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Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory: A brief review

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  • Kerner, Boris S.

Abstract

It is explained why the set of the fundamental empirical features of traffic breakdown (a transition from free flow to congested traffic) should be the empirical basis for any traffic and transportation theory that can be reliably used for control and optimization in traffic networks. It is shown that the generally accepted fundamentals and methodologies of the traffic and transportation theory are not consistent with the set of the fundamental empirical features of traffic breakdown at a highway bottleneck. To these fundamentals and methodologies of the traffic and transportation theory belong (i) Lighthill–Whitham–Richards (LWR) theory, (ii) the General Motors (GM) model class (for example, Herman, Gazis et al. GM model, Gipps’s model, Payne’s model, Newell’s optimal velocity (OV) model, Wiedemann’s model, Bando et al. OV model, Treiber’s IDM, Krauß’s model), (iii) the understanding of highway capacity as a particular (fixed or stochastic) value, and (iv) principles for traffic and transportation network optimization and control (for example, Wardrop’s user equilibrium (UE) and system optimum (SO) principles). Alternatively to these generally accepted fundamentals and methodologies of the traffic and transportation theory, we discuss the three-phase traffic theory as the basis for traffic flow modeling as well as briefly consider the network breakdown minimization (BM) principle for the optimization of traffic and transportation networks with road bottlenecks.

Suggested Citation

  • Kerner, Boris S., 2013. "Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory: A brief review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5261-5282.
  • Handle: RePEc:eee:phsmap:v:392:y:2013:i:21:p:5261-5282
    DOI: 10.1016/j.physa.2013.06.004
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    Citations

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    Cited by:

    1. Yamada, Takashi, 2022. "Generalizing the probability of reaching a destination in case of route blockage," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    2. 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).
    3. 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).
    4. Jiang, Rui & Hu, Mao-Bin & Zhang, H.M. & Gao, Zi-You & Jia, Bin & Wu, Qing-Song, 2015. "On some experimental features of car-following behavior and how to model them," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 338-354.
    5. 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).
    6. Xu, Xihua & Pang, John & Monterola, Christopher, 2015. "Asymmetric optimal-velocity car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 565-571.
    7. Li, Xiaopeng & Cui, Jianxun & An, Shi & Parsafard, Mohsen, 2014. "Stop-and-go traffic analysis: Theoretical properties, environmental impacts and oscillation mitigation," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 319-339.
    8. 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).
    9. 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).
    10. Rui Jiang & Mao-Bin Hu & Qing-Song Wu & Wei-Guo Song, 2017. "Traffic Dynamics of Bicycle Flow: Experiment and Modeling," Transportation Science, INFORMS, vol. 51(3), pages 998-1008, August.
    11. 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).
    12. Wu, Yuanyuan & Wang, David Z.W. & Zhu, Feng, 2022. "Influence of CAVs platooning on intersection capacity under mixed traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    13. 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.
    14. 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.
    15. Junfang Tian & Bin Jia & Shoufeng Ma & Chenqiang Zhu & Rui Jiang & YaoXian Ding, 2017. "Cellular Automaton Model with Dynamical 2D Speed-Gap Relation," Transportation Science, INFORMS, vol. 51(3), pages 807-822, August.
    16. 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.
    17. 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.
    18. Tian, Junfang & Jiang, Rui & Jia, Bin & Gao, Ziyou & Ma, Shoufeng, 2016. "Empirical analysis and simulation of the concave growth pattern of traffic oscillations," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 338-354.
    19. Chmura, Thorsten & Herz, Benedikt & Knorr, Florian & Pitz, Thomas & Schreckenberg, Michael, 2014. "A simple stochastic cellular automaton for synchronized traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 332-337.

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