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Public Transport

, Volume 7, Issue 3, pp 355–367 | Cite as

Analyzing railroad congestion in a dense urban network through the use of a road traffic network fundamental diagram concept

  • Pierre-Antoine CuniasseEmail author
  • Christine Buisson
  • Joaquin Rodriguez
  • Emmanuel Teboul
  • David de Almeida
Original Paper
  • 358 Downloads

Abstract

Transilien, the SNCF branch in charge of operating the main urban railroad network in the area of Paris, faces a regular increase of passenger flows. The planning of railway operations is made carefully through simulation runs which help to assess the timetable stability. However, many disturbances appear and cause train delays. Due to the nature of the railroad network those delays are cumulative and an on-line update of the timetable is not always successful in maintaining the trains schedules. In this tensed context, operators are searching solutions to enhance the use of the infrastructure capacity and achieve a better service quality. A needed step towards this objective is a better understanding of the phenomena of disruptions, in particular because the expansion of congestion is so far not clearly understood. This paper explores the possibility to transpose a traffic flow theory tool, the network fundamental diagram, in the field of dense railroad traffic. Railroad traffic is different from road traffic in many ways: railways are a planned system, traffic volume does not satisfy the continuum hypothesis, stations force stops and the signalization system brings a discrete behavior. Despite those big differences we show how to build a similar tool for a railroad system, the Line Fundamental Diagram (LFD), and how to interpret some obtained shapes for those diagrams. These diagrams give us some means to compare plan and reality. We also identify the limits that have to be overcome to take benefits of the road traffic tools in railroad traffic analysis.

Keywords

Railroad Mass transit Congestion Line fundamental diagram 

Notes

Acknowledgments

This research is conducted with the benefit of a PhD grant from Agence Nationale de la Recherche Technologique, France. The authors want to thank Ludovic Leclercq and Winnie Daamen for fruitful discussions during the preparation of this paper.

References

  1. Buisson C, Ladier C (2009) Exploring the impact of the homogeneity of traffic measurements on the existence of macroscopic fundamental diagrams. Transp Res Rec:127–136 Google Scholar
  2. Cassidy M, Jang K, Daganzo C (2011) Macroscopic fundamental diagrams for freeway networks: theory and observation. Transp Res Rec 2260: 8–15 Google Scholar
  3. Chiabaut N (2015) Evaluation of a multimodal urban arterial: the passenger macroscopic fundamental diagram. Transp Res Part B Google Scholar
  4. Courbon T, Leclercq L (2011) Cross-comparison of macroscopic fundamental diagram estimation methods. Proced Soc Behav Sci 20:417–426 Google Scholar
  5. Daganzo C (2007) Urban gridlock: Macroscopic modeling and mitigation approaches. Transp Res B 41(1):49–62)Google Scholar
  6. Daganzo C, Gayah V, Gonzales E (2011) Macroscopic relations of urban traffic variables: bifurcations, multivaluedness and instability. Transp Res Part B Methodol 45(1): 278–288Google Scholar
  7. Daganzo CF, Geroliminis N (2008) An analytical approximation for the macroscopic fundamental diagram of urban traffic. Transp Res Part B Methodol 42(9):771–781. doi: 10.1016/j.trb.2008.06.008 CrossRefGoogle Scholar
  8. Geroliminis N, Daganzo C (2007) Macroscopic modeling of traffic in cities. Transp Res Board (07-0413)Google Scholar
  9. Geroliminis N, Daganzo CF (2008) Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings. Transp Res Part B Methodol 42(9):759–770. doi: 10.1016/j.trb.2008.02.002 CrossRefGoogle Scholar
  10. Geroliminis N, Sun J (2011) Properties of a well-defined macroscopic fundamental diagram for urban traffic. Transp Res Part B Methodol 45(3):605–617. doi: 10.1016/j.trb.2010.11.004 CrossRefGoogle Scholar
  11. Geroliminis N, Sun J (2011) Properties of a well-defined macroscopic fundamental diagram for urban traffic. Transp Research Part B Methodol 45(3):605–617CrossRefGoogle Scholar
  12. Geroliminis N, Zheng N, Ampountolas K (2014) A three-dimensional macroscopic fundamental diagram for mixed bi-modal urban networks. Transp Res Part C EmergTechnol 42:168–181. doi: 10.1016/j.trc.2014.03.004 CrossRefGoogle Scholar
  13. Godfrey J (1969) The mechanism of a road network. Traffic Eng Control 11(7):323–327Google Scholar
  14. Gonzales EJ (2015) Coordinated pricing for cars and transit in cities with hypercongestion. Econ Transp. doi: 10.1016/j.ecotra.2015.04.003
  15. Gonzales EJ, Geroliminis N, Cassidy MJ, Daganzo CF (2010) On the allocation of city space to multiple transport modes. Transp Plan Technol 33(8):643–656CrossRefGoogle Scholar
  16. Goverde R (2005) Punctuality of railway operations and timetable stability analysis. Ph.D. thesis, Delft University of TechnologyGoogle Scholar
  17. Haddad J, Geroliminis N (2012) On the stability of traffic perimeter control in two-region urban cities. Transp Research Part B Methodol 46(9):1159–1176. doi: 10.1016/j.trb.2012.04.004 CrossRefGoogle Scholar
  18. Haddad J, Ramezani M, Geroliminis N (2013) Cooperative traffic control of a mixed network with two urban regions and a freeway. Transp Research Part B Methodol 54:17–36. doi: 10.1016/j.trb.2013.03.007 CrossRefGoogle Scholar
  19. Herman R, Prigogine I (1979) A two-fluid approach to town traffic. Science 204:148–151Google Scholar
  20. Mahmassani HS, Williams JC, Herman R (1984) Investigations of network-level traffic flow relationships: some simulation results. Transp Res Record 971:121–130Google Scholar
  21. Ji Y, Geroliminis N (2012) On the spatial partitioning of urban transportation networks. Transp Research Part B Methodol 46(10):1639–1656. doi: 10.1016/j.trb.2012.08.005 CrossRefGoogle Scholar
  22. Ji Y, Geroliminis N (2012) On the spatial partitioning of urban transportation networks. Transp Research Part B Methodol 46(10):1639–1656CrossRefGoogle Scholar
  23. Keyvan-Ekbatani M, Kouvelas A, Papamichail I, Papageorgiou M (2012) Exploiting the fundamental diagram of urban networks for feedback-based gating. Transp Research Part B Methodol 46(10):1393–1403. doi: 10.1016/j.trb.2012.06.008 CrossRefGoogle Scholar
  24. Keyvan-Ekbatani M, Papageorgiou M, Papamichail I (2013) Urban congestion gating control based on reduced operational network fundamental diagrams. Transp Res Part C Emerg Technol 33:74–87. doi: 10.1016/j.trc.2013.04.010 CrossRefGoogle Scholar
  25. Knoop V, Hoogendoorn S, Lint HV (2012) Routing strategies based on the macroscopic fundamental diagram. Transp Res Rec J Transp Res Board 2315:1–10CrossRefGoogle Scholar
  26. Lai YC, Liu YH, Lin YJ (2013) Development of base train equivalents for headway-based analytical railway capacity analysis. RailCopenhagenGoogle Scholar
  27. Nash A, Hurlimann, D (2004) Railroad simulation using opentrack. In: Proceedings of the 9th COMPRail conference (Computers in Railways IX)Google Scholar
  28. Radtke A., Bendfeld JP (2001) Handling of railway operation problems with railsys. In: WCRR-Proceedings, KolnGoogle Scholar
  29. Saberi M, Mahmassani HS (2012) Exploring the properties of network-wide flow-density relations in a freeway network. Transp Res Rec 2315:153–163Google Scholar
  30. Saberi M, Mahmassani HS, Hou T, Zockaie A (2014) Estimating network fundamental diagram using three-dimensional vehicle trajectories: Extending edie’s definitions of traffic flow variables to networks. Transp Res Rec J Transp Res Board 2422:12–20CrossRefGoogle Scholar
  31. UIC (1996) Links between railway infrastructure capacity and the quality of operations. International Union of Railways (UIC code 405) Google Scholar
  32. UIC (2004) Capacity. International Union of Railways (UIC code 406)Google Scholar
  33. Zheng N, Geroliminis N (2013) On the distribution of urban road space for multimodal congested networks. Transp Research Part B Methodol 57:326–341CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Pierre-Antoine Cuniasse
    • 1
    • 2
    Email author
  • Christine Buisson
    • 2
    • 3
  • Joaquin Rodriguez
    • 4
  • Emmanuel Teboul
    • 1
  • David de Almeida
    • 5
  1. 1.SNCF-TransilienParisFrance
  2. 2.IFSTTARParisFrance
  3. 3.ENTPEVaux-en VelinFrance
  4. 4.ESTAS-IFSTTARVilleneuve d’AscqFrance
  5. 5.SNCF-I&RParisFrance

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