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Emergent traffic flow patterns from different intelligent levels of autonomous vehicles in fog

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  • Qian, Yongsheng
  • Zhang, Qingru
  • Zeng, Junwei
  • Wei, Xu

Abstract

Before the widespread adoption of L4 and L5 autonomous vehicles, the road system will remain in a phase where L2 and L3 autonomous vehicles mix with human-driven vehicles for a long time. Low visibility in foggy conditions further affects both the traffic efficiency and safety of the mixed traffic flow. This paper considers the differences in driving characteristics of L0, L2, L3, and L4 autonomous vehicles under foggy conditions, constructs a two-lane cellular automata model for foggy highways, and calibrates the parameters of the Gipps model using actual car-following data. Through simulations under varying visibility conditions, we analyze the impact of autonomous vehicles at different levels on overall traffic flow. The results show that the autonomous vehicles can significantly enhance the capacity and average speed of the mixed traffic flows while reducing the congestion rate, and these benefits become more pronounced as the level of automation increases. Moreover, due to varying visibility, road density and penetration rates in different foggy scenarios, there are notable differences in how vehicles of different automation levels affect traffic safety (TET、TERCRI) and stability (SD). Within specific density ranges, the presence of autonomous vehicles improves the safety and stability of mixed traffic flow.

Suggested Citation

  • Qian, Yongsheng & Zhang, Qingru & Zeng, Junwei & Wei, Xu, 2026. "Emergent traffic flow patterns from different intelligent levels of autonomous vehicles in fog," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 683(C).
    • Handle: RePEc:eee:phsmap:v:683:y:2026:i:c:s037843712500891x
    DOI: 10.1016/j.physa.2025.131239
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    References listed on IDEAS

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