Traffic Simulation of Urban Street to Estimate Capacity

Main Article Content

Zainab Ahmed Alkaissi


This research aimed to develop a simulation traffic model for an urban street with heterogeneous traffic capable of analyzing different types of vehicles of static and dynamic characteristics based on trajectory analysis that demonstrated psychophysical driver behavior. The base developed model for urban traffic was performed based on the collected field data for the major urban street in Baghdad city. The parameter; CC1 minimum headway (represented the speed-dependent of the safety distance from stop line that the driver desired) justified in the range from (2.86sec) to (2.17 sec) indicated a good match to reflect the actual traffic behavior for urban traffic streets. A good indication of the convergence between simulated and field data of maximum error of 8% and below 10% for traffic flow rate and that provided a successfully simulated model by VISSIM for urban traffic behavior. The traffic speed decreased slowly, but still, variation in a large range from (30 km/hr to 55 km/hr) until a flow rate of 1000 vehicles/hr was reached, then the traffic speed decreased sharply. The dispersion between data points was caused by driver behavior and the special characteristics of the urban street. This dispersion of data points reduced and became less significant when it reached the capacity of the road. The obtained capacity value for divided urban traffic streets was (1610 vehicles/hr) with an optimum traffic density of 64 vehicles/km. Traffic simulation utilizing VISSIM parameters had been developed successfully since the simulation could estimate the field capacity with an acceptable range of error of 7.5 % (less than 10%).

Article Details

How to Cite
“Traffic Simulation of Urban Street to Estimate Capacity” (2022) Journal of Engineering, 28(4), pp. 51–63. doi:10.31026/j.eng.2022.04.04.

How to Cite

“Traffic Simulation of Urban Street to Estimate Capacity” (2022) Journal of Engineering, 28(4), pp. 51–63. doi:10.31026/j.eng.2022.04.04.

Publication Dates


• Alkaissi, Z.A., Jabbar A.K., Saja A., 2020. Discharge Headway Time Distribution Model on Congested Signalized Intersections and their Operation Management: A Case Study in Baghdad City. IOP Conf. Series: Materials Science and Engineering 870, doi:10.1088/1757-899X/870/1/012091.

• Alkaissi, Z.A. and Hussain, R.Y., 2020. Delay Time Analysis and Modelling of Signalised Intersections using Global Positioning System (GPS) Receivers. IOP Conf. Series: Materials Science and Engineering 671.doi:10.1088/1757-899X/671/1/012110.

• Alkaissi, Zainab Ahmed, 2018. Capacity Estimation of Urban Road in Baghdad City: A Case Study of Palestine Arterial Road. ARPN Journal of Engineering and Applied Sciences, Vol.13, No.21, Asian Research Publishing Network (ARPN).

• Alkaissi, Zainab Ahmed, 2018. Analytical Study of Headway Time Distribution on Congested Arterial: A Case Study Palestine Road in Baghdad City. International Congress and Exhibition" Sustainable Civil Infrastructures: Innovative Infrastructure Geotechnology", pp: 85-97.

• Alkaissi, Zainab Ahmed, 2017. Travel Time Prediction Models and Reliability Indices for Palestine Urban Road in Baghdad City. Al-Khwarizmi Engineering Journal, ISSN (printed):1818, ISSN (online):2312-0789, Vol. 13, Issue 13, pp: 120-130.

• Al-Ghamdi A.S., 2001. Analysis of Time Headways on Urban Roads: Case Study from Riyadh. Journal of Transportation Engineering. 127(4): 289-294.

• Al-Ghamdi A.S., 1999. Modeling Vehicle Headways for Low Traffic Lows on Urban Freeways and Arterial Roadways. Proceeding of the 5th International Conference on Urban Transport and the Environment for the 21st Century. Rhodes, Greece.

• Chang M., and Y. Kim., 2000. Development of capacity estimation method from statistical distribution of observed traffic flow. Proceedings of the 4th international symposium on highway capacity, Transportation Record Circular E-C018.

• Gajjar R., and Mohandas, M., 2016. Critical Assessment of Road Capacities on Urban Roads - A Mumbai Case-Study. Transportation Research Procedia. 17: 685-692.

• Joseph, and Nagakumar., 2014. Evaluation of Capacity and Level of Service of Urban Roads. International Journal of Emerging Technologies and Engineering (IJETE) ISSN: 2348-8050, ICRTIET-2014 Conference Proceeding, 30th - 31st August 2014.

• Mathew, T.V., and Radhakrishnan, P., 2020. Calibration of microsimulation models for nonlane-based heterogeneous traffic at signalized intersections. J. Urban Plan. Dev., 136, 59–66.

• Menneni, S., Sun, C., and Vortisch, P., 2008. Microsimulation calibration using speed-flow relationships, Transportation Research Record: Journal of the Transportation Research Board, 2088, pp. 1–9.

• Pratik Mankar, and B.V Khode., 2016. Capacity Estimation of Urban roads under Mixed Traffic Condition. International Research Journal of Engineering and Technology (IRJET). 3(4).

• PTV Vision, 2009, VISSIM tutorial, PTV AG, Karlruhe, Germany.

• Ratrout, N.T., and Rahman, S.M., 2009. A comparative analysis of currently used microscopic and macroscopic traffic simulation software. The Arabian Journal for Science and Engineering, Volume 34, Number 1B.

• Rajesh Gajjar, and Divya Mohandas., 2016. Critical Assessment of Road Capacities on Urban Roads - A Mumbai Case-Study. Transportation Research Procedia. 17: 685-692.

• Siddharth, S.P., and Ramadurai, G., 2013. Calibration of VISSIM for Indian heterogeneous traffic conditions. Procedia-Social and Behavioral Science, 104, 380–389.

Similar Articles

You may also start an advanced similarity search for this article.