Scholarlink

<p>This paper proposes a comprehensive speed guidance strategy for mixed vehicle platoons at signalized intersections. The strategy integrates communication delay compensation and models driver reaction time. This research addresses critical challenges in Cooperative Vehicle-Infrastructure Systems (CVIS), where heterogeneous vehicle behaviors and communication uncertainties significantly impact traffic efficiency. The key innovations include: (1) A four-dimensional speed guidance framework (acceleration, deceleration, constant speed, stopping) for mixed CAV-HV platoons; (2) A fuzzy logic-enhanced Smith predictor for dynamic V2X delay compensation; (3) A multi-factor driver reaction time model incorporating age, fatigue, and cognitive load effects. Quantitative results demonstrate that the system achieves maximum acceleration error reduction of 80.9% and speed error reduction of 62% under communication delays of 0.5–2.0&#xa0;s. The driver reaction time model improves trajectory prediction accuracy, increases intersection throughput by approximately 36% compared to fixed-parameter approaches. Prescan - MATLAB/Simulink co - simulation with 5 – vehicle platoons and field experiments with 3 - vehicle platoons confirm the practical effectiveness and safety of the proposed strategy. The integrated approach significantly enhances platoon coordination, reduces travel time, and improves overall intersection efficiency in mixed autonomous-human traffic environments.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Fuzzy logic-based speed guidance strategy for mixed platoons at intersections with communication delay compensation and driver reaction time modeling

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月23日

查看全文
  • Xiaofeng Liu,
  • Menghua Yan,
  • Runjia Dai,
  • Mingxing Gao

摘要

This paper proposes a comprehensive speed guidance strategy for mixed vehicle platoons at signalized intersections. The strategy integrates communication delay compensation and models driver reaction time. This research addresses critical challenges in Cooperative Vehicle-Infrastructure Systems (CVIS), where heterogeneous vehicle behaviors and communication uncertainties significantly impact traffic efficiency. The key innovations include: (1) A four-dimensional speed guidance framework (acceleration, deceleration, constant speed, stopping) for mixed CAV-HV platoons; (2) A fuzzy logic-enhanced Smith predictor for dynamic V2X delay compensation; (3) A multi-factor driver reaction time model incorporating age, fatigue, and cognitive load effects. Quantitative results demonstrate that the system achieves maximum acceleration error reduction of 80.9% and speed error reduction of 62% under communication delays of 0.5–2.0 s. The driver reaction time model improves trajectory prediction accuracy, increases intersection throughput by approximately 36% compared to fixed-parameter approaches. Prescan - MATLAB/Simulink co - simulation with 5 – vehicle platoons and field experiments with 3 - vehicle platoons confirm the practical effectiveness and safety of the proposed strategy. The integrated approach significantly enhances platoon coordination, reduces travel time, and improves overall intersection efficiency in mixed autonomous-human traffic environments.