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Research on on-street temporary parking effects based on cellular automaton model under the framework of Kerner’s three-phase traffic theory

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  • Hu, Xiaojian
  • Hao, Xiatong
  • Wang, Han
  • Su, Ziyi
  • Zhang, Fang

Abstract

In this paper, the on-street temporary parking behavior is studied under the framework of Kerner’s three-phase traffic theory based on an improved Kerner–Klenov–Schreckeneberg–Wolf (KKSW) cellular automation (CA) model named KKSW-OSTP (on-street temporary parking) model. The complete parking process is divided into four steps and the microscopic effects of these four steps are analyzed. The parking behavior has significant negative impacts on the traffic flow, while having limited positive impacts on the left lane. The congestion pattern caused by on-street temporary parking is analyzed. Localized synchronized flow pattern (LSP) is observed in low-density traffic condition. Moving synchronized flow pattern (MSP) and General Pattern (GP) are observed in high-density traffic condition. The macroscopic effects of on-street temporary parking on road traffic conditions are analyzed by introducing parking rate into the model. It is found that more on-street temporary parking demand results in higher probability of traffic breakdown and higher congestion level. However, with the increase of parking rate and leave-parking rate, the frequency of rear-end conflicts reduces.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:phsmap:v:545:y:2020:i:c:s0378437119320771
    DOI: 10.1016/j.physa.2019.123725
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    References listed on IDEAS

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    Cited by:

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    4. 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).
    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. Wu, Peijie & Chen, Tianyi & Diew Wong, Yiik & Meng, Xianghai & Wang, Xueqin & Liu, Wei, 2023. "Exploring key spatio-temporal features of crash risk hot spots on urban road network: A machine learning approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    7. 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).

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