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Long memory is important: A test study on deep-learning based car-following model

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  • Wang, Xiao
  • Jiang, Rui
  • Li, Li
  • Lin, Yi-Lun
  • Wang, Fei-Yue

Abstract

Whether long memory effect plays an important role in car-following models remains unsolved. In this paper, we study the possible relationship between long memory effect and hysteresis phenomena observed in practice. Especially, we have compared the performance of different deep learning based car-following models that take various time-scale historical information as inputs. Test show that hysteresis phenomena can be correctly simulated only by car-following models with long memory. So, we argue that car-following models should embed long memory effect appropriately.

Suggested Citation

  • Wang, Xiao & Jiang, Rui & Li, Li & Lin, Yi-Lun & Wang, Fei-Yue, 2019. "Long memory is important: A test study on deep-learning based car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 786-795.
  • Handle: RePEc:eee:phsmap:v:514:y:2019:i:c:p:786-795
    DOI: 10.1016/j.physa.2018.09.136
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    Cited by:

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    2. Yu, Lei, 2020. "A new continuum traffic flow model with two delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    3. Wen Huan Ai & Ming Ming Wang & Da Wei Liu, 2023. "Analysis of macroscopic traffic flow model considering throttle dynamics," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(6), pages 1-18, June.
    4. Jiang, Wuhao & Wang, Kai & Lv, Yan & Guo, Jianfeng & Ni, Zhongjin & Ni, Yihua, 2020. "Time series based behavior pattern quantification analysis and prediction — A study on animal behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    5. Wang, Zihao & Zhu, Wen-Xing, 2022. "Modeling and stability analysis of traffic flow considering electronic throttle dynamics on a curved road with slope," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).

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