Journal of Korean Society of Transportation (대한교통학회지)

Korean Society of Transportation (대한교통학회)
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Analysis of Characteristics of the Dynamic Flow-Density Relation and its Application to Traffic Flow Models

동적 교통량-밀도 관계의 특성 분석과 교통류 모형으로의 응용

  • Kim, Young-Ho (Youngsan University, School of Network & Information Engineering) ;
  • Lee, Si-Bok (Youngsan University, School of Network & Information Engineering)
  • Published : 2004.06.30
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Abstract

Online traffic flow modeling is attracting more attention due to intelligent transport systems and technologies. The flow-density relation plays an important role in traffic flow modeling and provides a basic way to illustrate traffic flow behavior under different traffic flow and traffic density conditions. Until now the research effort has focused mainly on the shape of the relation. The time series of the relation has not been identified clearly, even though the time series of the relation reflects the upstream/downstream traffic conditions and should be considered in the traffic flow modeling. In this paper the flow-density relation is analyzed dynamically and interpreted as a states diagram. The dynamic flow-density relation is quantified by applying fuzzy logic. The quantified dynamic flow-density relation builds the basis for online application of a macroscopic traffic flow model. The new approach to online modeling of traffic flow applying the dynamic flow-density relation alleviates parameter calibration problems stemming from the static flow-density relation.

지능형 교통체계(intelligent transport systems)의 구축이 점차 널리 확대됨에 따라 교통류의 실시간 모형화(online traffic flow modeling)의 중요성이 증대되고 있다. 교통량-밀도 관계는 주어진 교통량, 밀도 상황에서 교통류의 행태를 나타낼 뿐만 아니라 거시 교통류 모형의 결과에 많은 영향을 미친다. 현재까지 교통량-밀도관계에 관한 대부분의 연구는 그 관계식을 규명하는데 그치고 있다. 상류부와 하류부의 교통 상태에 따른 교통량-밀도관계의 시간적 변화는 교통류의 모형화에 반드시 고려되어야 할 특성이지만, 현재까지 그에 대한 연구가 폭넓게 이루어지지 않고 있는 실정이다. 본 논문에서는 한 지점에서의 교통량-밀도관계가 시간의 흐름에 따라 분석되었고 states diagram으로 표현되었다. 동적 교통량-밀도관계 (dynamic flow-density relation)는 states diagram으로부터 fuzzy-logic을 이용하여 유추되었고, 거시 교통류모형을 실시간으로 응용할 수 있는 기초를 제공하였다. 동적 교통량-밀도관계를 거시 교통류 모형에 이용함으로써 교통류의 실시간 모형화 과정에서 발생하는 모수추정 (parameter calibration) 문제를 완화하였다.

Keywords

References

  1. Belzner H. (2002), 'Ein hybrides Modell zur Kurzfristprognose lokaler VerkehrsgroBen' Diplomarbeit at Munich University of Technology
  2. Cassidy M. and R. Bertini (1999), 'Some traffic features at freeway bottlenecks' Transportation Research B 33, pp.25-42 https://doi.org/10.1016/S0191-2615(98)00023-X
  3. Daganzo F. C. (1994), 'The cell-transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory' Transportation Research B 28, pp.269-287 https://doi.org/10.1016/0191-2615(94)90002-7
  4. Daganzo F. C. (1995), 'Part II: Network Traffic' Transportation Research B 29, pp.79-93 https://doi.org/10.1016/0191-2615(94)00022-R
  5. Daganzo F. C. (1999a), 'The Lagged Cell-Transmission Model' Proceedings of the four-International Symposium on Transportation and Traffic Theory, Jerusalem, Israel, pp.147-171
  6. Daganzo F. C. (1999b), 'A Behavioral Theory of Multi-Lane Traffic Flow Part I: Long Homogeneous Freeway Sections' Rsearch Report University of California Berkeley-ITS-RR-99-5
  7. Hall L. F. and T. Lam (1988), 'The Characteristics of Congested Flow on a Freeway across Lanes, Space and Time' Transportation Research A 22, pp.45-56 https://doi.org/10.1016/0191-2607(88)90062-3
  8. Helbing D. A. Hennecke and M. Treiber (1999), 'Phase Diagram of Traffic States in the Presence of Inhomogeneities' Phys. Rev. Lett. 82, pp.4360-4363 https://doi.org/10.1103/PhysRevLett.82.4360
  9. Isaacs A. (1996), 'A Dictionary of Physics the third Edition' Oxford University Press
  10. Kerner B. S. and H. Rehborn (1996a) 'Experimental properties of complexity in traffic flow' Phys. Rev. E, 53, pp.4275-4278 https://doi.org/10.1103/PhysRevE.53.R4275
  11. Kerner B. S. P. Konhauser and M. Schilke (1996b), 'Dipole-layer effect in dense traffic flow' Phys. Lett. A 215, pp.45-56 https://doi.org/10.1016/0375-9601(96)00114-4
  12. Kerner B. S. (1999), 'Theory of Congested Traffic Flow: Self-Organization without Bottlenecks' Proceedings of the fourteenth International Symposium on Transportation and Traffic Theory, Jerusalem, Israel, pp.147 -171
  13. Kerner B. S., H. Rehborn H., M. Aleksic and A. Haug (2001), 'Methods for tracing & forecasting congested traffic patterns' tec. September, 2001
  14. Kim Y. (2002), 'Online Traffic Flow Model Applying Dynamic Flow-Density Relations' Ph.D Thesis at Munich University of Technology
  15. Koshi M., M. Iwasaki and I. Ohkura (1983), 'Some findings and an overview on vehicular flow characteristics' Proceedings of the eighth International Symposium on Transportation and Traffic Theory, Toronto, Canada
  16. Lange (2000), 'Traffic data of the German freeway A5' Autobahnamt Frankfurt
  17. Lee H. Y. H.-W. Lee and D. Kim (1999), 'Dynamic states of a continuum traffic equation with on-ramp' Phys. Rev. E, 59, pp.5101-5111 https://doi.org/10.1103/PhysRevE.59.5101
  18. Lighthill M. J. and G. B. Whitham (1955), 'On kinetic waves II: A theory of traffic flow on long crowded roads' Proceedings Royal Society, London, A 229, pp.317-345
  19. Poschinger A. (1999), 'Netzbeeinflussung auf Autobahnen mit dynamischen Sollwerten im Entscheidungsalgorithmus' Ph. D Thesis of Munich University of Technology
  20. Prigogine I. and R. Herman (1971), 'Kinetic Theory of Vehicular Traffic' American Elsevier, New York
  21. Woltereck (2000), 'Traffic data of the German freeway A8' Autobahndirektion Sudbayern, Munich within the investigation: Keller H., Steinhoff C., Glas F., 2000. A8W Lkw-Uberholverbot und Tempo 120
  22. Treiterer J. and J. A. Myers (1974), 'The hysteresis Phenomenon in Traffic Flow' Proceedings of the sixth International Symposium on Transportation and Traffic Theory, Sydney, Australia, pp.13-38
  23. Zhang H. M. (1999), 'A mathematical theory of traffic hysteresis' Transportation Research B 33, pp.1-23 https://doi.org/10.1016/S0191-2615(98)00022-8