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A behavioral car-following model that captures traffic oscillations

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  • Chen, Danjue
  • Laval, Jorge
  • Zheng, Zuduo
  • Ahn, Soyoung
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    Abstract

    This paper presents a behavioral car-following model based on empirical trajectory data that is able to reproduce the spontaneous formation and ensuing propagation of stop-and-go waves in congested traffic. By analyzing individual drivers’ car-following behavior throughout oscillation cycles it is found that this behavior is consistent across drivers and can be captured by a simple model. The statistical analysis of the model’s parameters reveals that there is a strong correlation between driver behavior before and during the oscillation, and that this correlation should not be ignored if one is interested in microscopic output. If macroscopic outputs are of interest, simulation results indicate that an existing model with fewer parameters can be used instead. This is shown for traffic oscillations caused by rubbernecking as observed in the US 101 NGSIM dataset. The same experiment is used to establish the relationship between rubbernecking behavior and the period of oscillations.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

    Volume (Year): 46 (2012)
    Issue (Month): 6 ()
    Pages: 744-761

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    Handle: RePEc:eee:transb:v:46:y:2012:i:6:p:744-761

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    Related research

    Keywords: Traffic oscillations; Car-following behavior; Reaction to oscillations; Driver heterogeneity; Rubbernecking;

    References

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    1. Bilbao-Ubillos, Javier, 2008. "The costs of urban congestion: Estimation of welfare losses arising from congestion on cross-town link roads," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(8), pages 1098-1108, October.
    2. 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.
    3. Li, Xiaopeng & Ouyang, Yanfeng, 2011. "Characterization of traffic oscillation propagation under nonlinear car-following laws," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1346-1361.
    4. Treiber, Martin & Kesting, Arne, 2011. "Evidence of convective instability in congested traffic flow: A systematic empirical and theoretical investigation," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1362-1377.
    5. Zheng, Zuduo & Ahn, Soyoung & Chen, Danjue & Laval, Jorge, 2011. "Freeway traffic oscillations: Microscopic analysis of formations and propagations using Wavelet Transform," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1378-1388.
    6. Ahn, Soyoung & Cassidy, Michael J. & Laval, Jorge, 2004. "Verification of a simplified car-following theory," Transportation Research Part B: Methodological, Elsevier, vol. 38(5), pages 431-440, June.
    7. Zheng, Zuduo & Ahn, Soyoung & Chen, Danjue & Laval, Jorge, 2011. "Applications of wavelet transform for analysis of freeway traffic: Bottlenecks, transient traffic, and traffic oscillations," Transportation Research Part B: Methodological, Elsevier, vol. 45(2), pages 372-384, February.
    8. Newell, G. F., 2002. "A simplified car-following theory: a lower order model," Transportation Research Part B: Methodological, Elsevier, vol. 36(3), pages 195-205, March.
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    Cited by:
    1. Chen, Danjue & Ahn, Soyoung & Laval, Jorge & Zheng, Zuduo, 2014. "On the periodicity of traffic oscillations and capacity drop: The role of driver characteristics," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 117-136.

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