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A platoon-based eco-driving control mechanism for low-density traffic flow

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  • Liu, Qingling
  • Xu, Xiaowen

Abstract

Forming traffic into platoons on the road has the potential for mitigation of traffic congestion and improvement in fuel economy, and can be more readily achieved by leveraging emerging connected and automated vehicles. This paper proposes a platoon-based eco-driving control mechanism that forms small-sized platoons and guides them to move on low-density traffic corridors. To facilitate this investigation, a low-density traffic corridor is divided into an initial road segment plus a series of subsequent road segments. To ensure computational efficiency, an approximate model based on the predefined function is employed. Simulation shows that traffic flow of small-sized platoons can bring considerable benefits in fuel consumption compared to that of large-sized platoons. This proposed control mechanism is shown to be significant in fuel economy.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:phsmap:v:637:y:2024:i:c:s0378437124000487
    DOI: 10.1016/j.physa.2024.129540
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    References listed on IDEAS

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    1. Xin, Qi & Fu, Rui & Yuan, Wei & Liu, Qingling & Yu, Shaowei, 2018. "Predictive intelligent driver model for eco-driving using upcoming traffic signal information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 806-823.
    2. 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.
    3. Zhang, Hanyu & Du, Lili, 2023. "Platoon-centered control for eco-driving at signalized intersection built upon hybrid MPC system, online learning and distributed optimization part I: Modeling and solution algorithm design," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 174-198.
    4. Liao, Peng & Tang, Tie-Qiao & Liu, Ronghui & Huang, Hai-Jun, 2021. "An eco-driving strategy for electric vehicle based on the powertrain," Applied Energy, Elsevier, vol. 302(C).
    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. 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.
    7. Zhang, Hanyu & Du, Lili, 2023. "Platoon-centered control for eco-driving at signalized intersection built upon hybrid MPC system, online learning and distributed optimization part II: Theoretical analysis," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 199-216.
    8. Zhang, Jian & Tang, Tie-Qiao & Yan, Yadan & Qu, Xiaobo, 2021. "Eco-driving control for connected and automated electric vehicles at signalized intersections with wireless charging," Applied Energy, Elsevier, vol. 282(PA).
    9. Chatzopoulou, Maria Anna & Simpson, Michael & Sapin, Paul & Markides, Christos N., 2019. "Off-design optimisation of organic Rankine cycle (ORC) engines with piston expanders for medium-scale combined heat and power applications," Applied Energy, Elsevier, vol. 238(C), pages 1211-1236.
    10. Schall, Dominik L. & Mohnen, Alwine, 2017. "Incentivizing energy-efficient behavior at work: An empirical investigation using a natural field experiment on eco-driving," Applied Energy, Elsevier, vol. 185(P2), pages 1757-1768.
    11. Xing, Yingying & Zhou, Huiyu & Han, Xiao & Zhang, Meng & Lu, Jian, 2022. "What influences vulnerable road users’ perceptions of autonomous vehicles? A comparative analysis of the 2017 and 2019 Pittsburgh surveys," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    12. 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.
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