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Traffic Simulation Analysis on Running Speed in a Connected Vehicles Environment

Author

Listed:
  • Bin Yu

    (School of Transportation, Southeast University, Nanjing 211189, China)

  • Miyi Wu

    (School of Transportation, Southeast University, Nanjing 211189, China)

  • Shuyi Wang

    (School of Transportation, Southeast University, Nanjing 211189, China)

  • Wen Zhou

    (School of Transportation, Southeast University, Nanjing 211189, China)

Abstract

Connected vehicles (CVs) exchange a variety of information instantly with surrounding vehicles and traffic facilities, which could smooth traffic flow significantly. The objective of this paper is to analyze the effect of CVs on running speed. This study compared the delay time, travel time, and running speed in the normal and the connected states, respectively, through VISSIM (a traffic simulation software developed by PTV company in German). The optimization speed model was established to simulate the decision-makings of CVs in MATLAB, considering the parameters of vehicle distance, average speed, and acceleration, etc. After the simulation, the vehicle information including speed, travel time, and delay time under the normal and the connected states were compared and evaluated, and the influence of different CV rates on the results was analyzed. In a two-lane arterial road, running speed in the connected state increase by 4 km/h, and the total travel time and delay time decrease by 5.34% and 16.76%, respectively, compared to those in the normal state. The optimal CV market penetration rate related to running speed and delay time is 60%. This simulation-based study applies user-defined lane change and lateral behavior rules, and takes different CV rates into consideration, which is more reliable and practical to estimate the impact of CV on road traffic characteristics.

Suggested Citation

  • Bin Yu & Miyi Wu & Shuyi Wang & Wen Zhou, 2019. "Traffic Simulation Analysis on Running Speed in a Connected Vehicles Environment," IJERPH, MDPI, vol. 16(22), pages 1-15, November.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:22:p:4373-:d:285202
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    References listed on IDEAS

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    1. Chen, Zhibin & He, Fang & Yin, Yafeng & Du, Yuchuan, 2017. "Optimal design of autonomous vehicle zones in transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 44-61.
    2. Tian, Junfang & Li, Guangyu & Treiber, Martin & Jiang, Rui & Jia, Ning & Ma, Shoufeng, 2016. "Cellular automaton model simulating spatiotemporal patterns, phase transitions and concave growth pattern of oscillations in traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 560-575.
    3. Chen, T. Donna & Kockelman, Kara M. & Hanna, Josiah P., 2016. "Operations of a shared, autonomous, electric vehicle fleet: Implications of vehicle & charging infrastructure decisions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 243-254.
    4. Ye, Lanhang & Yamamoto, Toshiyuki, 2018. "Modeling connected and autonomous vehicles in heterogeneous traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 269-277.
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