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Make or break: Coordinated assignment of parking space for breaks and rest periods in long-haul trucking

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  • Pilz, Danny
  • Schwerdfeger, Stefan
  • Boysen, Nils

Abstract

To avoid traffic accidents due to driver fatigue in long-haul trucking, there are laws and provisions all over the world that regulate breaks and rest periods of truck drivers. When aiming to follow the existing hours of service regulations, however, parking space for trucks in service areas is often scarce, especially along crowded mainlines. In this context, the paper on hand investigates whether a central platform coordinating the usage of limited parking capacity on the supply side and truck drivers’ individual drive and rest schedules on the demand side can be advantageous. Specifically, we formulate a holistic optimization problem, which jointly determines the drive and rest schedules for a given set of trucks with fixed routes and coordinates their assignment to a limited number of available parking spaces over time. To solve this problem, we introduce a heuristic solution procedure, which is benchmarked with the status quo, where each driver seeks parking space individually, and a booking platform that allows to reserve parking space ahead of arrival. Our computational results reveal that a booking platform that produces much less organizational overhead is almost as effective as a central matching platform based on perfect knowledge of all truck schedules.

Suggested Citation

  • Pilz, Danny & Schwerdfeger, Stefan & Boysen, Nils, 2022. "Make or break: Coordinated assignment of parking space for breaks and rest periods in long-haul trucking," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 45-64.
    • Handle: RePEc:eee:transb:v:164:y:2022:i:c:p:45-64
    DOI: 10.1016/j.trb.2022.08.002
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    References listed on IDEAS

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    Cited by:

    1. Marina Kouta & Yorgos Stephanedes, 2023. "Disaggregate Modelling for Estimating Location Choice of Safe and Secure Truck Parking Areas: A Case Study," Sustainability, MDPI, vol. 15(20), pages 1-20, October.
    2. Schuster, Amy M. & Agrawal, Shubham & Britt, Noah & Sperry, Danielle & Van Fossen, Jenna A. & Wang, Sicheng & Mack, Elizabeth A. & Liberman, Jessica & Cotten, Shelia R., 2023. "Will automated vehicles solve the truck driver shortages? Perspectives from the trucking industry," Technology in Society, Elsevier, vol. 74(C).

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