Stochastic modeling of traffic flow breakdown phenomenon: Application to predicting travel time reliability

Jing Dong*, Hani S. Mahmassani

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

This paper presents a modeling approach in generating random flow breakdowns on congested freeways and capturing subsequent wave propagation among heterogeneous drivers. The approach is intended for predicting travel time variability caused by such stochastic phenomena. It is assumed that breakdown may occur at different flow levels with some probability and would sustain for a random duration. This is modeled at the microscopic level by considering speed changes that are initiated by a leading vehicle and propagated by the following vehicles with correlated-distributed behavioral parameters. Numerical results from a Monte Carlo simulation demonstrate that the proposed stochastic modeling approach produces a realistic macroscopic traffic flow behavior and can be used to generate travel time distributions.

Original languageEnglish (US)
Article number6247508
Pages (from-to)1803-1809
Number of pages7
JournalIEEE Transactions on Intelligent Transportation Systems
Volume13
Issue number4
DOIs
StatePublished - 2012

Keywords

  • Car-following model
  • Monte Carlo simulation
  • duration model
  • flow breakdown probability
  • heterogeneous drivers
  • travel time reliability

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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