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An Improved Cellular Automaton Traffic Model Based on STCA Model Considering Variable Direction Lanes in I-VICS

Author

Listed:
  • Ziwen Song

    (Jiangsu key Laboratory of Traffic and Transportation Security, Huaiyin Institute of Technology, Huaian 223003, China
    School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

  • Feng Sun

    (Jiangsu key Laboratory of Traffic and Transportation Security, Huaiyin Institute of Technology, Huaian 223003, China
    School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

  • Rongji Zhang

    (School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

  • Yingcui Du

    (School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

  • Guiliang Zhou

    (Jiangsu key Laboratory of Traffic and Transportation Security, Huaiyin Institute of Technology, Huaian 223003, China)

Abstract

In this paper, we propose an improved cellular automaton model for the traffic operation characteristics of variable direction lanes in an Intelligent Vehicle Infrastructure Cooperation System (I-VICS). According to the proposed flow of variable oriented lane operation in the I-VICS environment, the idea for the improved model has been determined. According to an analysis of different signal states, an improved STCA model is proposed, in combination with the speed induction method of I-VICS and the variable direction lane switching strategy. In the assumed regular simulation environment, the STCA and STCA-V models are simulated under different vehicular densities. The results indicated that traffic parameters such as traffic flow and average speed of the variable direction lanes in the I-VICS environment are better than those in the conventional environment according to the operating rules of the proposed model. Moreover, lane utilization increased for the same density.

Suggested Citation

  • Ziwen Song & Feng Sun & Rongji Zhang & Yingcui Du & Guiliang Zhou, 2021. "An Improved Cellular Automaton Traffic Model Based on STCA Model Considering Variable Direction Lanes in I-VICS," Sustainability, MDPI, vol. 13(24), pages 1-17, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:24:p:13626-:d:698842
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    References listed on IDEAS

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    1. Kerner, Boris S., 2016. "Failure of classical traffic flow theories: Stochastic highway capacity and automatic driving," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 700-747.
    2. Li, Xin-Gang & Jia, Bin & Gao, Zi-You & Jiang, Rui, 2006. "A realistic two-lane cellular automata traffic model considering aggressive lane-changing behavior of fast vehicle," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 479-486.
    3. Jia, Bin & Jiang, Rui & Wu, Qing-Song & Hu, Mao-bin, 2005. "Honk effect in the two-lane cellular automaton model for traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 348(C), pages 544-552.
    4. Lv, Wei & Song, Wei-guo & Liu, Xiao-dong & Ma, Jian, 2013. "A microscopic lane changing process model for multilane traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1142-1152.
    5. Chowdhury, Debashish & Wolf, Dietrich E. & Schreckenberg, Michael, 1997. "Particle hopping models for two-lane traffic with two kinds of vehicles: Effects of lane-changing rules," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 235(3), pages 417-439.
    6. Ye, Lanhang & Yamamoto, Toshiyuki, 2019. "Evaluating the impact of connected and autonomous vehicles on traffic safety," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    7. Chen, Xinqiang & Chen, Huixing & Yang, Yongsheng & Wu, Huafeng & Zhang, Wenhui & Zhao, Jiansen & Xiong, Yong, 2021. "Traffic flow prediction by an ensemble framework with data denoising and deep learning model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    8. Pottmeier, A. & Barlovic, R. & Knospe, W. & Schadschneider, A. & Schreckenberg, M., 2002. "Localized defects in a cellular automaton model for traffic flow with phase separation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 308(1), pages 471-482.
    9. 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.
    10. Cremer, M. & Ludwig, J., 1986. "A fast simulation model for traffic flow on the basis of boolean operations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 28(4), pages 297-303.
    11. Knorr, Florian & Schreckenberg, Michael, 2012. "Influence of inter-vehicle communication on peak hour traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(6), pages 2225-2231.
    12. Z.-P. Li & Y.-C. Liu, 2006. "Analysis of stability and density waves of traffic flow model in an ITS environment," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 53(3), pages 367-374, October.
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