significant performance measures are inferred for monitoring and planning purposes." @default.
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- W3129436161 date "2020-12-01" @default.
- W3129436161 modified "2023-09-25" @default.
- W3129436161 title "Continuous Time Markov Chain Traffic Model for Urban Environments" @default.
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- W3129436161 doi "https://doi.org/10.1109/globecom42002.2020.9348256" @default.
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