Modeling and Simulation of Unconventional Traffic Circles

Microscopic simulation tools have been gaining popularity among traffic engineers. Enhanced input–output capabilities of these simulation tools allow engineers to model and to simulate complex transportation networks and to gather results relatively quickly. However, extensive validation and calibra...

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Bibliographic Details
Published inTransportation research record Vol. 1965; no. 1; pp. 201 - 209
Main Authors Bartin, Bekir, Ozbay, Kaan, Yanmaz-Tuzel, Ozlem, List, George
Format Journal Article
LanguageEnglish
Published Los Angeles, CA SAGE Publications 2006
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Summary:Microscopic simulation tools have been gaining popularity among traffic engineers. Enhanced input–output capabilities of these simulation tools allow engineers to model and to simulate complex transportation networks and to gather results relatively quickly. However, extensive validation and calibration efforts are required to verify the credibility of the results of these simulation models. This paper deals with the development of credible and valid simulation models of two unconventional traffic circles in New Jersey, namely, the Collingwood and Brooklawn Circles. These two circles are modeled in PARAMICS simulation software. Model development and the validation and calibration steps are presented in detail. PARAMICS is one of the few off-the-shelf simulation software packages that can model unconventional traffic circles. However, the default capabilities of PARAMICS are not sufficient to model statistically valid simulation models of these two unconventional circles. Use of the application programming interface (API) feature of PARAMICS is required to develop realistic models that can accurately represent drivers’ facility-specific behaviors. A gap acceptance–rejection binary probit model based on the analysis of field data was developed and implemented with PARAMICS API. The differences between the simulation results of the API enhanced model and the default PARAMICS model are presented to demonstrate the importance of extending the existing default models and the careful validation and calibration using real-world data. Finally, the sensitivity analyses of the developed simulation models are presented.
ISSN:0361-1981
2169-4052
DOI:10.1177/0361198106196500121