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A State-Dependent Approximation Method for Estimating Truck Queue Length at Marine Terminals

Author

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  • Wenrui Qu

    (School of Mathematics and Statistics, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China)

  • Tao Tao

    (Department of Transportation Studies, Texas Southern University, Houston, TX 77004-9986, USA)

  • Bo Xie

    (School of Mathematics and Statistics, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China)

  • Yi Qi

    (Department of Transportation Studies, Texas Southern University, Houston, TX 77004-9986, USA)

Abstract

As international trade and freight volumes increase, there is a growing port congestion problem, leading to the long truck queues at US marine terminal gates. To address this problem, some countermeasures have been proposed and implemented for reducing truck queue length at marine terminals. To assess the effectiveness of these countermeasures, a method for accurately estimating terminal gate truck queue length is needed. This study developed a new method, named the state-dependent approximation method, for estimating the truck queue length at marine terminals. Based on the simulation of the truck queuing system, it was found that it takes several hours for the truck queue length to reach its steady state, and neglecting the queue formation (queue dispersion) processes will cause overestimation (underestimation) of truck queue length. The developed model can take into account the queue formation and dispersion processes, and it can be used to estimate the truck queue length caused by short-term oversaturation at marine terminals. For model evaluation, a simulation-based case study was conducted to evaluate the prediction accuracy of the developed model by comparing its results with the simulated queue lengths and the results of other four existing methods, including the fluid flow model, the M/M/S queuing model, and a simulation-based regression model developed a previous study. The evaluation results indicate that the developed model outperformed the other four modeling methods for different states of queue formation and dispersion processes. In addition, this new method can accurately estimate the truck queue length caused by the short-term system oversaturation during peak hours. Therefore, it will be useful for assessing the effectiveness of the countermeasures that are targeted at reducing the peak-hour congestion at marine terminals.

Suggested Citation

  • Wenrui Qu & Tao Tao & Bo Xie & Yi Qi, 2021. "A State-Dependent Approximation Method for Estimating Truck Queue Length at Marine Terminals," Sustainability, MDPI, vol. 13(5), pages 1-18, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:5:p:2917-:d:512678
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    References listed on IDEAS

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    Cited by:

    1. Lange, Ann-Kathrin & Nellen, Nicole & Jahn, Carlos, 2022. "Truck appointment systems: How can they be improved and what are their limits?," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Jahn, Carlos & Blecker, Thorsten & Ringle, Christian M. (ed.), Changing Tides: The New Role of Resilience and Sustainability in Logistics and Supply Chain Management – Innovative Approaches for the Shift to a New , volume 33, pages 615-655, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    2. Karol Moszyk & Mariusz Deja & Michal Dobrzynski, 2021. "Automation of the Road Gate Operations Process at the Container Terminal—A Case Study of DCT Gdańsk SA," Sustainability, MDPI, vol. 13(11), pages 1-19, June.

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