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Understanding freight drivers' behavior and the impact on vehicles' fuel consumption and CO2e emissions

Author

Listed:
  • Zhuowu Zhang

    (Cardiff University)

  • Emrah Demir

    (Cardiff University
    Khalifa University Abu Dhabi)

  • Robert Mason

    (Cardiff University)

  • Carla Cairano-Gilfedder

    (BT Applied Research)

Abstract

Despite the significant impact of driver behavior on fuel consumption and carbon dioxide equivalent (CO2e) emissions, this phenomenon is often overlooked in road freight transportation research. We review the relevant literature and seek to provide a deeper understanding of the relationship between freight drivers’ behavior and fuel consumption. This study utilizes a real-life dataset of over 4000 driving records from the freight logistics sector to examine the effects of specific behaviors on fuel consumption. Analyzed behaviors include harsh acceleration/deceleration/cornering, over-revving, excessive revolutions per minute (RPM), and non-adherence to legal speed limits ranging from 20 to 70 miles per hour (mph). Our findings confirm existing literature by demonstrating the significant impact of certain driving characteristics, particularly harsh acceleration/cornering, on fuel consumption. Moreover, our research contributes new insights into the field, notably highlighting the substantial influence of non-adherence to the legal speed limits of 20 and 30 mph on fuel consumption, an aspect not extensively studied in previous research. We subsequently introduce an advanced fuel consumption model that takes into account these identified driver behaviors. This model not only advances academic understanding of fuel consumption determinants in road freight transportation, but also equips practitioners with practical insights to optimize fuel efficiency and reduce environmental impacts.

Suggested Citation

  • Zhuowu Zhang & Emrah Demir & Robert Mason & Carla Cairano-Gilfedder, 2023. "Understanding freight drivers' behavior and the impact on vehicles' fuel consumption and CO2e emissions," Operational Research, Springer, vol. 23(4), pages 1-35, December.
    • Handle: RePEc:spr:operea:v:23:y:2023:i:4:d:10.1007_s12351-023-00798-2
    DOI: 10.1007/s12351-023-00798-2
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    References listed on IDEAS

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    1. Emna Marrekchi & Walid Besbes & Diala Dhouib & Emrah Demir, 2021. "A review of recent advances in the operations research literature on the green routing problem and its variants," Annals of Operations Research, Springer, vol. 304(1), pages 529-574, September.
    2. W Maden & R Eglese & D Black, 2010. "Vehicle routing and scheduling with time-varying data: A case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 515-522, March.
    3. José I. Huertas & Michael Giraldo & Luis F. Quirama & Jenny Díaz, 2018. "Driving Cycles Based on Fuel Consumption," Energies, MDPI, vol. 11(11), pages 1-13, November.
    4. Franceschetti, Anna & Honhon, Dorothée & Van Woensel, Tom & Bektaş, Tolga & Laporte, Gilbert, 2013. "The time-dependent pollution-routing problem," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 265-293.
    5. W Dullaert & G K Janssens & K Sörensen & B Vernimmen, 2002. "New heuristics for the Fleet Size and Mix Vehicle Routing Problem with Time Windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(11), pages 1232-1238, November.
    6. Erdoğan, Sevgi & Miller-Hooks, Elise, 2012. "A Green Vehicle Routing Problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 100-114.
    7. Figliozzi, Miguel Andres, 2009. "Planning approximations to the average length of vehicle routing problems with time window constraints," Transportation Research Part B: Methodological, Elsevier, vol. 43(4), pages 438-447, May.
    8. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2014. "A review of recent research on green road freight transportation," European Journal of Operational Research, Elsevier, vol. 237(3), pages 775-793.
    9. Abdullahi, Hassana & Reyes-Rubiano, Lorena & Ouelhadj, Djamila & Faulin, Javier & Juan, Angel A., 2021. "Modelling and multi-criteria analysis of the sustainability dimensions for the green vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 292(1), pages 143-154.
    10. Yushan Yang & Nuoya Gong & Keying Xie & Qingfei Liu, 2022. "Predicting Gasoline Vehicle Fuel Consumption in Energy and Environmental Impact Based on Machine Learning and Multidimensional Big Data," Energies, MDPI, vol. 15(5), pages 1-17, February.
    11. Turkensteen, Marcel, 2017. "The accuracy of carbon emission and fuel consumption computations in green vehicle routing," European Journal of Operational Research, Elsevier, vol. 262(2), pages 647-659.
    12. Zhang, Ruiyou & Yun, Won Young & Moon, Ilkyeong, 2009. "A reactive tabu search algorithm for the multi-depot container truck transportation problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(6), pages 904-914, November.
    13. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2012. "An adaptive large neighborhood search heuristic for the Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 223(2), pages 346-359.
    14. Fontaras, Georgios & Samaras, Zissis, 2010. "On the way to 130 g CO2/km--Estimating the future characteristics of the average European passenger car," Energy Policy, Elsevier, vol. 38(4), pages 1826-1833, April.
    15. Aras, Necati & Aksen, Deniz & Gönül Tanugur, Ayse, 2008. "Locating collection centers for incentive-dependent returns under a pick-up policy with capacitated vehicles," European Journal of Operational Research, Elsevier, vol. 191(3), pages 1223-1240, December.
    16. Dale L. Belman & Kristen A. Monaco, 2001. "The Effects of Deregulation, De-Unionization, Technology, and Human Capital on the Work and Work Lives of Truck Drivers," ILR Review, Cornell University, ILR School, vol. 54(2A), pages 502-524, March.
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