IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2020i1p226-d469708.html
   My bibliography  Save this article

Eco-Driving and Its Impacts on Fuel Efficiency: An Overview of Technologies and Data-Driven Methods

Author

Listed:
  • Panagiotis Fafoutellis

    (School of Civil Engineering, Zografou Campus, National Technical University of Athens, 5 Iroon Polytechniou Str., GR 157 73 Athens, Greece)

  • Eleni G. Mantouka

    (School of Civil Engineering, Zografou Campus, National Technical University of Athens, 5 Iroon Polytechniou Str., GR 157 73 Athens, Greece)

  • Eleni I. Vlahogianni

    (School of Civil Engineering, Zografou Campus, National Technical University of Athens, 5 Iroon Polytechniou Str., GR 157 73 Athens, Greece)

Abstract

Eco-driving is a multidimensional concept that includes driving behavior, route selection and all other choices or behaviors related to the vehicles’ fuel consumption (e.g., the use of quality fuel, the use of air conditioning, driving at peak hours, etc.). The scope of this paper is to present an overview of recent literature referring to eco-driving and developed models for calculating fuel consumption, as well as the most important factors affecting it. Recent literature contains a large number of models that estimate fuel consumption, based on naturalistic driving data, which are collected using smartphones and OBDs. In this work, the existing literature is critically assessed in relation to conceptual, methodological and data related aspects. The analyses result to a set of limitations and challenges that are further discussed in the framework of system wide implementations for deriving policies that increase drivers’ awareness, but also improve system performance.

Suggested Citation

  • Panagiotis Fafoutellis & Eleni G. Mantouka & Eleni I. Vlahogianni, 2020. "Eco-Driving and Its Impacts on Fuel Efficiency: An Overview of Technologies and Data-Driven Methods," Sustainability, MDPI, vol. 13(1), pages 1-17, December.
  • Handle: RePEc:gam:jsusta:v:13:y:2020:i:1:p:226-:d:469708
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/1/226/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/1/226/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chia-Yu Hsu & Sirirat Sae Lim & Chin-Sheng Yang, 2017. "Data mining for enhanced driving effectiveness: an eco-driving behaviour analysis model for better driving decisions," International Journal of Production Research, Taylor & Francis Journals, vol. 55(23), pages 7096-7109, December.
    2. Alam, Md. Saniul & McNabola, Aonghus, 2014. "A critical review and assessment of Eco-Driving policy & technology: Benefits & limitations," Transport Policy, Elsevier, vol. 35(C), pages 42-49.
    3. 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.
    4. Xu, Yanzhi & Li, Hanyan & Liu, Haobing & Rodgers, Michael O. & Guensler, Randall L., 2017. "Eco-driving for transit: An effective strategy to conserve fuel and emissions," Applied Energy, Elsevier, vol. 194(C), pages 784-797.
    5. Sivak, Michael & Schoettle, Brandon, 2012. "Eco-driving: Strategic, tactical, and operational decisions of the driver that influence vehicle fuel economy," Transport Policy, Elsevier, vol. 22(C), pages 96-99.
    6. Huang, Yuhan & Ng, Elvin C.Y. & Zhou, John L. & Surawski, Nic C. & Chan, Edward F.C. & Hong, Guang, 2018. "Eco-driving technology for sustainable road transport: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 596-609.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yiwen Zhou & Fengxiang Guo & Simin Wu & Wenyao He & Xuefei Xiong & Zheng Chen & Dingan Ni, 2022. "Safety and Economic Evaluations of Electric Public Buses Based on Driving Behavior," Sustainability, MDPI, vol. 14(17), pages 1-17, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Yonggang & Chen, Qianyou & Li, Jie & Zhang, Yuanjian & Chen, Zheng & Lei, Zhenzhen, 2023. "Collaborated eco-routing optimization for continuous traffic flow based on energy consumption difference of multiple vehicles," Energy, Elsevier, vol. 274(C).
    2. Yang Wang & Alessandra Boggio-Marzet, 2018. "Evaluation of Eco-Driving Training for Fuel Efficiency and Emissions Reduction According to Road Type," Sustainability, MDPI, vol. 10(11), pages 1-16, October.
    3. Juan Francisco Coloma & Marta García & Gonzalo Fernández & Andrés Monzón, 2021. "Environmental Effects of Eco-Driving on Courier Delivery," Sustainability, MDPI, vol. 13(3), pages 1-21, January.
    4. Huang, Yuhan & Ng, Elvin C.Y. & Zhou, John L. & Surawski, Nic C. & Chan, Edward F.C. & Hong, Guang, 2018. "Eco-driving technology for sustainable road transport: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 596-609.
    5. Jaller, Miguel & Pahwa, Anmol & Zhang, Michael, 2021. "Cargo Routing and Disadvantaged Communities," Institute of Transportation Studies, Working Paper Series qt9qg2318x, Institute of Transportation Studies, UC Davis.
    6. Yuan, Weichang & Frey, H. Christopher, 2020. "Potential for metro rail energy savings and emissions reduction via eco-driving," Applied Energy, Elsevier, vol. 268(C).
    7. Bi, Huibo & Shang, Wen-Long & Chen, Yanyan & Wang, Kezhi & Yu, Qing & Sui, Yi, 2021. "GIS aided sustainable urban road management with a unifying queueing and neural network model," Applied Energy, Elsevier, vol. 291(C).
    8. Wojciech Adamski & Krzysztof Brzozowski & Jacek Nowakowski & Tomasz Praszkiewicz & Tomasz Knefel, 2021. "Excess Fuel Consumption Due to Selection of a Lower Than Optimal Gear—Case Study Based on Data Obtained in Real Traffic Conditions," Energies, MDPI, vol. 14(23), pages 1-15, November.
    9. Alejandro G. Tuero & Laura Pozueco & Roberto García & Gabriel Díaz & Xabiel G. Pañeda & David Melendi & Abel Rionda & David Martínez, 2017. "Economic Impact of the Use of Inertia in an Urban Bus Company," Energies, MDPI, vol. 10(7), pages 1-17, July.
    10. Guan Wang & Jintao Lai & Zhexi Lian & Zhen Zhang, 2023. "An Eco-Driving Strategy Considering Phase-Switch-Based Bus Lane Sharing," Sustainability, MDPI, vol. 15(9), pages 1-20, April.
    11. Vaezipour, Atiyeh & Rakotonirainy, Andry & Haworth, Narelle & Delhomme, Patricia, 2018. "A simulator evaluation of in-vehicle human machine interfaces for eco-safe driving," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 696-713.
    12. Watling, David P. & Connors, Richard D. & Chen, Haibo, 2023. "Fuel-optimal truck path and speed profile in dynamic conditions: An exact algorithm," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1456-1472.
    13. Liu, Qingling & Xu, Xiaowen, 2024. "A platoon-based eco-driving control mechanism for low-density traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    14. Lin, Rui & Wang, Peggy, 2022. "Intention to perform eco-driving and acceptance of eco-driving system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 444-459.
    15. Mohammed Obaid & Arpad Torok & Jairo Ortega, 2021. "A Comprehensive Emissions Model Combining Autonomous Vehicles with Park and Ride and Electric Vehicle Transportation Policies," Sustainability, MDPI, vol. 13(9), pages 1-15, April.
    16. Ma, Fangwu & Yang, Yu & Wang, Jiawei & Liu, Zhenze & Li, Jinhang & Nie, Jiahong & Shen, Yucheng & Wu, Liang, 2019. "Predictive energy-saving optimization based on nonlinear model predictive control for cooperative connected vehicles platoon with V2V communication," Energy, Elsevier, vol. 189(C).
    17. Sanguinetti, Angela & Queen, Ella & Yee, Christopher & Akanesuvan, Kantapon, 2020. "Average impact and important features of onboard eco-driving feedback: A meta-analysis," Institute of Transportation Studies, Working Paper Series qt9hm406d5, Institute of Transportation Studies, UC Davis.
    18. Saeed Vasebi & Yeganeh M. Hayeri, 2021. "Collective Driving to Mitigate Climate Change: Collective-Adaptive Cruise Control," Sustainability, MDPI, vol. 13(16), pages 1-30, August.
    19. Santos, Alberto & Maia, Pedro & Jacob, Rodrigo & Wei, Huang & Callegari, Camila & Oliveira Fiorini, Ana Carolina & Schaeffer, Roberto & Szklo, Alexandre, 2024. "Road conditions and driving patterns on fuel usage: Lessons from an emerging economy," Energy, Elsevier, vol. 295(C).
    20. Li, Menglin & Yin, Long & Yan, Mei & Wu, Jingda & He, Hongwe & Jia, Chunchun, 2024. "Hierarchical intelligent energy-saving control strategy for fuel cell hybrid electric buses based on traffic flow predictions," Energy, Elsevier, vol. 304(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2020:i:1:p:226-:d:469708. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.