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Impact analysis of driving stochasticity on heterogeneous traffic flow stability

Author

Listed:
  • Zhang, Zhishun
  • Xu, Ting
  • Easa, Said M.
  • Hui, Shouwei
  • Lai, Xinhe

Abstract

Research on interactions between Intelligent and Connected Vehicles (ICVs) and Human-Driven Vehicles (HDVs) has grown rapidly in recent years. Yet the role of driving stochasticity, expressed through heterogeneous HDV driving styles, remains unclear. Therefore, this study investigates the effects of HDV driving stochasticity on the stability evolution of heterogeneous traffic flow from both macroscopic and microscopic perspectives. We firstly classified stochastic driving behaviors of HDV from car-following (CF) events into three types using a K-means-Crested Porcupine Optimizer (K-CPO) clustering algorithm. Based on this classification, we employed an Intelligent Driver Model (IDM)-based CF model that embeds driving stochasticity and minor disturbances, and proposed an analytical framework for stability in heterogeneous traffic flow. Through numerical analyses and simulations at both macro and micro scales, five representative cases evaluate the effects of driving stochasticity under varying HDV driving styles, ICV penetration rates (ICV-PRs), traffic flow speeds, leading vehicle speeds and its speed fluctuations. The results show that increasing the proportion of more conservative HDVs enhances heterogeneous traffic flow stability. It amplifies the stabilizing influence of ICVs and mitigating the destabilizing effect of more aggressive HDVs, especially at higher ICV-PRs. When CHDVs constitute 66.67 % of HDVs, raising their proportion lowers the equilibrium speed by 7.00–9.89 % as ICV-PR increases from 0.1 to 0.9, respectively. In contrast, the aggressive human-driven vehicles (AHDVs) have the opposite effect. More aggressive HDVs further exert a less negative effect on the stability at lower speeds combined with lower ICV-PRs or at higher speeds. Moreover, higher ICV-PRs mitigate the destabilizing effects of more aggressive HDVs. When combined with a larger proportion of conservative HDVs further, heterogeneous traffic achieves better stability.

Suggested Citation

  • Zhang, Zhishun & Xu, Ting & Easa, Said M. & Hui, Shouwei & Lai, Xinhe, 2026. "Impact analysis of driving stochasticity on heterogeneous traffic flow stability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 681(C).
    • Handle: RePEc:eee:phsmap:v:681:y:2026:i:c:s0378437125007319
    DOI: 10.1016/j.physa.2025.131079
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    References listed on IDEAS

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