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Truck travel time reliability and prediction in a port drayage network

Author

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  • Wenjuan Zhao

    (Freight System Division, Washington State Department of Transportation, Olympia, Washington 98504-7407, USA.)

  • Anne V Goodchild

    (Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98195-2700, USA.)

Abstract

Port drayage is an important component of the marine intermodal system and affects the efficiency of the intermodal supply chain. Sharing and utilizing drayage truck arrival information could improve both port drayage and port operational efficiency. To assess the feasibility of truck arrival time predictions, this research explores how reliable the port drayage network is. First, two reliability measures are used to evaluate how the travel time reliability changes with trip origins and across drayage networks. Then, the truck routing choices between Origin-Destination (OD) pairs are examined. Last, a simple method is proposed to predict the 95 per cent confidence interval of travel time between any OD pair and is validated with GPS data. The research results demonstrate that the proposed travel time prediction method is sufficient for predicting truck arrival time windows at the terminal and can be translated into truck arrival group information. It is therefore sufficient to support the implementation of a previously proposed container-handling strategy and to improve the efficiency of the drayage truck/container terminal interface.

Suggested Citation

  • Wenjuan Zhao & Anne V Goodchild, 2011. "Truck travel time reliability and prediction in a port drayage network," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 13(4), pages 387-418, December.
    • Handle: RePEc:pal:marecl:v:13:y:2011:i:4:p:387-418
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    Citations

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    Cited by:

    1. Behzad Behdani & Bart Wiegmans & Violeta Roso & Hercules Haralambides, 2020. "Port-hinterland transport and logistics: emerging trends and frontier research," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 22(1), pages 1-25, March.
    2. 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.
    3. Escudero-Santana, Alejandro & Muñuzuri, Jesús & Cortés, Pablo & Onieva, Luis, 2021. "The one container drayage problem with soft time windows," Research in Transportation Economics, Elsevier, vol. 90(C).
    4. Chen, Rui & Meng, Qiang & Jia, Peng, 2022. "Container port drayage operations and management: Past and future," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    5. Adel Ghazikhani & Samaneh Davoodipoor & Amir M. Fathollahi-Fard & Mohammad Gheibi & Reza Moezzi, 2024. "Robust Truck Transit Time Prediction through GPS Data and Regression Algorithms in Mixed Traffic Scenarios," Mathematics, MDPI, vol. 12(13), pages 1-26, June.

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