Abstract
Recently, simulation models have been widely used around the world to evaluate the performance of different traffic facilities and management strategies for efficient and sustainable transportation systems. One of the keys factors for ensuring the reliability of the models in reflecting local conditions is the calibration and validation of microsimulation models. The majority of the existing calibration efforts focus is on the experimental designs of driver behaviour and lane-changing parameters. Towards this end, this paper describes the necessary procedure for the calibration and validation of a microscopic model using the VISSIM software, during peak hours. The procedure is applied on Muscat Expressway in the Sultanate of Oman. The calibration parameters and the measure-of-effectiveness are identified by using multi-parameter sensitivity analysis. The optimum values for these parameters are obtained by minimising errors between simulated data and field data. In our proposed model, we used traffic volume and travel speed for model calibration, as well as average travel time for validation of the calibrated model. The achieved results showed that driving characteristics significantly impacted the merging/diverging traffic flow ratio in the merging area, the link length and the distance between on-ramps and off-ramps, as well as the percentage of heavy vehicles. The results also showed that having both the advanced merging and cooperative lane-change settings active, along with safety distance reduction factor, necessary lane change, minimum headway (front/rear), and emergency stop, had a significant influence on simulation precision, especially at on-ramps and off-ramps. Finally, our proposed model can be utilized as a base for future traffic strategy analysis and intelligent transportation systems evaluation to help decision makers with long-term and sustainable development decisions.
Similar content being viewed by others
References
Aghabayk K, Sarvi M, Young W, Kautzsch L (2013) A novel methodology for evolutionary calibration of VISSIM by multi-threading. In: Australasian transport research forum 2013 proceedings
Aria E, Olstam J, Schwietering C (2016) Investigation of automated vehicle effects on driver’s behavior and traffic performance. Transp Res Proced 15:761–770. https://doi.org/10.1016/j.trpro.2016.06.063
Blair B, Hughes J, Allshouse W, McKenzie L, Adgate J (2018) Truck and multivehicle truck accidents with injuries near Colorado oil and gas operations. Int J Environ Res Public Health 15:1861
Carson J (2010) Best practices in traffic incident management. In: Report FHWA-HOP-1—050, FHWA, U.S. Department of Transportation, September 2010. https://doi.org/10.1080/19439962.2016.1199623
Chitturi M, Benekohal R (2008) Calibration of VISSIM for freeways. In: Presented at the 87th TRB annual meeting and publication in TRR, 2008
Choa F, Milam RT, Stanek D (2002) CORSIM, PARAMICS, and VISSIM: what the manuals never told you. In: Proceedings of 9th TRB conference on the application of transportation planning methods, TRB, Louisiana, USA, pp 392–402
Ciulffo B, Punzo V, Torrieri V (2008) Comparison of simulation-based and model-based calibrations of traffic-flow microsimulation models. Transp Res Rec 2088:36–44
Dan M, Robert B, Geza P, Praprut S, Kevin B, Gerald U (2017) Use of intelligent transportation systems in rural work zones. In: FHWA/TX-11/0-6427-1. Project performed in cooperation with the Texas Department of Transportation and the Federal Highway Administration. http://tti.tamu.edu/documents/0-6427-1.pdf
Emelie F (2016) Driving behavior modeling and evaluation of merging control strategies—A microscopic simulation study on Sirat Expressway. 2016. Department of Science and Technology. Linköping University
Espejel-Garcia D, Saniger-Alba JA, Wenglas-Lara G, Espejel-Garcia VV, Villalobos-Aragon A (2017) Comparison among manual and automatic calibration methods in VISSIM in an Expressway (Chihuahua, Mexico). Open J Civ Eng 7:539–552
Farrag SG, Outay F, Yasar AU et al (2020) Toward the improvement of traffic incident management systems using Car2X technologies. Pers Ubiquit Comput. https://doi.org/10.1007/s00779-020-01368-5
Fellendorf M, Vortisch P (2010) Fundamentals of traffic simulation, vol 145. Springer, NewYork
FHWA-HRT-04-040 (2004) Traffic analysis toolbox volume III: guidelines for applying traffic microsimulation software. In: Final Report 2004
FODT (2014) Traffic analysis handbook. A reference for planning and operations. Florida Department of Transportation
Fountoulakis M, Bekiaris-Liberis N, Roncoli C, Papamichail I, Papageorgiou M (2017) Highway traffic state estimation with mixed connected and conventional vehicles: microscopic simulation-based testing. Transp Res Part C 78:13–33
Gao Y (2008) Calibration and comparison of the VISSIM and INTEGRATION microscopic traffic simulation models. Thesis submitted to the Virginia Polytechnic Institute and State University September 5, 2008, Blacksburg, Virginia
Ge Q, Menendez M (2012) Sensitivity analysis for calibrating VISSIM in modeling the Zurich network. In: 12th Swiss transport research conference, 2012
Gomes G, May A, Horowitz R (2004) Congested freeway microsimulation micro-simulation model using VISSIM. In: Transportation Research Record: Journal of the Transportation Research Board, No. 1876, TRB, National Research Council, Washington, D.C., 2004, pp 71–81
Henclewood D, Suh W, Rodgers MO, Fujimoto R, Hunter MP (2017) A calibration procedure for increasing the accuracy of microscopic traffic simulation models. Simulation 93:35–47
Hidas P (2005) Modeling vehicle interactions in microscopic simulation of merging and weaving. Transp Res Part C Emerg Technol 13:37–62
Higgs B, Abbas MM, Medina A (2011) Analysis of the Wiedemann car following model over different speeds using naturalistic data. In: 3rd International conference on road safety and simulation, September 2011
Highway Design Standard (2010) Sultanate of Oman. Ministry of transportation and communications
Himani A (2016) Enhancing the side to main street merging using autonomous vehicle technology. A thesis presented to the Graduate Faculty of the University of Akron
Jing D, Andrew H, Navid S, Chaoru L, Neal H, Skylar K (2015) VISSIM calibration for urban freeways 2015. In: Trans Project 14-487. Ctre (center for transportation of research and education) Iowa Department of Transportation
Kehoe P (2011) An analysis of traffic behavior at freeway diverge sections using traffic microsimulation software. Master thesis submitted to the faculty of the Virginia Polytechnic Institute and State University, Blackburg, Virgina
Kim SJ, Kim W, Rilett LR (2005) Calibration of microsimulation models using nonparametric statistical techniques. Transp Res Rec 1935:111–119
Kritsadaniramit A, Mekpruksawong V, Learnpetch P, Phanurai S, Dapanwai S (2016) The evaluation of traffic performance after applied the urgent traffic management strategies using microscopic simulation model. In: Expressway Authority of Thailand (EXATa). National civil engineering conference, volume 20, 8–10 July 2016
Lee JB, Ozbay K (2009) New calibration methodology for microscopic traffic simulation using enhanced simultaneous perturbation stochastic approximation approach. Transp Res Rec 2124:233–240
Low N, Gleeson B (2015) Impact of congestion growth in Muscat. UK Essays, London
Lownes N, Machemehl R (2006) Sensitivity of simulated capacity to modification of VISSIM driver behavior parameters. In: Transportation Research Record: Journal of the Transportation Research Board, No. 1988, Transportation Research Board of the National Academies, Washington, D.C., 2006, pp 102–110
Ma J, Dong H, Zhang HM (2007) Calibration of microsimulation with heuristic optimization methods. Transp Res Rec 1999:208–217
Maheshwary P, Bhattacharyya K, Maitra B, Boltze M (2019) A methodology for calibration of traffic micro-simulator for urban heterogeneous traffic operations. J Traffic Transp Eng. https://doi.org/10.1016/j.jtte.2018.06.007
Manjunatha P, Vortisch P, Mathew T (2013) Methodology for the calibration of VISSIM in mixed traffic. Transportation Research Board, Washington, DC
Marczak F, Daame W, Buisson C (2013) Key variables of merging behavior: empirical comparison between two sites and assessment of gap acceptance theory. In: 20th International symposium on transportation and traffic theory (ISTTT) 2013
Mathew T (2014a) Car-following models. In: Transportation systems engineering, course material chapter 14, IIT Bombay
Mathew T (2014b) Lane changing models. Transportation systems engineering, course material chapter 15, February 19 2014, IIT Bombay
MDOT Minnesota Department of Transportation (2014) Corridor Simulation Modeling-Requirements and Resources. St. Paul, MN, 2013. Accessed Online: January 10, 2014
Mehar A, Chandra S, Velmurugan S (2014) Highway capacity through VISSIM calibrated for mixed traffic conditions. KSCE J Civ Eng 18:639–645
Menneni S, Sun C, Vortisch P (2008) Microsimulation calibration using speed-flow relationships. Transp Res Rec 2008:1–9
Moridpour S, Rose G (2010) Lane changing models: a critical review. Transp Lett 2:157–175
Muscat Municipality (2018) Traffic study Report. Design of widening of Muscat expressway Muscat Municipality
Nissan A, Koutsopoulosb H (2011) Evaluation of the impact of advisory variable speed limits on motorway capacity and level of service. Proced Soc Behav Sci 16:100–109
NTS National Transport Survey (2017) Oman National Spatial Strategy. In: National Transport Survey (NTS) Final Draft Inception Report. Supreme Council for Planning. November 2017
Olstam JJ, Tapani A (2004) Comparison of car-following models. In: VTI meddelande 960A-2004. Swedish National Road and Transport Research Institute (VTI)
Organization for Economic Cooperation and Development OECD (2013) Better use of infrastructures to reduce environmental and congestion costs. OECD Economic Surveys: Belgium 2013. OECD Publishing, Paris, pp 11–13
Panwai S, Dia H (2005) Comparative evaluation of microscopic car-following behavior. IEEE Trans Intell Transp Syst 6(3):314–325
Park B, Qi H (2003) Development and evaluation of a procedure for the calibration of simulation models. Transp Res Rec 2005:208–217
Park B, Qi H (2005) Development and evaluation of simulation model calibration procedure. In: 84th annual meeting preprint CD-ROM, Transportation research board, Washington, D.C
Park B, Schneeberger JD (2003) Microscopic simulation model calibration and validation: case study of VISSIM simulation model for a coordinated actuated signal system. Transp Res Rec 2003(1856):185–192
PTV AG (2016) Merging and weaving: inside merge. PTV VISSIM example description. PTV Group, Karlsruhe
PTV AG (2017) PTV VISSIM 9 user manual. PTV AG, Karlsruhe
Raka H, Gao Y (2011) Calibrating the steady state model using macroscopic loop detector data. TRB Circular E-C149, TRB, National Research Council, Washington, DC
Rakesh B, Shweta B (2010) Public transportation services in Oman: a study of public perceptions. J Public Transp 13(4):1
Rakha H, Crowther B (2002) A comparison of greenshields, pipes, and van aerde car-following and traffic stream models. Transp Res Rec 1802:248–262
Shelke M, Malhotra A, Mahalle PN (2019) Fuzzy priority based intelligent traffic congestion control and emergency vehicle management using congestion-aware routing algorithm. Int J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-019-01523-8
Simon B (2011) Intelligent Transport Systems (ITS: latest developments and use of micro-simulation assessment. In: Publishes project report PPR606. Transport Research Laboratory (TRB)
Song R, Sun J (2016) Calibration of a micro-traffic simulation model with respect to the spatial-temporal evolution of expressway on-ramp bottlenecks. Simulation 92:535–546
Srikanth S, Mehar A, Parihar A (2017) Calibration of Vissim model for multilane highways using speed flow curves. Stavební Obz Civ Eng J 26:303–314
Su Y, Sun W (2019) Dynamic differential models for studying traffic flow and density. Int J Ambient Intell Humaniz Comput 10:315–320. https://doi.org/10.1007/s12652-017-0506-4
Sun D, Li Y (2012) Microscopic car-following model for the traffic flow: the state of the art. J Control Theory Appl 10(2):133–143
Treiber M, Kesting A (2013) Chapter 10 Elementary car-following models. Data, models and simulation. Springer, Heidelberg (978-3-642-32460-4 (eBook))
Uchiyamaa N, Taniguchib E (2014) Analysis of impacts on dispatcher’s route choice behaviour by road improvements on using a trial and error learning model. In: Procedia—Social and Behavioral Sciences, 8th international conference on city logistics, vol 125, pp 297–311
Weise T (2008) Global optimization algorithms—theory and application. Springer, New York
Whaley MT (2016) Developing freeway merging calibration techniques for analysis of ramp metering In Georgia through VISSIM simulation. http://hdl.handle.net/1853/55068
WSDOT (Washington State Department of Transportation) (2014) Protocol for Vissim simulation (C. Mai, C. McDaniel-Wilson, D. Noval, et al.). http://www.oregon.gov/ODOT/TD/TP/APM/AddC.pdf
Yang W, Sun Y, Huang H et al (2020) Persistent transportation traffic volume estimation with differential privacy. Int J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-020-01692-x
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Farrag, S.G., El-Hansali, M.Y., Yasar, AUH. et al. A microsimulation-based analysis for driving behaviour modelling on a congested expressway. J Ambient Intell Human Comput 11, 5857–5874 (2020). https://doi.org/10.1007/s12652-020-02098-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-020-02098-5