Transport Simulation Model Calibration with Two-Step Cluster Analysis Procedure

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The calibration results of transport simulation model depend on selected parameters and their values. The aim of the present paper is to calibrate a transport simulation model by a two-step cluster analysis procedure to improve the reliability of simulation model results. Two global parameters have been considered: headway and simulation step. Normal, uniform and exponential headway generation models have been selected for headway. Application of two-step cluster analysis procedure to the calibration procedure has allowed reducing time needed for simulation step and headway generation model value selection.

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  • [1] D. D.Q. Duong F. F. Saccomanno and B. R. Hellinga Calibration of microscopic traffic model for simulating safety performance Compendium of papers of the 89th Annual TRB Conference Jan. 10–14 2010 Washington DC. TRB 2010.

  • [2] L. Vasconcelos Á. Seco and A. B. Silva Hybrid calibration of microscopic simulation models EWGT2013 – 16th Meeting of the EURO Working Group on Transportation Social and Behavioral Sciences Procedia 2013. Springer International Publishing Switzerland 2014.

  • [3] M. Treiber and A. Kesting “Microscopic Calibration and Validation of Car-Following Models – A Systematic Approach” in 20th Int. Symp. on Transportation and Traffic Theory (ISTTT) Noordwijk Netherlands 2013. ISTTT Procedia 2014.

  • [4] C. Antoniou J. Barcelo M. Brackstone H.B. Celikoglu B. Ciuffo V. Punzo P. Sykes T. Toledo P. Vortisch and P. Wagner “Traffic Simulation: Case for guidelines” European Commission Joint Research Centre Institute for Energy and Transport European Union Tech. Rep. LB-NA-26534-EN-N 2014.

  • [5] J. B. Lee “Calibration of Traffic Simulation Models Using Simultaneous Perturbation Stochastic Approximation (SPSA) Method extended through Bayesian Sampling Methodology” PhD. thesis Graduate School-New Brunswick Rutgers The State University of New Jersey New Brunswick NJ United States 2008.

  • [6] R. A. Masterson “Dynamic Tailoring and Tuning for Space-Based Precision Optical Structures” PhD. thesis Massachusetts Institute of Technology Cambridge MA United States 2005.

  • [7] TSS-Transport Simulation Systems. Aimsun 6.0 User’s manual. 2009.

  • [8] D. Shteinman “Two Methods to Improve the Quality and Reliability of Calibrating & Validating Simulation Models” Road & Transport Research: A Journal of Australian and New Zealand Research and Practice vol. 23 issue 3 pp. 65–78 Sep. 2014.

  • [9] D. Altas A. Kubas and J. Sezen “Analysis of environmental sensitivity in Thrace region through two step cluster” Trakia Journal of Science vol. 11 pp. 318–329 2013.

  • [10] S. Bekhor M. E. Ben-Akiva and M. S. Ramming “Evaluation of choice set generation algorithms for route choice models” Annals of Operations Research vol. 144 issue 1 pp. 235–247 Apr. 2006.

  • [11] S. Bera and K. V. K. Rao “Estimation of origin-destination matrix from traffic counts: the state of the art” European Transport \ Trasporti Europei vol. 49 pp. 3–23 Apr. 2011.

  • [12] J. Janga C. Parkb B. Kimc N. Choi “Modeling of Time Headway Distribution on Suburban Arterial: Case Study from South Korea” Social and Behavioral Sciences Procedia vol. 16 pp. 240–247 2011.

  • [13] S. M. Abtahi M. Tamannaei and H. Haghshenash “Analysis and modeling time headway distributions under heavy traffic flow conditions in the urban highways: case of Isfahan” Transport vol. 26(4) pp. 375–382 2011.

  • [14] N. Zenina and J. Merkurjevs “Analysis of simulation input and output to compare simulation tools” Mechanics Transport Communications no. 3 p. V4 Nov. 2009. [Paper]. Available: [Accessed June 12 2010].

  • [15] G. Zhang Y. Wang H. Wei and Y. Chen “Examining Headway Distribution Models with Urban Freeway Loop Event Data” Transportation Research Record: Journal of the Transportation Research Board vol. 1999 p. 16 2007.

  • [16] D. Ni J. D. Leonard II A. Guin and B. M. Williams “Systematic Approach for Validating Traffic Simulation Models” Transportation Research Record: Journal of the Transportation Research Board vol. 1876 p. 12 2004.

  • [17] B. B. Park and H. M. Qi “Development and Evaluation of a Procedure for the Calibration of Simulation Models” Transportation Research Record: Journal of the Transportation Research Board vol. 1934 p. 9 2005. [Online]. Available: TRBOnline [Accessed September 05 2015].

  • [18] J. Hourdakis P. G. Michalopoulos and J. Kottommannil “A Practical procedure for calibrating microscopic traffic simulation models” Transportation Research Record: Journal of the Transportation Research Board vol. 1852 p. 9 2003.

  • [19] J. Ma and K. M. Kockelman “Crash Modeling Using Clustered Data from Washington State: Prediction of Optimal Speed Limits” Transportation Research Record: Journal of the Transportation Research Board vol. 1818 p. 6 2002.

  • [20] S.Hu “Akaike Information Criterion” 2007. [Online]. Available: Center for Research in Scientific Computation [Accessed August 05 2015].

  • [21] Wikipedia “Federal Highway Administration”. [Online]. Available: [Accessed July 15 2015].

  • [22] FHWA - Federal Highway Administration “Traffic Analysis Toolbox Volume III - Guidelines for Applying Traffic Microsimulation Modeling Software” 2004. [Online]. Available: FHWA [Accessed August 13 2015].

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