I was lucky enough to be involved in a research project back in 2002 that required a simulation model of the South Jersey traffic network. This was a tall order for me then for I had no idea what the proper steps of building a large-scale simulation model. Data were scarce, especially input data. In other words, it was not a straightforward task to gather geometric details, number of lanes,traffic signal timings, etc. Besides, the simulation tools were not as sophisticated as they are now and there were little to none online aerial imagery back then, and that caused so many problems in terms of building a large scale model to the right scale.
I have my misgivings about the potential of using large-scale microscopic simulation models. Even with today’s enhanced computational power, the calibration and validation process of traffic simulation models is a major challenge because of the high level of uncertainty in the modeled systems. The majority of this uncertainty stems from the necessity of large amount input data that are not always available or observable, thus leaving the analysts with a large set of parameters for calibration.
Furthermore, there are not many available resources detailing the steps of a proper simulation model development process. There are eight known countries that use such guidance documents, namely the United Kingdom, the U.S., Australia, Germany, Canada, New Zealand Netherlands and Japan (references). An excellent review of these and a lengthy discussion on how to improve these available guidelines can be found in Antoniou et al. (2014). Readers who are interested in a more scientific approach to simulation model development should check out Daamen et al. (2015).
Despite my misgivings, I still believe they provide some insight into the impacts of certain operational and planning decisions.
Below are some of my papers on this topic:
- Iyer, S., Ozbay, K. and Bartin, B. (2010). “Ex Post Evaluation of Calibrated Simulation Models of Significantly Different Future Systems.” Transportation Research Record: Journal of the Transportation Research Board. No. 2161, pp. 49-56. (Link)
- Bartin, B., Mudigonda, S. and Ozbay, K. (2008). “Impact of Electronic Toll Collection on Air Pollution Levels: Estimation Using Microscopic Simulation Model of Large-Scale Transportation Network.” Transportation Research Record: Journal of the Transportation Research Board. Vol. 2011. pp. 68-77. (Link)
- Bartin, B., K, Yanmaz-Tuzel, O. and List, G. (2006). “Modeling and Simulation of Unconventional Traffic Circles.” Transportation Research Record: Journal of the Transportation Research Board. Vol. 1965, pp. 201-209. (Link)
- Ozbay, K., Bartin, B. and Chien, S. (2004). “South Jersey Real-Time Motorist Information Systems: Theory and Practice.” Transportation Research Record: Journal of the Transportation Research Board. 1886, pp. 68-75. (Link)
- Ozbay, K. and Bartin, B. (2003). “Incident Management Simulation.” SCS Simulation Journal, 79, No. 2, pp. 69-82. (Link)
A few useful resources I can list for this specific topic are as follows:
- Law, A. M. and Kelton, W. D. (1991). Simulation Modeling and Analysis. 2nd Edition, McGraw-Hill, Inc. (Link)
- Toledo, T. and Koutsopoulos, H.N. (2004). “Statistical validation of traffic simulation models”. Transportation Research Record: Journal of the Transportation Research Board, No. 1876, pp. 142–150. (Link)
- Dowling, R., Skabardonis, A. and Alexiadis, V. (2004). Traffic Analysis Toolbox. Volume III: Guidelines for Applying Traffic Microsimulation Software. Publication FHWA-HOP-04-040. FHWA, U.S. Department of Transportation. (Link)
- Antoniou, C., Barcelo, J., Brackstone, M., Celikoglu, H. B., Ciuffo, B., Punzo, V., Sykes, P. Toledo, T., Vortisch, P. and Wagner, P. (2014). “Traffic Simulation: Case for guidelines” JRC Science and Policy Reports EUR 26534. Editors: Brackstone, M. and Punzo, V. (Link)
- Daamen W., Buisson C. and S. Hoogendoorn (eds) (2015). Traffic Simulation and Data: Validation methods and Applications. CRC Press. (Link)