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

Abstract


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.


Keywords


integrated approach, transportation network, simulation model

Full Text:

PDF

References


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

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

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

V. Blue, J. Adler, Modeling four-directional pedestrian flows. Transportation Research Record, Issue no. 1710 (2000) pp. 20–27.

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

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

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

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

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

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

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

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

M. Griliches, Z. Intriligator, Handbook of Econometrics, Volume 1, Chapter 3, ed. Los Angeles, CA, USA: North Holland, 1983, pp. 182-187.

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

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

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

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

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

S. Hoogendoorn, P. Bovy, State-of-the-art of vehicular traffic flow modelling, Proceedings of the Institution of Mechnical Engineers, Part I no. 215 (2001) pp. 283-303.

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

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

A. Kirchner, K. Nishinari, A. Schadschneider, Friction effects and clogging in a cellular automaton model for pedestrian dynamics, Physical Review, E 67(056122) (2003).

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

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

R. Knosala,. Zastosowania metod sztucznej inteligencji w inżynierii produkcji (eng. Applying Artificial Intelligence Methods in Production Engineering), Warsaw, Wydawnictwa Naukowo-techniczne, 2002.

J. Korbicz, J. Kościelny, Z. Kowalczuk, M. Cholewa, Diagnostyka procesów. Modele, metody sztucznej inteligencji, zastosowania (eng. Process diagnostics. Models, artificial intelligence methods and applications). pp. 315 ed. Warsaw: Wydawnictwa Naukowo-Techniczne, 2002.

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

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

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

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

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

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

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

K. Nagel, From particle hopping models to traffic flow theory, Transportation Research Record, Issue 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)

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

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

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

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

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

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

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

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

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

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

B. Yegnanarayana, Artificial Neural Networks, PHI Learning Pvt. Ltd., India, 2004, pp. 280

B. Yegnanarayana, Artificial Neural Networks, New Delhi: Prentice-Hall of India Private Limited, 2006 pp. 24.

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

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


Refbacks

  • There are currently no refbacks.