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Estimation of delays at traffic signals for variable demand conditions

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  • Akçelik, Rahmi
  • Rouphail, Nagui M.

Abstract

This paper proposes a delay model for signalized intersections that is suitable for variable demand conditions. The model is applicable to the entire range of expected operations, including highly oversaturated conditions with initial queues at the start of the analysis period. The proposed model clarifies several issues related to the determination of the peak flow period, as well as the periods immediately preceding and following the peak. Separate formulas are provided for estimating delay in each of the designated flow periods as well as in the total flow period. Formulas are also provided to estimate the duration of the oversaturation period where applicable. The strength of the model lies in the use of simple rules for determining flow rates within and outside the peak, using the peak flow factor, a generalization of the well-known peak hour factor parameter. Simple rules are also provided for the identification of the location and duration of the peak flow period from observations of the demand profile. Such information is considered vital from an intersection design and evaluation viewpoint. Application of the model to a variety of operating conditions indicates that the estimated delay for vehicles arriving in the peak flow period is an acceptable predictor of the average delay incurred during the total flow period, even when oversaturation persists beyond the total flow period. On the other hand, the use of the average degree of saturation with no consideration of peaking can lead to significant underestimation of delay, particularly when operating at or near capacity conditions. These findings were confirmed by comparing the model results with other models found in the literature. The significant contribution of this work is not simply in the development of improved delay estimates, but, more important, in providing an integrated framework for an estimation process that incorporates (a) the peaking characteristics in the demand flow pattern, (b) the designation of flow-specific periods within the total flow period in accordance with the observed peaking and (c) the estimation of performance parameters associated within each flow period and in combination with other periods. A revised delay formula for the U.S. Highway Capacity Manual (HCM) is proposed. The revised formula has no constraints on the peak flow period degree of saturation, unlike the current HCM formula. It is also recommended that a simple formula for estimating the duration of oversaturation be used in conjunction with the revised delay formula.

Suggested Citation

  • Akçelik, Rahmi & Rouphail, Nagui M., 1993. "Estimation of delays at traffic signals for variable demand conditions," Transportation Research Part B: Methodological, Elsevier, vol. 27(2), pages 109-131, April.
  • Handle: RePEc:eee:transb:v:27:y:1993:i:2:p:109-131
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    Cited by:

    1. Wei Huang & Guangming Xu & Hong K. Lo, 2020. "Pareto-Optimal Sustainable Transportation Network Design under Spatial Queuing," Networks and Spatial Economics, Springer, vol. 20(3), pages 637-673, September.
    2. Raadsen, Mark P.H. & Bliemer, Michiel C.J., 2019. "Steady-state link travel time methods: Formulation, derivation, classification, and unification," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 167-191.
    3. Elżbieta Macioszek & Agata Kurek, 2020. "The Use of a Park and Ride System—A Case Study Based on the City of Cracow (Poland)," Energies, MDPI, vol. 13(13), pages 1-26, July.
    4. Fernandez, Rodrigo & Valenzuela, Eduardo & Casanello, Federico & Jorquera, Carola, 2006. "Evolution of the TRANSYT model in a developing country," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(5), pages 386-398, June.
    5. Luigi Moccia & Duncan W. Allen & Eric C. Bruun, 2018. "A technology selection and design model of a semi-rapid transit line," Public Transport, Springer, vol. 10(3), pages 455-497, December.
    6. Bliemer, Michiel C.J. & Raadsen, Mark P.H. & Smits, Erik-Sander & Zhou, Bojian & Bell, Michael G.H., 2014. "Quasi-dynamic traffic assignment with residual point queues incorporating a first order node model," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 363-384.
    7. Ran, Bin & Rouphail, Nagui M. & Tarko, Andrzej & Boyce, David E., 1997. "Toward a class of link travel time functions for dynamic assignment models on signalized networks," Transportation Research Part B: Methodological, Elsevier, vol. 31(4), pages 277-290, August.
    8. Tirachini, Alejandro & Hensher, David A., 2011. "Bus congestion, optimal infrastructure investment and the choice of a fare collection system in dedicated bus corridors," Transportation Research Part B: Methodological, Elsevier, vol. 45(5), pages 828-844, June.
    9. Suhaib Alshayeb & Aleksandar Stevanovic & Nikola Mitrovic & Elio Espino, 2022. "Traffic Signal Optimization to Improve Sustainability: A Literature Review," Energies, MDPI, vol. 15(22), pages 1-24, November.
    10. Dion, Francois & Rakha, Hesham & Kang, Youn-Soo, 2004. "Comparison of delay estimates at under-saturated and over-saturated pre-timed signalized intersections," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 99-122, February.
    11. Viti, Francesco & van Zuylen, Henk J., 2010. "Probabilistic models for queues at fixed control signals," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 120-135, January.

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