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Adaptive offsets for signalized streets

Author

Listed:
  • Daganzo, Carlos F.
  • Lehe, Lewis J.
  • Argote-Cabanero, Juan

Abstract

This paper shows that severe congestion on streets controlled by traffic signals can be reduced by dynamically adapting the signal offsets to the prevailing density with a simple rule that keeps the signals’ green-red ratios invariant. Invariant ratios reduce a control policy’s impact on the crossing streets, so a policy can be optimized and evaluated by focusing on the street itself without the confounding factors present in networks. Designed for heavy traffic with spillovers, the proposed policies are adaptive and need little data – they only require average traffic density readings and no demand forecasts.

Suggested Citation

  • Daganzo, Carlos F. & Lehe, Lewis J. & Argote-Cabanero, Juan, 2018. "Adaptive offsets for signalized streets," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 926-934.
    • Handle: RePEc:eee:transb:v:117:y:2018:i:pb:p:926-934
    DOI: 10.1016/j.trb.2017.08.011
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    References listed on IDEAS

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    1. Daganzo, Carlos F., 2011. "On the macroscopic stability of freeway traffic," Transportation Research Part B: Methodological, Elsevier, vol. 45(5), pages 782-788, June.
    2. Laval, Jorge A. & Castrillón, Felipe, 2015. "Stochastic approximations for the macroscopic fundamental diagram of urban networks," Transportation Research Part B: Methodological, Elsevier, vol. 81(P3), pages 904-916.
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    Keywords

    ISTTT22; Traffic signals; Adaptive offsets; MFD; Congestion;
    All these keywords.

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