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Discontinuous transition from free flow to synchronized flow induced by short-range interaction between vehicles in a three-phase traffic flow model

Author

Listed:
  • Gao, Kun
  • Jiang, Rui
  • Wang, Bing-Hong
  • Wu, Qing-Song

Abstract

In this paper, we incorporate a limitation on the interaction range between neighboring vehicles into the cellular automaton model proposed by Gao and Jiang et al. [K. Gao, R. Jiang, S. X. Hu, B. H. Wang and Q. S. Wu, Phys. Rev. E 76 (2007) 026105], which was established within the framework of Kerner’s three-phase traffic theory and has been shown to be able to reproduce the three-phase traffic flow. This modification eliminates an unrealistic phenomenon found in the previous model, where the velocity-adaptation effect between neighboring vehicles can exist even if those vehicles are infinitely far away from each other. Therefore, in the improved model, we regulate that such interactions can only occur within a finite distance. For simplicity, we suppose a constant value to describe this distance in this paper. As a result, when compared to the previous model, the improved model mainly simulates the following results which are believed to be an improvement. (1) The improved model successfully reproduces the expected discontinuous transition from free flow to synchronized flow and the related “moving synchronized flow pattern”, which are both absent in the original model but have been observed in real traffic. (2) The improved model simulates the correlation functions, time headway distributions and optimal velocity functions which are all more consistent with the empirical data than the previous model and most of the other models published before. (3) Together with the previous two models considering the velocity-difference effect, this model finally accomplishes a significative process of developing traffic flow models from the traditional “fundamental diagram approach” to the three-phase traffic theory. This process should be helpful for us to understand the traffic dynamics and mechanics further and deeper.

Suggested Citation

  • Gao, Kun & Jiang, Rui & Wang, Bing-Hong & Wu, Qing-Song, 2009. "Discontinuous transition from free flow to synchronized flow induced by short-range interaction between vehicles in a three-phase traffic flow model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(15), pages 3233-3243.
    • Handle: RePEc:eee:phsmap:v:388:y:2009:i:15:p:3233-3243
    DOI: 10.1016/j.physa.2009.04.033
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    References listed on IDEAS

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    1. Jiang, Rui & Wu, Qing-Song & Zhu, Zuo-Jin, 2002. "A new continuum model for traffic flow and numerical tests," Transportation Research Part B: Methodological, Elsevier, vol. 36(5), pages 405-419, June.
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    Citations

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    Cited by:

    1. Davis, L.C., 2012. "Mitigation of congestion at a traffic bottleneck with diversion and lane restrictions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1679-1691.
    2. Tomoko Sakiyama & Ikuo Arizono, 2019. "Reversible Transitions in a Cellular Automata-Based Traffic Model with Driver Memory," Complexity, Hindawi, vol. 2019, pages 1-8, December.
    3. Tang, Jinjun & Wang, Yinhai & Wang, Hua & Zhang, Shen & Liu, Fang, 2014. "Dynamic analysis of traffic time series at different temporal scales: A complex networks approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 303-315.
    4. Tianjun Feng & Keyi Liu & Chunyan Liang, 2023. "An Improved Cellular Automata Traffic Flow Model Considering Driving Styles," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    5. Yan, Ying & Zhang, Shen & Tang, Jinjun & Wang, Xiaofei, 2017. "Understanding characteristics in multivariate traffic flow time series from complex network structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 477(C), pages 149-160.
    6. Kokubo, Satoshi & Tanimoto, Jun & Hagishima, Aya, 2011. "A new Cellular Automata Model including a decelerating damping effect to reproduce Kerner’s three-phase theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 561-568.
    7. Hu, Xiaojian & Wang, Wei & Yang, Haifei, 2012. "Mixed traffic flow model considering illegal lane-changing behavior: Simulations in the framework of Kerner’s three-phase theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(21), pages 5102-5111.
    8. Ding, Zhongjun & Chen, Bokui & Zhang, Lele & Jiang, Rui & Wu, Yao & Ding, Jianxun, 2019. "Segment travel time route guidance strategy in advanced traveler information systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    9. Rehborn, Hubert & Klenov, Sergey L. & Palmer, Jochen, 2011. "An empirical study of common traffic congestion features based on traffic data measured in the USA, the UK, and Germany," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4466-4485.
    10. 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.
    11. Li, Xin & Li, Xingang & Xiao, Yao & Jia, Bin, 2016. "Modeling mechanical restriction differences between car and heavy truck in two-lane cellular automata traffic flow model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 49-62.
    12. Tian, Junfang & Treiber, Martin & Ma, Shoufeng & Jia, Bin & Zhang, Wenyi, 2015. "Microscopic driving theory with oscillatory congested states: Model and empirical verification," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 138-157.

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