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A microsimulation-based analysis for driving behaviour modelling on a congested expressway

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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.

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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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Fellendorf M, Vortisch P (2010) Fundamentals of traffic simulation, vol 145. Springer, NewYork

    Book  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Hidas P (2005) Modeling vehicle interactions in microscopic simulation of merging and weaving. Transp Res Part C Emerg Technol 13:37–62

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Low N, Gleeson B (2015) Impact of congestion growth in Muscat. UK Essays, London

    Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Manjunatha P, Vortisch P, Mathew T (2013) Methodology for the calibration of VISSIM in mixed traffic. Transportation Research Board, Washington, DC

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Menneni S, Sun C, Vortisch P (2008) Microsimulation calibration using speed-flow relationships. Transp Res Rec 2008:1–9

    Article  Google Scholar 

  • Moridpour S, Rose G (2010) Lane changing models: a critical review. Transp Lett 2:157–175

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Google Scholar 

  • Panwai S, Dia H (2005) Comparative evaluation of microscopic car-following behavior. IEEE Trans Intell Transp Syst 6(3):314–325

    Article  Google Scholar 

  • Park B, Qi H (2003) Development and evaluation of a procedure for the calibration of simulation models. Transp Res Rec 2005:208–217

    Google Scholar 

  • 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

    Article  Google Scholar 

  • PTV AG (2016) Merging and weaving: inside merge. PTV VISSIM example description. PTV Group, Karlsruhe

    Google Scholar 

  • PTV AG (2017) PTV VISSIM 9 user manual. PTV AG, Karlsruhe

    Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  MathSciNet  Google Scholar 

  • Treiber M, Kesting A (2013) Chapter 10 Elementary car-following models. Data, models and simulation. Springer, Heidelberg (978-3-642-32460-4 (eBook))

    MATH  Google Scholar 

  • 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

    MATH  Google Scholar 

  • 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

    Article  Google Scholar 

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Correspondence to Siham G. Farrag.

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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

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