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Tytuł artykułu

The link transmission model: an efficient implementation of kinematics wave theory for dynamic network loading

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Warianty tytułu
PL
Model ruchu LTM: efektywne zastosowanie teorii fali kinematycznej dla dynamicznego obciążania sieci ulic
Języki publikacji
EN
Abstrakty
EN
This paper presents a numerical solution method for a dynamic network loading (DNL) model that is consistent with the first order kinematics wave theory. The multi-commodity link transmission model (MC LTM) determines time-dependent link volumes, link travel times and route travel times on a traffik network, given the time-dependent route flow rates. Compared to existing cell transmission models, the MC LTM provides the same realism of traffik flow propagation. The computational complexity however is substantially smaller, since the procedure requires only calculations at network nodes.
PL
Artykuł przedstawia metodę numerycznego rozwiązywania modelu dynamicznego obciążania sieci ulic (DNL) zgodnego z teorią fali kinematycznej pierwszego rzędu. Wielościeżkowy model (MC LTM) wyznacza dla założonych, zależnych od czasu intensywności przepływów: natężenia ruchu na połączeniach, czasy podróży dla połączeń i czasy podróży dla ścieżek sieci. Model MC LTM charakteryzuje się podobną adekwatnością jak istniejące modele CTM, jednakże jego złożoność obliczeniowa jest istotnie mniejsza, ponieważ wymaga obliczeń jedynie w węzłach sieci.
Rocznik
Strony
147--167
Opis fizyczny
Bibliogr. 28 poz., rys.
Twórcy
autor
autor
autor
autor
  • Katholieke Universiteit Leuven, Transportation Planning and Highway Engineering, Belgium
Bibliografia
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  • 3. Carey M.: Optimal Time Varying Flows On Congested Networks. Operations Research, 35(1), 1987, pp. 58-69.
  • 4. Chen H.-K., Hsueh C.F.: A Model and an AIgorithm for the Dynamic User Optimal Route Choice Problem. Transportation Research, 32B(3), 1998, pp. 219-234.
  • 5. Daganzo C.F.: The cell-transmission model. A dynamic representation of highway traffic consistent with the hydrodynamic theory. Transportation Research, 28B, 1994, pp. 269-288.
  • 6. Daganzo C.F.: The cell transmission model, part II: network traffic. Transportation Research, 29B, 1995, pp. 79-94.
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  • 8. Janson B.N.: Convergent Algorithm for Dynamic Traffic Assignment. Transportation Research Record, 1328, 1991, pp. 69-80.
  • 9. Jin W.L., Zhang H.M.: On the distribution schemes for determining flows through a merge. Transportation Research, 37B, 2003, pp. 521-540.
  • 10. Jin WL, Zhang H.M.: A multicommodity kinematic wave simulation model of network traffic flow. Transportation Research Record: Journal of the Transportation Research Board, 1883: 59-67, 2004.
  • 11. Kuwahara M. and Akamatsu T.: Dynamic user optimal assignment with physical queues for a many-to-many OD pattern. Transportation Research 35B, 2001, pp. 461-479.
  • 12. Lebacque J.P.: The Godunov scheme and what it means for first order traffic flow models. Proceedings of the 13th ISTTT. Ed. J. B. Lesort, 1996.
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  • 14. Lo H.K., Szeto W.Y.: A cell-based variational inequality formulation of the dynamic user optimal assignment problem. Transportation Research, B(36), 2002a, pp. 421-443.
  • 15. Lo H.K., Szeto W.Y.: A cell-based dynamic traffic assignment model: formulation and properties. Mathematical and computer modelling, 35 (7-8), 2002b, pp. 849-865.
  • 16. Lo H.K., Szeto W.Y.: Pradigms of Modeling Advanced Traveler Information Services. Proceedings of the IEEE 5th International Conference on Intelligent Transportation Systems (ITSC '02), 2002c, pp. 460-465A.
  • 17. Lo H.K.: A dynamic traffic assignment formulation that encapsulates the cell transmission model. [In:] A. Ceder (ed.): Transprotation and Traffic Theory. Pergamon, Oxford, 1999, pp. 327-350.
  • 18. Merchant D.K., Nemhauser G.L.: Optimality Conditions for a Dynamic Traffic Assignment Model. Transportation Science, 12(3), 1978a, pp. 200-207.
  • 19. Merchant D.K., Nemhauser G.L.: A model and an algorithm for the Dynamic Traffic Assignment Problems. Transportation Science, 12(3), 1978b, pp. 183-199.
  • 20. Newell G.F.: A simplified theory of kinematic waves in highway traffic. Part I: General theory. Part II: Queuing at freeway bottlenecks. Part III: Multi-destination flows. Transportation Research 27B, 1993, pp. 281-313.
  • 21. Peeta S., Ziliaskopoulos A.K.: Foundations of Dynamic Traffic Assignment: The Past, the Present and the Future. Networks and Spatial Economics, 1, 2001, pp. 233-265.
  • 22. Ran B., Boyce D.E.: A link-based Variational Inequality Formulation of Ideal Dynamic User Optimal Route Choice Problem. Transportation Research, 4C(I), 1996, pp. 1-12.
  • 23. Richards P.I.: Shockwaves on the highway. Operations Research, 4, 1956, pp. 42-51.
  • 24. Szeto W.Y., Lo H.K.: A cell-based simultaneous route and departure time choice model with elastic demand. Transportation Research, B(38), 2004, pp. 593-612.
  • 25. Waller S.T., Ukkusuri S.V.: A linear programming formulation for the user optimal dynamic traffic assignment problem. Transportation Science, February 2003.
  • 26. Wie B.W., Tobin R.L., Friesz T.L., Bernstein D.: A Discrete Time, Nested Cost Operator Approach to the Dynamic Network User Equilibrium Problem. Transportation Science, 29(1), 1995, pp. 79--92.
  • 27. Yperman I., Logghe S., Immers L.H.: The Link Transmission Model: An efficient implementation of the kinematic wave theory in traffic networks. Proceedings of the 10th EWGT Meeting, Poznań, Poland, 2005.
  • 28. Zhang H.M., Nie Y: Modeling network flow with and without link interactions: properties and implications. Proc. 84th Annual Meeting of the TRB, Washington, DC, 2005.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPZ4-0009-0025
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