Modeling driver behavior on urban streets

Ruili Wang, Mingzhe Liu, Ray Kemp, Min Zhou

Research output: Journal PublicationArticlepeer-review

10 Citations (Scopus)

Abstract

Traffic flow on straight roads is the most common traffic phenomenon in urban road traffic networks. In this paper, a realistic cellular automaton (CA) model is proposed to investigate driver behavior on urban straight roads based on our field observations. Two types of driver behavior, free and car-following, are simulated. Free driving behavior is modeled by a novel five-stage speeding model (two acceleration stages, one steady stage and two deceleration stages). Car-following processes are simulated by using 1.5-s as the average headway (1.5-s rule), which is observed in local urban networks. Vehicular mechanical restrictions (acceleration and deceleration capabilities) are appropriately reflected by a five-stage speeding model, which has the dual-regimes of acceleration and deceleration. A fine grid (the length of each cell corresponds to 1 m) is used. Our simulation results demonstrate that the introduction of the dual-regimes of acceleration and deceleration, 1.5-s rule and fine grid matches actual driver behavior well on urban straight roads.

Original languageEnglish
Pages (from-to)903-916
Number of pages14
JournalInternational Journal of Modern Physics C
Volume18
Issue number5
DOIs
Publication statusPublished - May 2007
Externally publishedYes

Keywords

  • Cellular automata
  • Driver behavior
  • Traffic flow
  • Urban traffic

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematical Physics
  • General Physics and Astronomy
  • Computer Science Applications
  • Computational Theory and Mathematics

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