Original scientific paper
https://doi.org/10.7307/ptt.v31i5.3100
An Automatic Calibration Procedure of Driving Behaviour Parameters in the Presence of High Bus Volume
Nima Dadashzadeh
orcid.org/0000-0001-5425-0572
; Graduate School of Science Engineering and Technology, Istanbul Technical University, Istanbul, Turkey
Murat Ergun
; Transportation Eng. Devision, Civil Engineering Faculty, Istanbul Technical University, Istanbul, Turkey
Sercan Kesten
; Civil Engineering Division, Department of Engineering, Işık University, Istanbul, Turkey
Marijan Žura
; Traffic Technical Institute (PTI), Faculty of Civil and Geodetic Engineering, University of Ljubljana, Ljubljana, Slovenia
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.
Keywords
Hrčak ID:
227927
URI
Publication date:
18.10.2019.
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