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A new car-following model for autonomous vehicles flow with mean expected velocity field

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  • Wen-Xing, Zhu
  • Li-Dong, Zhang

Abstract

Due to the development of the modern scientific technology, autonomous vehicles may realize to connect with each other and share the information collected from each vehicle. An improved forward considering car-following model was proposed with mean expected velocity field to describe the autonomous vehicles flow behavior. The new model has three key parameters: adjustable sensitivity, strength factor and mean expected velocity field size. Two lemmas and one theorem were proven as criteria for judging the stability of homogeneousautonomous vehicles flow. Theoretical results show that the greater parameters means larger stability regions. A series of numerical simulations were carried out to check the stability and fundamental diagram of autonomous flow. From the numerical simulation results, the profiles, hysteresis loop and density waves of the autonomous vehicles flow were exhibited. The results show that with increased sensitivity, strength factor or field size the traffic jam was suppressed effectively which are well in accordance with the theoretical results. Moreover, the fundamental diagrams corresponding to three parameters respectively were obtained. It demonstrates that these parameters play almost the same role on traffic flux: i.e. before the critical density the bigger parameter is, the greater flux is and after the critical density, the opposite tendency is. In general, the three parameters have a great influence on the stability and jam state of the autonomous vehicles flow.

Suggested Citation

  • Wen-Xing, Zhu & Li-Dong, Zhang, 2018. "A new car-following model for autonomous vehicles flow with mean expected velocity field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 2154-2165.
  • Handle: RePEc:eee:phsmap:v:492:y:2018:i:c:p:2154-2165
    DOI: 10.1016/j.physa.2017.11.133
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    Citations

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    Cited by:

    1. Gu, Yewen & Goez, Julio C. & Mario, Guajardo & Wallace, Stein W., 2019. "Autonomous vessels: State of the art and potential opportunities in logistics," Discussion Papers 2019/6, Norwegian School of Economics, Department of Business and Management Science.
    2. Wang, Xiaoning & Liu, Minzhuang & Ci, Yusheng & Wu, Lina, 2022. "Effect of front two adjacent vehicles’ velocity information on car-following model construction and stability analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    3. Umberto Crisalli & Andrea Gemma & Marco Petrelli, 2023. "Investigating the Effects of Automated Vehicles on Large Urban Road Networks: Some Evidence from Rome," Sustainability, MDPI, vol. 15(13), pages 1-10, July.
    4. Junyan Han & Jinglei Zhang & Xiaoyuan Wang & Yaqi Liu & Quanzheng Wang & Fusheng Zhong, 2020. "An Extended Car-Following Model Considering Generalized Preceding Vehicles in V2X Environment," Future Internet, MDPI, vol. 12(12), pages 1-15, November.
    5. Ma, Ke & Wang, Hao & Ruan, Tiancheng, 2021. "Analysis of road capacity and pollutant emissions: Impacts of Connected and automated vehicle platoons on traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    6. Lin Li & Serdar Coskun & Jiaze Wang & Youming Fan & Fengqi Zhang & Reza Langari, 2021. "Velocity Prediction Based on Vehicle Lateral Risk Assessment and Traffic Flow: A Brief Review and Application Examples," Energies, MDPI, vol. 14(12), pages 1-30, June.
    7. Cui, Ziyu & Wang, Xiaoning & Ci, Yusheng & Yang, Changyun & Yao, Jia, 2023. "Modeling and analysis of car-following models incorporating multiple lead vehicles and acceleration information in heterogeneous traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    8. Xiaoyuan Wang & Junyan Han & Chenglin Bai & Huili Shi & Jinglei Zhang & Gang Wang, 2021. "Research on the Impacts of Generalized Preceding Vehicle Information on Traffic Flow in V2X Environment," Future Internet, MDPI, vol. 13(4), pages 1-17, March.

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