An automatic calibration procedure of driving behaviour parameters in the presence of high bus volume

Nima Dadashzadeh, Murat Ergun, Sercan Kesten, Marijan Žura*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Most of the microscopic traffic simulation programs used today incorporate car-following and lane-change models to simulate driving behaviour across a given area. The main goal of this study has been to develop an automatic calibration process for the parameters of driving behaviour models using metaheuristic algorithms. Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and a combination of GA and PSO (i.e. hybrid GAPSO and hybrid PSOGA) were used during the optimization stage. In order to verify our proposed methodology, a suitable study area with high bus volume on-ramp from the O-1 Highway in Istanbul has been modelled in VISSIM. Traffic data have been gathered through detectors. The calibration procedure has been coded using MATLAB and implemented via the VISSIM-MATLAB COM interface. Using the proposed methodology, the results of the calibrated model showed that hybrid GAPSO and hybrid PSOGA techniques outperformed the GA-only and PSO-only techniques during the calibration process. Thus, both are recommended for use in the calibration of microsimulation traffic models, rather than GA-only and PSO-only techniques.

Original languageEnglish
Pages (from-to)491-502
Number of pages12
JournalPromet - Traffic and Transportation
Volume31
Issue number5
DOIs
Publication statusPublished - Nov 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019, Faculty of Transport and Traffic Engineering. All rights reserved.

Funding

This study is a part of Ph.D. thesis of the corresponding author from the Istanbul Technical University, Turkey. We would like to thank Prof. Dr. Tomaž Maher and Assist. Dr. Rok Marsetič from the Traffic Technical Institute of Civil and Geodetic Engineering Faculty, University of Ljubljana, Slovenia, for their kind support, valuable comments, and helpful suggestions. The authors are also thankful to the PTV-AG Karlsruhe Company for their support in providing a thesis-based unlimited version of VISSIM software.

FundersFunder number
Traffic Technical Institute of Civil and Geodetic Engineering Faculty, University of Ljubljana
Istanbul Teknik Üniversitesi

    Keywords

    • Calibration
    • Driving behaviour
    • Genetic algorithm
    • Particle swarm optimization
    • Traffic simulation models
    • VISSIM

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