Probabilistic model of traffic breakdown with random propagation of disturbance for ITS application

Bongsoo Son, Taewan Kim, Hyung Jin Kim, Soobeom Lee

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

8 Scopus citations

Abstract

In this paper, a probabilistic model of vehicular traffic breakdown applicable to Intelligent Transportation Systems (ITS) is presented. When traffic demand exceeds freeway capacity, the so-called breakdown occurs and the congestion begins. While preventing the breakdown is a major concern of traffic operation, the mechanism of breakdown is not thoroughly explained and most of the research regarding traffic breakdown rely on empirical analysis. To further our understanding of traffic breakdown, this paper explains the phenomenon of traffic breakdown in terms of random propagation of traffic disturbance and proposes a probabilistic model of breakdown. A Monte-Carlo simulation is also conducted to investigate the characteristics of the proposed model.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsMircea Gh. Negoita, Robert J. Howlett, Lakhmi C. Jain
PublisherSpringer Verlag
Pages45-51
Number of pages7
ISBN (Print)9783540232056
DOIs
StatePublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3215
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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