Microscopic Simulation of Toll Plaza Safety and Operations
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32799
Microscopic Simulation of Toll Plaza Safety and Operations

Authors: Bekir O. Bartin, Kaan Ozbay, Sandeep Mudigonda, Hong Yang

Abstract:

The use of microscopic traffic simulation in evaluating the operational and safety conditions at toll plazas is demonstrated. Two toll plazas in New Jersey are selected as case studies and were developed and validated in Paramics traffic simulation software. In order to simulate drivers’ lane selection behavior in Paramics, a utility-based lane selection approach is implemented in Paramics Application Programming Interface (API). For each vehicle approaching the toll plaza, a utility value is assigned to each toll lane by taking into account the factors that are likely to impact drivers’ lane selection behavior, such as approach lane, exit lane and queue lengths. The results demonstrate that similar operational conditions, such as lane-by-lane toll plaza traffic volume can be attained using this approach. In addition, assessment of safety at toll plazas is conducted via a surrogate safety measure. In particular, the crash index (CI), an improved surrogate measure of time-to-collision (TTC), which reflects the severity of a crash is used in the simulation analyses. The results indicate that the spatial and temporal frequency of observed crashes can be simulated using the proposed methodology. Further analyses can be conducted to evaluate and compare various different operational decisions and safety measures using microscopic simulation models.

Keywords: Microscopic simulation, toll plaza, surrogate safety, application programming interface.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1317410

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 723

References:


[1] Mudigonda, S., Bartin, B. and Ozbay, K (2009). “Microscopic Modeling of Lane Selection and Lane Changing at Toll Plazas.” Proceedings of the Transportation Research Board 88th Annual Meeting.
[2] Ozbay, K., Yang, H., Bartin, B. and Mudigonda, S. (2008). “Derivation and Simulation Based Validation of a New Surrogate Safety Measure.” Transportation Research Record: Journal of the Transportation Research Board. Vol. 2083. pp. 105-113.
[3] Junga, A. J., (1990), “ A Multi-Purpose Toll Collection Plaza Model”, Proceedings of the 1990 Winter Simulation Conference
[4] Correa E., Metzner C. and Nino N. “TollSim: Simulation and Evaluation of Toll Stations”, International Transactions in Operational Research, 2004, pp 121-138.
[5] Burris, M. W., and Hildebrand, E. D., (1996), “Using Microsimulaion to Quantify the Impact of Electronic Toll Collection”, ITE Journal, July 1996, pp 21-24.
[6] Chien S.I., Spasovic L.N., Opie E.K., Korikanthimathi V. and, Besenski D. “Simulation-based Analysis for Toll Plazas with Multiple Toll Methods”, 84th Transportation Research Board Annual Meeting, January 2005
[7] Nezamuddin, N, and Al-Deek, H., “Developing a Microscopic Toll Plaza and Toll Road Corridor Model using PARAMICS”, Presented at the 87th TRB Annual Conference, 2008, Washington, D.C.
[8] Ozbay. K, Mudigonda, S and Bartin, B. “Calibration of an Integrated Freeway and Toll Plaza Model.” Presented at the 85th TRB Annual Conference, 2006, Washington, D.C.
[9] Bartin, B., Mudigonda, S. and Ozbay, K. “Estimation of the Impact of Electronic Toll Collection on Air Pollution Levels using Microscopic Simulation Model of a Large-Scale Transportation Network.” In Transportation Research Record: Journal of Transportation Research Board. No. 2011. 2008. pp.68-77.
[10] Darzentas, J., D. F. Cooper, P. A. Storr, and M. R. C. McDowell. 1980. “Simulation of Road Traffic Conflicts at T-Junctions.” Simulation. pp. 155–164.
[11] Archer, J., and I. Kosonen. 2000. “The Potential of Micro-Simulation Modelling in Relation to Traffic Safety” Assessment. Proc., Simulation in Industry. 12th European Simulation Symposium 2000 (D. P. F. Moller, ed.), Society for Computer Simulation International Arbeitsgemeinschaft Simulation, University of Hamburg, Germany, Sept. 28–30,.pp. 427–431.
[12] Gettman, D., and L. Head. Surrogate Safety Measures from Traffic Simulation Models, Final Report. FHWA-RD-03-050, FHWA, U.S. Department of Transportation, 2003.
[13] Van der Horst, R. “Time-to-Collision as a Cue for Decision Making in Braking.” Vision in Vehicles, Vol. 3, 1991, pp. 19–26.
[14] Farber, B. Designing a Distance Warning System from the User Point of View. APSIS Report, Institute fur Arbeitspsychologie and Interdisziplinare Systemforchung, Glonn-Haslach, Germany, 1991.
[15] Hogema, J. H., and W. H. Janssen. Effect of Intelligent Cruise Controlon Driving Behavior. Report TM-1996-C-12. TNO Human Factors, Soesterberg, Netherlands.