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Failure of classical traffic flow theories: Stochastic highway capacity and automatic driving

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  • Kerner, Boris S.

Abstract

In a mini-review Kerner (2013) it has been shown that classical traffic flow theories and models failed to explain empirical traffic breakdown — a phase transition from metastable free flow to synchronized flow at highway bottlenecks. The main objective of this mini-review is to study the consequence of this failure of classical traffic-flow theories for an analysis of empirical stochastic highway capacity as well as for the effect of automatic driving vehicles and cooperative driving on traffic flow. To reach this goal, we show a deep connection between the understanding of empirical stochastic highway capacity and a reliable analysis of automatic driving vehicles in traffic flow. With the use of simulations in the framework of three-phase traffic theory, a probabilistic analysis of the effect of automatic driving vehicles on a mixture traffic flow consisting of a random distribution of automatic driving and manual driving vehicles has been made. We have found that the parameters of automatic driving vehicles can either decrease or increase the probability of the breakdown. The increase in the probability of traffic breakdown, i.e., the deterioration of the performance of the traffic system can occur already at a small percentage (about 5%) of automatic driving vehicles. The increase in the probability of traffic breakdown through automatic driving vehicles can be realized, even if any platoon of automatic driving vehicles satisfies condition for string stability.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:450:y:2016:i:c:p:700-747
    DOI: 10.1016/j.physa.2016.01.034
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    References listed on IDEAS

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    1. Daganzo, Carlos & Laval, Jorge A., 2003. "On the Numerical Treatment of Moving Bottlenecks," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt69r4t5pp, Institute of Transportation Studies, UC Berkeley.
    2. Lily Elefteriadou, 2014. "An Introduction to Traffic Flow Theory," Springer Optimization and Its Applications, Springer, edition 127, number 978-1-4614-8435-6, June.
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    Cited by:

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    4. 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.
    5. 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.
    6. 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).
    7. Zhou, Shirui & Ling, Shuai & Zhu, Chenqiang & Tian, Junfang, 2022. "Cellular automaton model with the multi-anticipative effect to reproduce the empirical findings of Kerner’s three-phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    8. Hu, Xiaojian & Lin, Chenxi & Hao, Xiatong & Lu, RuiYing & Liu, TengHui, 2021. "Influence of tidal lane on traffic breakdown and spatiotemporal congested patterns at moving bottleneck in the framework of Kerner’s three-phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    9. Hu, Xiaojian & Hao, Xiatong & Wang, Han & Su, Ziyi & Zhang, Fang, 2020. "Research on on-street temporary parking effects based on cellular automaton model under the framework of Kerner’s three-phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    10. Sehyun Tak & Jeongyun Kim & Donghoun Lee, 2022. "Study on the Extraction Method of Sub-Network for Optimal Operation of Connected and Automated Vehicle-Based Mobility Service and Its Implication," Sustainability, MDPI, vol. 14(6), pages 1-28, March.
    11. Qin, Shunda & He, Zhiting & Cheng, Rongjun, 2018. "An extended lattice hydrodynamic model based on control theory considering the memory effect of flux difference," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 809-816.
    12. Vranken, Tim & Sliwa, Benjamin & Wietfeld, Christian & Schreckenberg, Michael, 2021. "Adapting a cellular automata model to describe heterogeneous traffic with human-driven, automated, and communicating automated vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    13. 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.
    14. Yang, Haifei & Zhai, Xue & Zheng, Changjiang, 2018. "Effects of variable speed limits on traffic operation characteristics and environmental impacts under car-following scenarios: Simulations in the framework of Kerner’s three-phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 567-577.
    15. 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.
    16. Lyu, Zelin & Hu, Xiaojian & Zhang, Fang & Liu, Tenghui & Cui, Zhiwei, 2022. "Heterogeneous traffic flow characteristics on the highway with a climbing lane under different truck percentages: The framework of Kerner’s three-phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    17. Zhu, Liling & Tang, Yandong & Yang, Da, 2021. "Cellular automata-based modeling and simulation of the mixed traffic flow of vehicle platoon and normal vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    18. Cheng, Qixiu & Lin, Yuqian & Zhou, Xuesong (Simon) & Liu, Zhiyuan, 2024. "Analytical formulation for explaining the variations in traffic states: A fundamental diagram modeling perspective with stochastic parameters," European Journal of Operational Research, Elsevier, vol. 312(1), pages 182-197.
    19. Junyan Han & Xiaoyuan Wang & Gang Wang, 2022. "Modeling the Car-Following Behavior with Consideration of Driver, Vehicle, and Environment Factors: A Historical Review," Sustainability, MDPI, vol. 14(13), pages 1-27, July.
    20. Hu, Xiaojian & Qiao, Longqi & Hao, Xiatong & Lin, Chenxi & Liu, Tenghui, 2022. "Research on the impact of entry points on urban arterial roads in the framework of Kerner’s three-phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    21. Vranken, Tim & Schreckenberg, Michael, 2022. "Modelling multi-lane heterogeneous traffic flow with human-driven, automated, and communicating automated vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).

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