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Advanced information feedback strategy in intelligent two-route traffic flow systems

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Abstract

The optimal information feedback has a significant effect on many socioeconomic systems like stock market and traffic systems aiming to make full use of resources. In this paper, we study dynamics of traffic flow with real-time information. The influence of a feedback strategy named vehicle number feedback strategy (VNFS) is introduced, in which we only calculate the vehicle number of first 500 route sites from the entrance. Moreover, the two-route traffic system has only one entrance and one exit, which is different from those in the previous work. Our model incorporates the effects of adaptability into the cellular automaton models of traffic flow, and simulation results by adopting this optimal information feedback strategy have demonstrated higher efficiency in controlling spatial distribution of traffic patterns than the other three information feedback strategies, i.e., TTFS, MVFS and CCFS.

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References

  1. Chowdhury D, Santen L, Schadschneider A. Statistical physics of vehicular traffic and some related systems. Phys Rep, 2000, 329: 199–329

    Article  MathSciNet  Google Scholar 

  2. Helbing D. Traffic and related self-driven many-particle systems. Rev Mod Phys, 2001, 73: 1067–1141

    Article  Google Scholar 

  3. Nagatani T. The physics of traffic jams. Rep Prog Phys, 2002, 65: 1331–1386

    Article  Google Scholar 

  4. Long J C, Gao Z Y, Ren H L, et al. Urban traffic congestion propagation and bottleneck identification. Sci China Ser F-Inf Sci, 2008, 51: 948–964

    Article  MathSciNet  Google Scholar 

  5. Rothery R W. Traffic flow theory. In: Gartner N, Messner C J, Rathi A J, eds. Transportation Research Board Special Report, Vol. 165. Washington, DC: Transportation Research Board, 1992. Chap. 4

    Google Scholar 

  6. Paveri-Fontana S L. Boltzmann-like treatments for traffic flow-critical review of basic model and an alternative proposal for dilute traffic analysis. Transp Res, 1975, 9: 225–235

    Article  Google Scholar 

  7. Lehmann H. Distribution function properties and the fundamental diagram in kinetic traffic flow theory. Phys Rev E, 1996, 54: 6058–6064

    Article  MathSciNet  Google Scholar 

  8. Wagner C, Hoffmann C, Sollacher R, et al. Second-order continuum traffic flow model. Phys Rev E, 1996, 54: 5073–5085

    Article  Google Scholar 

  9. Helbing D. Gas-kinetic derivation of Navier-Stokes-like traffic equations. Phys Rev E, 1996, 53: 2366–2381

    Article  MathSciNet  Google Scholar 

  10. Helbing D, Treiber M. Gas-kinetic-based traffic model explaining observed hysteretic phase transition. Phys Rev Lett, 1998, 81: 3042–3045

    Article  Google Scholar 

  11. Dong L F, Shu Y T, Chen H M, et al. Packet delay analysis on IEEE 802.11 DCF under finite load traffic in multi-hop ad hoc networks. Sci China Ser F-Inf Sci, 2008, 51: 408–416

    Article  MATH  MathSciNet  Google Scholar 

  12. Nagel K, Schreckenberg M. A cellular automaton model for freeway traffic. J Phys I, 1992, 2: 2221–2229

    Article  Google Scholar 

  13. Biham O, Middleton A A, Levine D. Self-organization and a dynamic transition in traffic-flow models. Phys Rev A, 1992, 46: R6124–R6127

    Article  Google Scholar 

  14. Yokoya Y. Dynamics of traffic flow with real-time traffic information. Phys Rev E, 2004, 69: 016121

    Article  Google Scholar 

  15. Friesz T L, Luque J, Tobin R L, et al. Dynamic network traffic assignment considered as a continuous-time optimalcontrol problem. Oper Res, 1989, 37: 893–901

    Article  MATH  MathSciNet  Google Scholar 

  16. Ben-Akiva M, De Palma A, Kaysi I. Dynamic network models and driver information-systems. Transp Res Part A, 1991, 25: 251–266

    Article  Google Scholar 

  17. Dong C F, Ma X, Wang B H. Weighted congestion coefficient feedback in intelligent transportation systems. Phys Lett A, 2010, 374: 1326–1331

    Article  Google Scholar 

  18. Arnott R, de Palma A, Lindsey R. Does providing information to drivers reduce traffic congestion. Transp Res Part A, 1991, 25: 309–318

    Article  Google Scholar 

  19. Kachroo P, Özbay K. Real time dynamic traffic routing-based on fuzzy feedback control methodology. Transp Res Rec, 1996, 1556: 137–146

    Article  Google Scholar 

  20. Wahle J, Bazzan A L C, Klügl F, et al. Decision dynamics in a traffic scenario. Phys A, 2000, 287: 669–681

    Article  Google Scholar 

  21. Lee K, Hui P M, Wang B H, et al. Effects of announcing global information in a two-route traffic flow model. J Phys Soc Jpn, 2001, 70: 3507–3510

    Article  Google Scholar 

  22. Wang W X, Wang B H, Zheng W C, et al. Advanced information feedback in intelligent traffic systems. Phys Rev E, 2005, 72: 066702

    Article  Google Scholar 

  23. Wang B H, Mao D, Hui P M. The two-way decision traffic flow model: mean field theory. In: Proceedings of the Second International Symposium on Complexity Science, Shanghai, 2002. 204

  24. Wang B H, Wang L, Xu B M, et al. The gradual accelerating traffic flow gellular automaton model in which only high speed car can be delayed. Acta Phys Sin, 2000, 49: 1926–1932

    Google Scholar 

  25. Fu C J, Wang B H, Ying C Y, et al. Intelligent decision-making in a two-route traffic flow model. Acta Phys Sin, 2006, 55: 4032–4038

    Google Scholar 

  26. Peng L J, Kang R. One-dimensional cellular automaton model of traffic flow considering drivers’ features. Acta Phys Sin, 2009, 58: 830–835

    Google Scholar 

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Correspondence to ChuanFei Dong.

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Dong, C., Ma, X. & Wang, B. Advanced information feedback strategy in intelligent two-route traffic flow systems. Sci. China Inf. Sci. 53, 2265–2271 (2010). https://doi.org/10.1007/s11432-010-4070-1

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