A Conceptual Framework for Assessing Congestion and Its Impacts

Jennie Lioris (), Alexander Kurzhanskiy () and Pravin Varaiya ()
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Jennie Lioris: École des Ponts-ParisTech
Alexander Kurzhanskiy: California PATH
Pravin Varaiya: University of California, Berkeley

A chapter in Applied Simulation and Optimization 2, 2017, pp 3-41 from Springer

Abstract: Abstract In urban areas, intersections are the main constraints on road capacity while traffic flows do not necessarily directly conform to the speed-flow relationship. It is rather the signal timing and the interplay between the clearing rate of each intersection which determines the formation and duration of congestion. Junctions often differ in their design and throughput. General conclusions on the relationship between vehicle speed and traffic flows on a junction link are rarely possible. Well-adapted models are required for a comprehensive study of the behaviour of each intersection as well for the interactions between junctions. This chapter assesses the potential benefits of adaptive traffic plans for improved network management strategies, under varying traffic conditions. Queueing analysis in association with advanced simulation techniques reveal congestion mitigation actions when the pre-timed actuation plan is replaced by the max-pressure feedback control. The case of unpredicted local demand fluctuation is studied, where uncontrolled congestion is progressively propagated to the entire network under the open-loop policy. Travel-time variability is measured under both plans and within all traffic schemes while frequency of stop-and-go actions are also encountered. Reliability of predictable trip durations is a major factor to be considered when ensuring “on time” arrivals and the related costs when the time is converted into benefits.

Keywords: Traffic responsive signal; Adaptive control; Pre-timed control; Max-pressure practical policy; Discrete event simulation; Performance evaluation; Queueing network model (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/978-3-319-55810-3_1

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