A passing probability model for intelligent transportation system

Hsun-Jung Cho*, Rih Jin Li

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Intelligent transportation system (ITS) uses electronic technologies such as information and communication technologies to improve the efficiency of transportation management. In the theoretical framework of gas-kinetic traffic flow model, the probability of capable passing is essential for ITS. The probability of capable passing is assumed be a linear function of the traffic concentration, indicating that the probability of capable passing decreases proportionally with an increasing concentration. This work improves the model by introducing the speed desired by the driver into the original two-lane cellular automata (CA) model. This study also examines the accuracy of the linearity assumption. A capable passing principle is established to simulate the capable passing probability for different concentrations and can be embedded in a system on chip of ITS.

Original languageEnglish
Title of host publicationComputation in Modern Science and Engineering - Proceedings of the International Conference on Computational Methods in Science and Engineering 2007 (ICCMSE 2007)
Pages1005-1008
Number of pages4
Edition2
DOIs
StatePublished - 1 Dec 2007
EventInternational Conference on Computational Methods in Science and Engineering 2007, ICCMSE 2007 - Corfu, Greece
Duration: 25 Sep 200730 Sep 2007

Publication series

NameAIP Conference Proceedings
Number2
Volume963
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

ConferenceInternational Conference on Computational Methods in Science and Engineering 2007, ICCMSE 2007
CountryGreece
CityCorfu
Period25/09/0730/09/07

Keywords

  • Capable passing
  • Cellular automata
  • Gas-kinetic model
  • Intelligent transportation system

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