IDEAS home Printed from https://ideas.repec.org/a/hin/complx/1956521.html
   My bibliography  Save this article

Reversible Transitions in a Cellular Automata-Based Traffic Model with Driver Memory

Author

Listed:
  • Tomoko Sakiyama
  • Ikuo Arizono

Abstract

Here, we develop a new cellular automata-based traffic model. In this model, individual vehicles cannot estimate global traffic flows but can only detect the vehicle ahead. Each vehicle occasionally adjusts its velocity based on the distance to the vehicle in front. Our model generates reversible phase transitions in the vehicle flux over a wide range of vehicle densities, and the traffic system undergoes scale-free evolution with respect to the flux. We thus believe that our model reveals the relationship between the macro-level flows and micro-level mechanisms of multi-agent systems for handling traffic congestion, and illustrates how drivers’ decisions impact free and congested flows.

Suggested Citation

  • 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.
    • Handle: RePEc:hin:complx:1956521
    DOI: 10.1155/2019/1956521
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2019/1956521.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2019/1956521.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2019/1956521?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Neto, J.P.L. & Lyra, M.L. & da Silva, C.R., 2011. "Phase coexistence induced by a defensive reaction in a cellular automaton traffic flow model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3558-3565.
    3. 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.
    4. 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.
    5. Treiber, Martin & Kesting, Arne & Helbing, Dirk, 2010. "Three-phase traffic theory and two-phase models with a fundamental diagram in the light of empirical stylized facts," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 983-1000, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Treiber, Martin & Kesting, Arne, 2018. "The Intelligent Driver Model with stochasticity – New insights into traffic flow oscillations," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 613-623.
    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. 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.
    4. Yuan, Zijian & Wang, Tao & Zhang, Jing & Li, Shubin, 2022. "Influences of dynamic safe headway on car-following behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
    5. 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.
    6. Li, Yongfu & Zhao, Hang & Zhang, Li & Zhang, Chao, 2018. "An extended car-following model incorporating the effects of lateral gap and gradient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 177-189.
    7. Wang, Zhengli & Qi, Xin & Jiang, Hai, 2018. "Estimating the spatiotemporal impact of traffic incidents: An integer programming approach consistent with the propagation of shockwaves," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 356-369.
    8. 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.
    9. 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.
    10. Zhang, Jing & Xu, Keyu & Li, Shubin & Wang, Tao, 2020. "A new two-lane lattice hydrodynamic model with the introduction of driver’s predictive effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    11. Ye, Lanhang & Yamamoto, Toshiyuki, 2018. "Impact of dedicated lanes for connected and autonomous vehicle on traffic flow throughput," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 588-597.
    12. Wang, Zhengli & Jiang, Hai, 2019. "Simultaneous correction of the time and location bias associated with a reported crash by exploiting the spatiotemporal evolution of travel speed," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 199-223.
    13. Zhang, Jing & Wang, Bo & Li, Shubin & Sun, Tao & Wang, Tao, 2020. "Modeling and application analysis of car-following model with predictive headway variation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    14. Wang, Tao & Li, Guangyao & Zhang, Jing & Li, Shubin & Sun, Tao, 2019. "The effect of Headway Variation Tendency on traffic flow: Modeling and stabilization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 566-575.
    15. 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.
    16. Tian, Junfang & Zhang, H.M. & Treiber, Martin & Jiang, Rui & Gao, Zi-You & Jia, Bin, 2019. "On the role of speed adaptation and spacing indifference in traffic instability: Evidence from car-following experiments and its stochastic model," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 334-350.
    17. Fu, Ding-Jun & Li, Qi-Lang & Jiang, Rui & Wang, Bing-Hong, 2020. "A simple cellular automaton model with dual cruise-control limit in the framework of Kerner’s three-phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    18. Zhang, Jing & Xu, Keyu & Li, Guangyao & Li, Shubin & Wang, Tao, 2021. "Dynamics of traffic flow affected by the future motion of multiple preceding vehicles under vehicle-connected environment: Modeling and stabilization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    19. He, Zhengbing & Zheng, Liang & Guan, Wei, 2015. "A simple nonparametric car-following model driven by field data," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 185-201.
    20. Treiber, Martin & Kesting, Arne, 2011. "Evidence of convective instability in congested traffic flow: A systematic empirical and theoretical investigation," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1362-1377.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:complx:1956521. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.