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Value of eco-friendly route choice for heavy-duty trucks

Author

Listed:
  • Scora, George
  • Boriboonsomsin, Kanok
  • Barth, Matthew

Abstract

Heavy-duty trucks are a critical component of any goods movement system; however, they consume a large amount of fuel and emit significant pollutant and greenhouse gas emissions. An important consideration for reducing fuel consumption and improving trucking operations is efficient vehicle routing. Many existing fleet management and routing systems are based on minimizing distance traveled which does not necessarily minimize fuel consumption or emissions, particularly when under traffic congestion and in areas with hilly terrain.

Suggested Citation

  • Scora, George & Boriboonsomsin, Kanok & Barth, Matthew, 2015. "Value of eco-friendly route choice for heavy-duty trucks," Research in Transportation Economics, Elsevier, vol. 52(C), pages 3-14.
    • Handle: RePEc:eee:retrec:v:52:y:2015:i:c:p:3-14
    DOI: 10.1016/j.retrec.2015.10.002
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    Citations

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    Cited by:

    1. 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.
    2. Jules Muvuna & Tuleen Boutaleb & Slobodan B. Mickovski & Keith Baker & Ghoreyshi Seyed Mohammad & Mario Cools & Wissal Selmi, 2020. "Information Integration in a Smart City System—A Case Study on Air Pollution Removal by Green Infrastructure through a Vehicle Smart Routing System," Sustainability, MDPI, vol. 12(12), pages 1-14, June.
    3. Jiang, Ying & Zhang, Junyi, 2019. "Interaction between company Manager's and Driver's decisions on expressway routes for truck transport," Transport Policy, Elsevier, vol. 76(C), pages 1-12.
    4. Guiliano, Genevieve, 2016. "Freight Efficiency Strategies: Information Technology," Institute of Transportation Studies, Working Paper Series qt8ng5j9wj, Institute of Transportation Studies, UC Davis.
    5. Boriboonsomsin, Kanok & Vu, Alexander & Barth, Matthew, 2016. "Environmentally Friendly Driving Feedback Systems Research and Development for Heavy Duty Trucks," Institute of Transportation Studies, Working Paper Series qt9mk9r1hm, Institute of Transportation Studies, UC Davis.
    6. 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.
    7. Poulad Moradi & Joachim Arts & Josu'e Vel'azquez-Mart'inez, 2023. "Load Asymptotics and Dynamic Speed Optimization for the Greenest Path Problem: A Comprehensive Analysis," Papers 2306.01687, arXiv.org.
    8. 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).
    9. Hugo Ferreira & Carlos Manuel Rodrigues & Carlos Pinho, 2019. "Impact of Road Geometry on Vehicle Energy Consumption and CO 2 Emissions: An Energy-Efficiency Rating Methodology," Energies, MDPI, vol. 13(1), pages 1-27, December.

    More about this item

    Keywords

    Heavy-duty truck; Environmentally friendly; Eco-friendly; Routing; Navigation; Vehicle emission modeling; Fuel optimization;
    All these keywords.

    JEL classification:

    • L90 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - General
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R49 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Other

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