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Impact on Congestion and Fuel Consumption of a Cooperative Adaptive Cruise Control System with Lane-Level Position Estimation

Author

Listed:
  • Edgar Talavera

    (Escuela Técnica Superior de Ingeniería de Sistemas Informáticos (ETSISI), Universidad Politécnica de Madrid (UPM), 28031 Madrid, Spain)

  • Alberto Díaz-Álvarez

    (University Institute for Automobile Research (INSIA), Universidad Politécnica de Madrid (UPM), 28031 Madrid, Spain)

  • Felipe Jiménez

    (University Institute for Automobile Research (INSIA), Universidad Politécnica de Madrid (UPM), 28031 Madrid, Spain)

  • José E. Naranjo

    (University Institute for Automobile Research (INSIA), Universidad Politécnica de Madrid (UPM), 28031 Madrid, Spain)

Abstract

In recent years, vehicular communications systems have evolved and allowed for the improvement of adaptive cruise control (ACC) systems to make them cooperative (cooperative adaptive cruise control, CACC). Conventional ACC systems use sensors on the ego-vehicle, such as radar or computer vision, to generate their behavioral decisions. However, by having vehicle-to-X (V2X) onboard communications, the need to incorporate perception in the vehicle is drastically reduced. Thus, in this paper a CACC solution is proposed that only uses communications to make its decisions with the help of previous road mapping. At the same time, a method to develop these maps is presented, combining the information of a computer vision system to correct the positions obtained from the navigation system. In addition, the cut-in and cut-out maneuvers for a CACC platoon are taken into account, showing the tests of these situations in real environments with instrumented vehicles. To show the potential of the system in a larger-scale implementation, simulations of the behavior are provided under dense traffic conditions where the positive impact on the reduction of traffic congestion and fuel consumption is appreciated.

Suggested Citation

  • Edgar Talavera & Alberto Díaz-Álvarez & Felipe Jiménez & José E. Naranjo, 2018. "Impact on Congestion and Fuel Consumption of a Cooperative Adaptive Cruise Control System with Lane-Level Position Estimation," Energies, MDPI, vol. 11(1), pages 1-17, January.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:1:p:194-:d:126798
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    Citations

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    Cited by:

    1. Fabio Cococcetta & Roberto Finesso & Gilles Hardy & Omar Marello & Ezio Spessa, 2019. "Implementation and Assessment of a Model-Based Controller of Torque and Nitrogen Oxide Emissions in an 11 L Heavy-Duty Diesel Engine," Energies, MDPI, vol. 12(24), pages 1-19, December.
    2. Li, Haijian & Zhang, Junjie & Sun, Xiaoliang & Niu, Jun & Zhao, Xiaohua, 2022. "A survey of vehicle group behaviors simulation under a connected vehicle environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    3. 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).
    4. Changyin Dong & Hao Wang & Quan Chen & Daiheng Ni & Ye Li, 2019. "Simulation-Based Assessment of Multilane Separate Freeways at Toll Station Area: A Case Study from Huludao Toll Station on Shenshan Freeway," Sustainability, MDPI, vol. 11(11), pages 1-22, May.
    5. Andrzej Łebkowski, 2018. "Reduction of Fuel Consumption and Pollution Emissions in Inland Water Transport by Application of Hybrid Powertrain," Energies, MDPI, vol. 11(8), pages 1-16, July.
    6. Stefano d’Ambrosio & Roberto Finesso & Gilles Hardy & Andrea Manelli & Alessandro Mancarella & Omar Marello & Antonio Mittica, 2021. "Model-Based Control of Torque and Nitrogen Oxide Emissions in a Euro VI 3.0 L Diesel Engine through Rapid Prototyping," Energies, MDPI, vol. 14(4), pages 1-25, February.

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