4.7 Article

Congestion analysis of unsignalized intersections: The impact of impatience and Markov platooning

期刊

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
卷 273, 期 3, 页码 1026-1035

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ejor.2018.09.049

关键词

Queuing; Unsignalized intersection; Gap acceptance with impatience; Stochastic capacity analysis; Markov platooning

资金

  1. NWO Gravitation project NETWORKS [024.002.003]

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This paper considers an unsignalized intersection used by two traffic streams. The first stream of cars is using a primary road, and has priority over the other stream. Cars belonging to the latter stream cross the primary road if the gaps between two subsequent cars on the primary road are larger than their critical headways. A question that naturally arises relates to the capacity of the secondary road: given the arrival pattern of cars on the primary road, what is the maximum arrival rate of low-priority cars that can be sustained? This paper addresses this issue by considering a compact model that sheds light on the dynamics of the considered unsignalized intersection. The model, which is of a queueing-theoretic nature, reveals interesting insights into the impact of the user behavior on the capacity. The contributions of this paper are threefold. First, we introduce a new way to analyze the capacity of the minor road. By representing the unsignalized intersection by an appropriately chosen Markovian model, the capacity can be expressed in terms of the solution of an elementary system of linear equations. The setup chosen is so flexible that it allows us to include a new form of bunching on the main road that allows for dependence between successive gaps, which we refer to as Markov platooning; this is the second contribution. The tractability of this model facilitates studying the impact that driver impatience and various platoon formations on the main road have on the capacity of the minor road. Finally, in numerical experiments we observe various surprising features of the aforementioned model. (C) 2018 Elsevier B.V. All rights reserved.

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