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Microscopic modeling of the relaxation phenomenon using a macroscopic lane-changing model

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  • Laval, Jorge A.
  • Leclercq, Ludovic

Abstract

A crucial challenge faced by current microscopic traffic flow models is capturing the relaxation phenomena commonly observed near congested on-ramps: vehicles are willing to accept very short spacings as they enter the freeway, but "relax" to more comfortable values shortly thereafter. This paper introduces a framework to solve this problem using a macroscopic theory of vehicle lane-changing inside microscopic models. In this theory, lane changes take place according to a stochastic process that has been validated in the field, and whose mean value is a function of lane-specific macroscopic quantities. As a consequence, the lane-changing logic becomes very simple compared to existing microscopic lane-changing models, and requires only one extra parameter. The resulting microscopic model is validated with empirical data.

Suggested Citation

  • Laval, Jorge A. & Leclercq, Ludovic, 2008. "Microscopic modeling of the relaxation phenomenon using a macroscopic lane-changing model," Transportation Research Part B: Methodological, Elsevier, vol. 42(6), pages 511-522, July.
    • Handle: RePEc:eee:transb:v:42:y:2008:i:6:p:511-522
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    1. Newell, G. F., 1998. "A moving bottleneck," Transportation Research Part B: Methodological, Elsevier, vol. 32(8), pages 531-537, November.
    2. Newell, G. F., 1993. "A simplified theory of kinematic waves in highway traffic, part III: Multi-destination flows," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 305-313, August.
    3. Munoz, Juan Carlos & Daganzo, Carlos F, 2002. "Fingerprinting Traffic From Static Freeway Sensors," University of California Transportation Center, Working Papers qt1mf4n2w8, University of California Transportation Center.
    4. Cassidy, Michael J. & Rudjanakanoknad, Jittichai, 2005. "Increasing the capacity of an isolated merge by metering its on-ramp," Transportation Research Part B: Methodological, Elsevier, vol. 39(10), pages 896-913, December.
    5. Gipps, P.G., 1986. "Multsim: a model for simulating vehicular traffic on multi-lane arterial roads," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 28(4), pages 291-295.
    6. Laval, Jorge A. & Daganzo, Carlos F., 2006. "Lane-changing in traffic streams," Transportation Research Part B: Methodological, Elsevier, vol. 40(3), pages 251-264, March.
    7. Daganzo, Carlos F., 2006. "In traffic flow, cellular automata = kinematic waves," Transportation Research Part B: Methodological, Elsevier, vol. 40(5), pages 396-403, June.
    8. Leclercq, Ludovic, 2007. "Hybrid approaches to the solutions of the "Lighthill-Whitham-Richards" model," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 701-709, August.
    9. Daganzo, Carlos F., 2005. "A variational formulation of kinematic waves: basic theory and complex boundary conditions," Transportation Research Part B: Methodological, Elsevier, vol. 39(2), pages 187-196, February.
    10. Newell, G. F., 1993. "A simplified theory of kinematic waves in highway traffic, part I: General theory," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 281-287, August.
    11. Daganzo, Carlos F., 1997. "A continuum theory of traffic dynamics for freeways with special lanes," Transportation Research Part B: Methodological, Elsevier, vol. 31(2), pages 83-102, April.
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