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An Exploration of Factors Affecting Drivers’ Daily Fuel Consumption Efficiencies Considering Multi-Level Random Effects

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  • Dawei Li

    (Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast University, Nanjing 210096, China
    Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic SiPaiLou #2, Xuanwu District, Nanjing 210096, China)

  • Cheng Li

    (China Academy of Transportation Sciences, No.240, Huixinli, Chaoyang District, Beijing 100029, China)

  • Tomio Miwa

    (EcoTopia Science Institute & Green Mobility Collaborative Research Center, Nagoya University, Nagoya 4648603, Japan)

  • Takayuki Morikawa

    (Graduate School of Environmental Studies & Green Mobility Collaborative Research Center, Nagoya University, Nagoya 4648603, Japan)

Abstract

This paper investigates the factors affecting drivers’ vehicle fuel consumption efficiency, which was defined as the daily average fuel consumption for a unit of driving mileage. Based on the long-term Controller Area Network (CAN) data collected from private cars during 10 months in Toyota City, Japan, we explored the relationships between drivers’ fuel consumption efficiencies, and factors including drivers’ characteristics, car attributes, date-specific environmental attributes, and travel behavior. Furthermore, a multi-level model was applied to explicitly incorporate the effects of individual-specific, date-specific, and observation-specific unobserved factors. According to the estimation results, it was found that, on working days, model fit was significantly enhanced by incorporating all three error terms. Several findings regarding the relationships between observed factors and drivers’ fuel consumption efficiencies were also obtained.

Suggested Citation

  • Dawei Li & Cheng Li & Tomio Miwa & Takayuki Morikawa, 2019. "An Exploration of Factors Affecting Drivers’ Daily Fuel Consumption Efficiencies Considering Multi-Level Random Effects," Sustainability, MDPI, vol. 11(2), pages 1-13, January.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:2:p:393-:d:197516
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    References listed on IDEAS

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    Cited by:

    1. Jian Gong & Junzhu Shang & Lei Li & Changjian Zhang & Jie He & Jinhang Ma, 2021. "A Comparative Study on Fuel Consumption Prediction Methods of Heavy-Duty Diesel Trucks Considering 21 Influencing Factors," Energies, MDPI, vol. 14(23), pages 1-18, December.
    2. Naif Alsaadi, 2021. "Comparative Analysis and Statistical Optimization of Fuel Economy for Sustainable Vehicle Routings," Sustainability, MDPI, vol. 14(1), pages 1-17, December.
    3. Kai Liu & Dong Liu & Cheng Li & Toshiyuki Yamamoto, 2019. "Eco-Speed Guidance for the Mixed Traffic of Electric Vehicles and Internal Combustion Engine Vehicles at an Isolated Signalized Intersection," Sustainability, MDPI, vol. 11(20), pages 1-13, October.
    4. Sai Chand & Emily Moylan & S. Travis Waller & Vinayak Dixit, 2020. "Analysis of Vehicle Breakdown Frequency: A Case Study of New South Wales, Australia," Sustainability, MDPI, vol. 12(19), pages 1-14, October.

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