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Safe and Ecological Speed Control for Heavy-Duty Vehicles on Long–Steep Downhill and Sharp-Curved Roads

Author

Listed:
  • Huifu Jiang

    (Research Institute of Highway, Ministry of Transport, Beijing 100088, China)

  • Wei Zhou

    (Research Institute of Highway, Ministry of Transport, Beijing 100088, China)

  • Chang Liu

    (Research Institute of Highway, Ministry of Transport, Beijing 100088, China)

  • Guosheng Zhang

    (Research Institute of Highway, Ministry of Transport, Beijing 100088, China)

  • Meng Hu

    (Research Institute of Highway, Ministry of Transport, Beijing 100088, China)

Abstract

To contribute to the development of sustainable transport that is safe, eco-friendly, and efficient, this research proposed a safe and ecological speed control system for heavy-duty vehicles on long–steep downhill and sharp-curved roads under a partially connected vehicles environment consisting of connected heavy-duty vehicles (CHDVs) and conventional human-driven vehicles. This system prioritizes braking and lateral motion safety before improving fuel efficiency and ensuring traffic mobility at optimal status, and optimizes the speed trajectories of CHDVs to control the entire traffic. Speed optimization is modelled as an optimal control problem and solved by the iterative Pontryagin’s maximum principle algorithm. The simulation-based evaluation shows that the proposed system effectively reduces the peak temperature of the brake drums, the lateral slip angle of the vehicle wheels, and the lateral load transfer rate of the vehicle body; all these measurements of effectiveness are limited to safe ranges. A detailed investigation reveals that the proposed system reduces fuel consumption by up to 15.49% and inhibits the adverse effects on throughput. All benefits increase with the market penetration rate (MPR) of CHDVs and the traffic congestion level and reach significant levels under low MPRs of CHDVs. This indicates that the proposed system has good robustness for the impedance from conventional vehicles and could be implemented in the near future.

Suggested Citation

  • Huifu Jiang & Wei Zhou & Chang Liu & Guosheng Zhang & Meng Hu, 2020. "Safe and Ecological Speed Control for Heavy-Duty Vehicles on Long–Steep Downhill and Sharp-Curved Roads," Sustainability, MDPI, vol. 12(17), pages 1-35, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:17:p:6813-:d:402495
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    References listed on IDEAS

    as
    1. Huifu Jiang & Jia Hu & Byungkyu Brian Park & Meng Wang & Wei Zhou, 2019. "An Extensive Investigation of an Eco-Approach Controller under a Partially Connected and Automated Vehicle Environment," Sustainability, MDPI, vol. 11(22), pages 1-24, November.
    2. Ma, Jiaqi & Li, Xiaopeng & Zhou, Fang & Hu, Jia & Park, B. Brian, 2017. "Parsimonious shooting heuristic for trajectory design of connected automated traffic part II: Computational issues and optimization," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 421-441.
    3. Huifu Jiang & Shi An & Jian Wang & Jianxun Cui, 2018. "Eco-Approach and Departure System for Left-Turn Vehicles at a Fixed-Time Signalized Intersection," Sustainability, MDPI, vol. 10(1), pages 1-20, January.
    4. Zhou, Fang & Li, Xiaopeng & Ma, Jiaqi, 2017. "Parsimonious shooting heuristic for trajectory design of connected automated traffic part I: Theoretical analysis with generalized time geography," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 394-420.
    5. Akcelik, Rahmi, 1989. "Efficiency and drag in the power-based model of fuel consumption," Transportation Research Part B: Methodological, Elsevier, vol. 23(5), pages 376-385, October.
    6. Ali Keyvanfar & Arezou Shafaghat & Nasiru Zakari Muhammad & M. Salim Ferwati, 2018. "Driving Behaviour and Sustainable Mobility—Policies and Approaches Revisited," Sustainability, MDPI, vol. 10(4), pages 1-27, April.
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    1. Maria Torres-Falcon & Omar Rodríguez-Abreo & Francisco Antonio Castillo-Velásquez & Alejandro Flores-Rangel & Juvenal Rodríguez-Reséndiz & José Manuel Álvarez-Alvarado, 2021. "Novel Mathematical Method to Obtain the Optimum Speed and Fuel Reduction in Heavy Diesel Trucks," Energies, MDPI, vol. 14(23), pages 1-17, December.

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