超高速公路智能网联车辆编队策略研究

doi:10.16097/j.cnki.1009-6744.2025.06.006

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (6): 62-73.DOI: 10.16097/j.cnki.1009-6744.2025.06.006

• 智能交通系统与信息技术 • 上一篇下一篇

超高速公路智能网联车辆编队策略研究

何永明^*，卢杨彭，刘汇洋，李鑫然

东北林业大学，土木与交通学院，哈尔滨150040

收稿日期:2025-08-05 修回日期:2025-09-30 接受日期:2025-10-16 出版日期:2025-12-25 发布日期:2025-12-23
作者简介:何永明(1979—)，男，湖北广水人，副教授，博士。
基金资助:
黑龙江省自然科学基金(LH2023E011)；长沙理工大学极端环境绿色长寿道路工程全国重点实验室开放基金(kfj230105)。

Platooning Strategies Study for Connected Autonomous Vehicles on Superhighways

HE Yongming^*, LU Yangpeng, LIU Huiyang, LI Xinran

School of Civil Engineering and Transportation, Northeast Forestry University, Harbin 150040，China

Received:2025-08-05 Revised:2025-09-30 Accepted:2025-10-16 Online:2025-12-25 Published:2025-12-23
Supported by:
Natural Science Foundation of Heilongjiang Province, China (LH2023E011)；Open Fund of National Key Laboratory of Green and Long-Life Road Engineering in Extreme Environment, Changsha University of Science & Technology (kfj230105)。

摘要/Abstract

摘要： 编队的鲁棒控制策略对于实现智能网联车辆在超高速公路上的安全高效运行至关重要。为提高超高速公路场景下智能网联车辆编队的运行稳定性与安全性，本文提出一种车辆编队控制策略。构建考虑通信时延的全速度差模型作为底层跟驰基础，在领导者-跟随者信息拓扑下，设计一种非线性编队控制律，其核心在于通过反解底层跟驰模型的最优速度函数动态计算与速度相关的非线性期望间距，确保编队控制的稳态目标与单车驾驶行为的平衡态相统一。通过传递函数法严谨分析模型的稳定性，并基于H∞性能指标优化控制器参数。仿真结果表明：在120~160km·h^-1的动态变速场景下，与CACC(Cooperative Adaptive Cruise Control)基准策略相比，DLFC(Delayed Leader-Follower Control)策略展现出较好的弦稳定性与动态跟踪性能，能够有效抑制扰动放大。在随机扰动的极限紧急制动场景下，经蒙特卡洛仿真验证，DLFC策略相较于基准策略展现出高安全冗余，能有效规避碰撞风险，并将车队遭遇高风险状态的概率控制在20%以内，能够保障超高速公路场景下车辆编队的安全性。

关键词: 智能交通, 编队策略, 稳定性分析, 智能网联车辆, 超高速公路

Abstract: Robust platoon control strategies are crucial for enabling safe and efficient operation of Connected and Automated Vehicles (CAV) in superhighway scenarios. This paper proposes a CAV platooning strategy to enhance the stability and safety of platoons on superhighways. First, a comprehensive full velocity difference model considering communication delays is developed as the fundamental car-following foundation. Then, under a leader-follower information topology, a nonlinear platoon control law is designed, where the optimal velocity function of the underlying car-following model is inverted to dynamically compute a speed dependent nonlinear desired spacing. This approach ensures consistency between the steady-state platoon target and individual vehicle driving equilibrium. Furthermore, both local and string stability of the proposed model are rigorously analyzed using transfer function methods, and controller parameters are systematically optimized via the H∞ norm. Simulation results demonstrate that, in dynamic speed scenarios ranging from 120 km·h-1 to 160 km·h^-1, the proposed Delayed Leader-Follower Control (DLFC) strategy achieves significantly better string stability and tracking performance compared with the benchmark Cooperative Adaptive Cruise Control (CACC) strategy, with smoother acceleration responses that effectively prevent disturbance amplification along the platoon. In the extreme emergency braking scenarios with random disturbances, the comprehensive Monte Carlo simulations verify that the DLFC strategy provides higher safety margins, effectively avoids collision risks, and reduces the probability of high-risk states to below 20%, thereby substantially improving platoon safety under extreme superhighway conditions.

Key words: intelligent transportation, platooning strategy, stability analysis, connected autonomous vehicles, superhighway

中图分类号:

U491

何永明, 卢杨彭, 刘汇洋, 李鑫然. 超高速公路智能网联车辆编队策略研究[J]. 交通运输系统工程与信息, 2025, 25(6): 62-73.

HE Yongming, LU Yangpeng, LIU Huiyang, LI Xinran. Platooning Strategies Study for Connected Autonomous Vehicles on Superhighways[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(6): 62-73.

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超高速公路智能网联车辆编队策略研究

Platooning Strategies Study for Connected Autonomous Vehicles on Superhighways

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