An Integrated Approach towards Building a Simulation Model Supporting the Management of the Passenger Transportation System. Part 1 - Theoretical basis.

Joanna Gąbka, Sławomir Susz, Maria Rosienkiewicz


This article presents an integrated approach towards building a simulation model of the transportation network. The proposed method is based on the recommendations of the Blue Book for Sector of Public Transport in cities, agglomerations and regions issued by Jaspers (Joint Assistance to Support Projects in European Regions). It comprises six steps with such elements as econometric modelling, artificial neural networks and mathematical model. It is dedicated to developing simulation models for the purpose of picturing present situation and dependencies dominating in the transportation network, easily reflecting effects of potential modifications and providing forecasts for the future. The described hybrid method was verified in practice by building the simulation model which is presented in the next article in this series entitled: An Integrated Approach towards Building a Simulation Model Supporting the Management of the Passenger Transportation System. Part 2 – Case Study.


integrated approach, transportation network, simulation model

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Aw A., Klar A., Materne T., Rascle M., Derivation of Continuum Traffic Flow Models from Microscopic Follow-the-Leader Models, "SIAM Journal of Applied Mathematics", 63 (2002) pp. 259-278.

Blue V., Adler J., Emergent fundamental pedestrian flows from cellular automata microsimulation, "Transportation Research Record", 1644 (1998), pp. 29–36.

Blue V., Adler J., Cellular automata microsimulation of bi-directional pedestrian flows, "Transportation Research Record", 1678 (1999), pp. 135–141.

Blue V., Adler J., Modeling four-directional pedestrian flows, "Transportation Research Record", 1710 (2000), pp. 20–27.

Blue V., Adler J., Flow capacities from cellular automata modeling of proportional splits of pedestrians by direction, [in:] Sharma M., Schreckenberg S. (edd.), Pedestrian and Evacuation Dynamics, Springer, Berlin 2001, pp. 115–121.

Bourrel E., Lesort J., Mixing microscopic and macroscopic representations of traffic flow: Hybrid model based on Lighthill-Whitham-Richards theory, "Transportation Research Record", 1852 (2003), pp. 193–200.

Brilon W., Wu N., Evaluation of cellular automata for traffic flow simulation on freeway and urban streets, "Stadt Region Land", 66 (1998), pp. 111–117.

Burstedde C., Kirchner K., Klauck K., Schadschneider A., Zittartz J., Cellular automaton approach to pedestrian dynamics - applications, [in:] Sharma M., Schreckenberg S. (edd.), Pedestrian and Evacuation Dynamics, Springer, Berlin 2001, pp. 87–97.

Daamen W., Modelling Passenger Flows in Public Transport Facilities, The Netherlands: T2004/6, 2004, TRAIL Thesis Series.

Dijkstra J., Jessurun A., Timmermans H., Simulating pedestrian activity scheduling behavior and movement patterns using a multi-agent Cellular Automata model, Washington, 2002, CD-ROM with Proceedings, Transportation Research Board.

Fukui M., Ishibashi Y., Jamming transition in cellular automaton models for pedestrian on passageway, "Journal of the Physical Society of Japan", 68 (1999a), pp. 3738–3739.

Circella G., Hunt J., Stefan K. J., Brownlee A. T., Simplified model of local transit services, "European Journal of Transport and Infrastructure Research", 14 (2014)/2, pp. 122-142.

Griliches M., Intriligator Z., Handbook of Econometrics, vol. 1, Chapter 3, ed. Los Angeles, CA, USA: North Holland 1983.

Helbing D., A fluid dynamic model for the movement of pedestrians, "Complex Systems", 6 (1992), pp. 391–415.

Helbing D., Verkehsdynamik (ang. Traffic dynamics), Springer Verlag, Berlin-Heidelberg 1997.

Helbing D., Molnar P., Social force model for pedestrian dynamics, "Physical Review", 51 (1995)/5, pp. 4282–4286.

Hood W., Koopmans T., Studies in Econometric Method, Cowles Commission Monograph, no. 14, John Wiley, New York 1953.

Hoogendoorn S., Multiclass Continuum Modelling of Multilane, PhD Thesis, Delft: Delft University of Technology, Delft University Press, 1999.

Hoogendoorn S., Bovy P., State-of-the-art of vehicular traffic flow modelling, [in:] Proceedings of the Institution of Mechnical Engineers, Pt. 1, no. 215 (2001), pp. 283-303.

Hoogendoorn S., Bovy P., Pedestrian route-choice and activity scheduling theory and models, "Transportation Research. Part B", 38 (2004), pp. 169–190.

Hoogendoorn S., Bovy P., Dynamic user-optimal assignment in continuous time and space, "Transportation Research. Part B", 38 (2004), pp. 571–592.

Kirchner A., Nishinari K., Schadschneider A., Friction effects and clogging in a cellular automaton model for pedestrian dynamics, "Physical Review E", 67 (2003), pp. 56-122.

Klüpfel H., A cellular automaton Model for Crowd Movement and Egress Simulation, PhD thesis: Duisburg-Essen Universität, Duisburg 2003.

Klüpfel H., Meyer-König T., Characteristics of the PedGo software for crowd movement and egress simulation, [in:] Galea E. (ed.), Pedestrian and Evacuation Dynamics, CMS Press University of Greenwich, London 2003, pp. 331–340.

Knosala R., Zastosowania metod sztucznej inteligencji w inżynierii produkcji, Wydawnictwa Naukowo-Techniczne, Warszawa 2002.

Korbicz J., Kościelny J., Kowalczuk Z., Cholewa M., Diagnostyka procesów. Modele, metody sztucznej inteligencji, zastosowania, Wydawnictwa Naukowo-Techniczne, Warszawa 2002.

Lawrence K. D., Klimberg R. K., Lawrence S. M., Fundamentals of Forecasting Using Excel, ed. Industrial Press, 2009.

Løvas G., Modeling and simulation of pedestrian traffic flow, "Transportation Research B", 28 (1994)/6, pp. 429–443.

Menon P. K., Sweriduk G. D., Bilimoria K. D., A new approach to modeling, analysis and control of air traffic flow, Proc.AIAA Guide, Navigation Control Conference, Monterey 2002.

Menon P. K., Sweriduk G. D., Lam T., Cheng V. H. L., Bilimoria K. D., Air traffic flow modeling, analysis and control, [in:] Austin, TX Proceedings AIAA Guide, Navigation Control Conference, 2003.

Alias Lazim M., Econometric Forecasting Models and Model Evaluation: A Case Study of Air Passenger Traffic Flow, Lancaster University, Lancaster 1995.

Moon M., Demand and Supply Integration: The Key to World-Class Demand Forecasting, FT Press, USA, 2013.

Næss P., Andersen J., Nicolaisen M. S., Strand A., Transport modelling in the context of the ‘predict and provide’ paradigm, "European Journal of Transport and Infrastructure Research", 14 (2014)/2, pp. 102-121.

Nagel K., From particle hopping models to traffic flow theory, "Transportation Research Record", 1644 (1998), pp. 1–9.

Niebieska Księga. Sektor Transportu Publicznego w miastach, aglomeracjach, regionach, Jaspers, 2015 (eng. Blue Book for Sector of Public Transport in cities, agglomerations and regions issued by Joint Assistance to Support Projects in European Regions)

Ören T., Modeling and Simulation Body of Knowledge (M&SBoK)-Index, MSBOK, Ottawa 2010.

Prigogine I., Herman R., Kinetic Theory of Vehicular Traffic, American Elsevier, New York 1971.

Saric T., Simunovic G., Simunovic K., Use of Neural Networks in Prediction and Simulation of Steel Surface Roughness, "International Journal of Simulation Modelling", 12 (2013)/4, pp. 225-236.

Schadschneider A., Cellular automaton approach to pedestrian dynamics - theory, [in:] Sharma S., Schreckenberg M. (edd.), Pedestrian and Evacuation Dynamics, Springer, Berlin 2001, pp. 75–85.

Schelhorn T., O’Sullivan D., Haklay M., Thurstain-Goodwin M., STREETS: An agent based pedestrian model, [in:] College U. (ed.), Proceedings of Computers in Urban Planning and Urban Management, Centre for Advanced Spacial Analysis Working Paper Series, Paper 9, London 1999.

Still G., Crowd Dynamics, PhD thesis, University of Warwick, Coventry, 2000.

Teknomo K., Microscopic Pedestrian Flow Characteristics: Development of an Image Processing Data Collection and Simulation Model, PhD thesis, Graduate School of Information Sciences, Tohoku University, Tohoku 2002.

Vandepitte D., Moens D., Quantification of uncertain and variable model parameters in non-deterministic analysis, Springer, Berlin 2011.

Wageningen-Kessels F., Multi-class continuum traffic flow models: Analysis and simulation methods, TRAIL Thesis Series no. T2013/7, the Netherlands Research School TRAIL, Delft 2013.

Willis A., Kukla R., Kerridge J., Hine J., Laying the foundations: The use of video footage to explore pedestrian dynamics in PEDFLOW, [in:] Schreckenberg M., Sharma S. (edd.), Pedestrian and Evacuation Dynamics, Springer, Berlin 2001, pp. 181–186.

Yegnanarayana B., Artificial Neural Networks, PHI Learning Pvt. Ltd., India, 2004.

Yegnanarayana B., Artificial Neural Networks, Prentice-Hall of India Private Limited, New Delhi 2006.

Yuhaski S., Smith J., Modeling circulation systems in buildings using state dependent models, "Queuing Systems", 4 (1989), pp. 319–338.

Ziliaskopoulos S., Peeta A., Foundations of Dynamic Traffic Assignment: The Past, the Present and the Future, "Networks and Spatial Economics", 1 (2001)/4, pp. 233-266.


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