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Mobile Application Based Heavy Vehicle Fatigue Compliance in Australian Operations

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Databases Theory and Applications (ADC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10837))

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Abstract

The Australian National Heavy Vehicle Regulator (NHVR) defines the rules for fatigue management in heavy haulage trucking operations. The rules place restrictions on total work and minimum rest hours, and are aimed at regulating the potential for fatigue risk amongst drivers. This paper presents a performance-based fatigue management system based on driver fatigue data stored in simple mobile databases and deployed via Android smart phones. The system funded by WorkSafe Tasmania and entitled, Logistics Fatigue Manager (LFM), was evaluated with a cohort of heavy haulage drivers in Australian forestry. The correlation between driver fatigue estimates and actual sleep hours (recorded using FitBits) is confirmed, and is also supported through driver interviews. The benefit is that management of fatigue risk could be more tailored to individual drivers opening up efficiency gains across supply chains.

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References

  1. NHVR: Basic Fatigue Management (2016). https://www.nhvr.gov.au/safety-accreditation-compliance/fatigue-management/work-and-rest-requirements/standard-hours

  2. Department of Infrastructure and Regional Development-Australian Government: Freightline 1—Australia freight transport overview (2014)

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  3. NHVR: Electronic Work Diary (2016). https://www.nhvr.gov.au/safety-accreditation-compliance/fatigue-management/electronic-work-diaries-ewds

  4. NHVR: Chain of Responsibility (2015). https://www.nhvr.gov.au/safety-accreditation-compliance/chain-of-responsibility

  5. Goel, A., et al.: Truck driver scheduling in Australia. Comput. Oper. Res. 39, 1122–1132 (2012)

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Correspondence to Luke Mirowski .

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Mirowski, L., Scanlan, J. (2018). Mobile Application Based Heavy Vehicle Fatigue Compliance in Australian Operations. In: Wang, J., Cong, G., Chen, J., Qi, J. (eds) Databases Theory and Applications. ADC 2018. Lecture Notes in Computer Science(), vol 10837. Springer, Cham. https://doi.org/10.1007/978-3-319-92013-9_24

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  • DOI: https://doi.org/10.1007/978-3-319-92013-9_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92012-2

  • Online ISBN: 978-3-319-92013-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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