OJCE  Vol.7 No.4 , December 2017
A Comparison among Manual and Automatic Calibration Methods in VISSIM in an Expressway (Chihuahua, Mexico)
Abstract: Traffic microsimulation is an essential tool in urban transportation and road planning. Its calibration is essential to attain representative results validated with real-world conditions. VISSIM (Verkehr in Städten—SIMulationsmodell) operates with the Wiedemann’s psycho-physical car-following model for freeway travel that considers safety distances (standstill and movement) during simulation. Calibration in this paper was achieved by using two different approaches: a) manual and b) genetic algorithm (with the GEH statistic formula) calibration techniques. Calibration and validation of this model were performed at the Periferico de la Juventud expressway in Chihuahua City, in northern Mexico. The Periferico de la Juventud (PDJ) has a N-S orientation and a length of ca. 20 km, with its northern section being its most congested portion. Its highest vehicle volume occurs at noon, with 3700 vehicles per hour, with 95% being passenger cars and the other 5% heavy goods vehicles. PDJ’s speed limit is 70 km·h-1, but the driver’s behavior has a tendency towards the aggressive performance. A total of 82 standstill and 82 look-ahead distances were obtained from unmanned aerial vehicles (UAV) images, with values ranging from 0.8 to 4.7 m and from 0.2 to 28 m, respectively. VISSIM calibrated parameter values were calculated for this expressway, being slightly above than the VISSIM default ones; and was validated with travel times and look-ahead distances. Results contribute information for the city’s future installment of public transportation systems, and should help decision makers deal with future urban planning.
Cite this paper: Espejel-Garcia, D. , Saniger-Alba, J. , Wenglas-Lara, G. , Espejel-Garcia, V. and Villalobos-Aragon, A. (2017) A Comparison among Manual and Automatic Calibration Methods in VISSIM in an Expressway (Chihuahua, Mexico). Open Journal of Civil Engineering, 7, 539-552. doi: 10.4236/ojce.2017.74036.

[1]   Salvo, G., Caruso, L., Scordo, A., Guido, G. and Vitale, A. (2014) Comparison between Vehicle Speed Profiles Acquired by Differential GPS and UAV. 17th Meeting of the Euro Working Group on Transportation Ewgt 2014, Sevilla, 2-4 July 2014.

[2]   Choa, F., Milam, R.T. and Stanek, D. (2003) CORSIM, PARAMICS and VISSIM: What the Manuals Never Told You. In: Benner, G. and Donnelly, R., Eds., Proceedings of the Ninth TRB Conference on the Application of Transportation Planning Methods, Baton Rouge, 6-10 April 2003, 392-402.

[3]   Lownes, N.E. and Machemehl, R.B. (2006) VISSIM, a Multi-Parameter Sensitivity Analysis. In: Perrone, L.F., Wieland, F.P., Liu, J., Lawson B.G., Nicol, D.M. and Fujimoto, R.M., Eds., Proceedings of the 2006 Winter Simulation Conference IEEE Xplore, Monterrey, 3-6 December 2006, 1406-1413.

[4]   Fellendorf, M. and Vortisch, P. (2010) Microscopic Traffic Flow Simulator VISSIM. In: Barceló, J., Ed., Fundamentals of Traffic Simulation, International Series in Operations Research & Management Science, Springer, New York, 145, 63-93.

[5]   Wiedemann, R. (1974) Simulation des Stra?enverkehrsflusses. (In German) Schtiftenreibe des Institus fur Verkehrswesen der Universitat Karlsruhe, Heft 8.

[6]   Wiedemann, R. (1999) Modeling of RTI-Elements on Multi-Lane Roads. Advanced Telematics in Road Transport, Edited by the Comission of the European Community, DG XIII.

[7]   Panwai, S. and Dia, H. (2005) Comparative Evaluation of Microscopic Car-Following Behavior. IEEE Transactions on Intelligent Transportation Systems, 6, 314-325.

[8]   Fedra, K. (2000) Urban Environmental Management: Monitoring GIS and Modeling. Computers, Environment and Urban Systems, 23, 443-457.

[9]   Kim, S.J., Kim, W. and Rilett, L. (2005) Calibration of Microsimulation Models Using Nonparametric Statistical Techniques. Transportation Research Broad of the National Academies, Washington DC, 111-119.

[10]   Park, B. and Won, J. (2006) Microscopic Simulation Model Calibration and Validation Handbook. Publication FHWA/VTRC 07-CR6. FHWA, U.S. Department of Transportation, Washington DC.

[11]   Lee, D., Yang, X. and Chandrasekar, P. (2000) Parameter Calibration for PARAMICS Using Genetic Algorithm, Proceedings of 80th Annual Meeting of the Transportation Research Board, Washington, DC., 2000.

[12]   Miller, D.M. (2009) Developing a Procedure to Identify Parameters for Calibration of a VISSIM Model. Master in Science Thesis, Georgia Institute of Technology, Georgia.

[13]   Ma, T. and Abdulhai, B. (2002) Genetic Algorithm-Based Optimization Approach and Generic Tool for Calibrating Traffic Microscopic Simulation Parameters. Transportation Research Record: Journal of the Transportation Research Board, 1800, 6-15.

[14]   Park, B. and Qi, H. (2005) Development and Evaluation of a Procedure for the Calibration of Simulation Models. Transportation Research Record: Journal of the Transportation Research Board, 1934, 208-217.

[15]   Park, B. and Schneeberger, J. (2003) Microscopic Simulation Model Calibration and Validation: Case Study of VISSIM Simulation Model for a Coordinated Actuated Signal System. Transportation Research Record: Journal of the Transportation Research Board, 1856, 185-192.

[16]   Rrecaj, A.A. and Bombol, K.M. (2015) Calibration and Validation of the VISSIM Parameters—State of the Art. TEM Journal-Technology Education Management Informatics, 4, 255-269.

[17]   Censo de población y vivienda México (2010) INEGI (Instituto Nacional de Estadística y Geografía)

[18]   Carrasco, H. (2016) Supera Tráfico a Vialidades. El Diario de Juárez, June 2016.

[19]   Plan de Desarrollo Urbano del Centro de Población Chihuahua, Tercera Actualización. IMPLAN, H. Ayuntamiento de Chihuahua (2009).

[20]   Quezada, M. and Barrientos, H. (2016) Se queda Chihuahua sin transporte público. El Diario de Chihuahua, July 2016.

[21]   Google Earth (2016) “Chihuahua City” 28°40’14.74” N and 106°05’24.63” W. Google Earth. October 6, 2017. November 22, 2017.

[22]   US Department Transportation (2006) Traffic Detector Handbook. 3rd Edition, Vol. 1, FHWA-HRT-06-108, 1-2.

[23]   Garber, N.J. and Hoel, L.A. (2005) Traffic and Highway Engineering. 5th Edition, Cengage Learning, Stamford.

[24]   Leduc, G. (2008) Road Traffic Data: Collection Methods and Applications. Working Papers on Energy, Transport and Climate Change, 1(55).

[25]   Cusack, B. and Khaleghparast, R. (2015). Evaluating Small Drone Surveillance Capabilities to Enhance Traffic Conformance Intelligence. The Proceedings of the 8th Australian Security and Intelligence Conference, Perth, 30 November-2 December 2015, 21-27.

[26]   VISSIM User’s Guide. PTV (Planung Transport Verkehr) VISSIM 8.0 (2014)

[27]   Gardes, Y., May, A.D., Dahlgren, J. and Skabardonis, A. (2002) Freeway Calibration and Application of the PARAMICS Model. 81st Annual Meeting of the Transportation Research Board, Washington DC.

[28]   Chu, L., Liu, H.X., Oh, J.S. and Recker, W. (2003) A Calibration Procedure for Microscopic Traffic Simulation. Intelligent Transportation Systems Proceedings, 2, 1574-1579.

[29]   Moridpour, S., Sarvi, M., Rose, G. and Mazloumi, E. (2012) Lane-Changing Decision Model for Heavy Vehicle Drivers. Journal of Intelligent Transportation Systems, 16, 24-35.

[30]   Duong, D.D., Saccomanno, F.F. and Hellinga, B.R. (2011) Effects of Microscopic Traffic Platform Calibration on Errors in Safety and Traffic Metrics. 3rd International Conference on Road Safety and Simulation, Indianapolis.

[31]   Menneni, S., Sun, C. and Vortisch, P. (2008) Microsimulation Calibration Using Speed-Flow Relationships. Transportation Research Record: Journal of the Transportation Research Board, 2088, 1-9.

[32]   Yang, Y., Dong, H., Qin, Y. and Zhang, Q. (2016) Parameter Calibration Method of Microscopic Traffic Flow Simulation Models Based on Orthogonal Genetic Algorithm. The 22nd International Conference on Distributed Multimedia Systems, Salerno, 25-26 November 2016, 55-60.

[33]   Manjunatha, P., Vortisch, P. and Mathew, T.V. (2013) Methodology for the Calibration of VISSIM in Mixed Traffic. Transportation Research Board 92nd Annual Meeting, 13-3677.

[34]   UKHA (UK Highways Agency) (1975) Design Manual for Roads and Bridges. 12, Section 2.