可接受间距策略下网联车辆队列安全优化控制方法

doi:10.16097/j.cnki.1009-6744.2025.06.005

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (6): 50-61.DOI: 10.16097/j.cnki.1009-6744.2025.06.005

• 智能交通系统与信息技术 • 上一篇下一篇

可接受间距策略下网联车辆队列安全优化控制方法

杨海飞^*1，唐勇¹，郭延永²，李红伟¹ ，赵恩泽¹

1. 河海大学，土木与交通学院，南京210024；2.东南大学，交通学院，南京210096

收稿日期:2025-07-11 修回日期:2025-08-25 接受日期:2025-08-28 出版日期:2025-12-25 发布日期:2025-12-23
作者简介:杨海飞(1984—)，男，贵州贵阳人，副教授。
基金资助:
国家自然科学基金 (52272343)；武汉市交通强国建设试点科技联合项目 (2024-2-1)。

Safety Optimization Control for Connected Vehicle Platoon Under Acceptable Spacing Policy

YANG Haifei^*1, TANG Yong¹, GUO Yanyong², LI Hongwei¹, ZHAO Enze¹

1. School of Civil and Transportation Engineering, Hohai University, Nanjing 210024, China; 2. School of Transportation, Southeast University, Nanjing 210096, China

Received:2025-07-11 Revised:2025-08-25 Accepted:2025-08-28 Online:2025-12-25 Published:2025-12-23
Supported by:
National Natural Science Foundation of China (52272343)；WuhanPilot Construction of a Strong Transportation Country Science and Technology Joint Research Projects (2024-2-1)。

摘要/Abstract

摘要： 基于可接受间距策略的三相自适应巡航系统(Three-Phase Adaptive Cruise Control,TPACC)以线性控制器实现车辆间的速度同步，虽然较恒定时距策略改善了稳定性，但在面临复杂交通扰动时更易诱发交通冲突。为此，本文在车联网支持下运用模型预测控制(Model Predictive Control, MPC)对CTPACC(Cooperative TPACC)车辆队列进行安全优化。首先，构建考虑系统延时的CTPACC运动学模型，通过数值实验阐明可接受间距策略下队列控制的稳定性与安全性关系；进而，提出基于速度同步的MPC安全优化策略，同时，引入终端约束与贝叶斯优化保障系统稳定，并设计延时补偿机制改善控制性能；最后，结合典型工况验证所提策略的有效性。结果显示：线性控制器过高的稳定裕度将导致追尾事故或紧急安全模式介入，且安全性与稳定性呈现非单调性关系。针对此，无延时补偿MPC在控制稳定基础上带来安全性整体提升，延时补偿机制进一步实现稳定性与安全性的全面优化，理论工况下，安全风险指标时间积分碰撞时间、时间暴露碰撞时间、队列振荡指标平均最大超调量和总绝对加加速度值的降幅达到24.4%~61.7%、29.7%~57.4%、52.7%~90.8%和13.9%~81.3%，且在扰动强度敏感性实验以及实际工况测试中均表现相同趋势。此外，所提策略抑制紧急安全模式介入，提升车辆控制平稳性。交通流相变分析表明，延时补偿MPC在瓦解拥堵核的同时，两项安全风险指标较典型线性控制器分别下降50.4%与53.3%。

关键词: 智能交通, 安全优化控制, 模型预测控制, 网联车辆队列, 可接受间距策略

Abstract: The existing Three-Phase Adaptive Cruise Control (TPACC) based on the acceptable spacing policy realizes speed synchronization with linear controller, improving stability over the constant headway policy but is more likely to induce traffic conflicts when facing complex traffic disturbances. To improve this, this paper uses Model Predictive Control (MPC) to optimize the safety of Coperative TPACC (CTPACC) with the support of vehicle network technology. A kinematic model of CTPACC is developed considering the system delay. The relationship between stability and safety under acceptable spacing policy is clarified using numerical experiments. Then, a safety optimization policy of MPC based on speed synchronization is proposed, and terminal constraints and Bayesian optimization are introduced to maintain the stability. A delay compensation mechanism is designed to improve the control performance. At last, the effectiveness of the proposed policy is verified by typical working conditions. The results show that, excessively high stability margin of the linear controller will lead to rear-end accidents or emergency safety mode intervention, and safety and stability show a non-monotonic relationship. To address this, the proposed MPC without delay compensation achieves an overall improvement in safety while maintaining stability. The delay compensation mechanism further enables comprehensive optimization of both margins of stability and safety. In the theoretical working condition, the reductions in the safety risk indicators of time-integrated time-to-collision, time-exposed time-to-collision, the platoon oscillation indicators of average maximum overshoot, total absolute jerk reach 24.4%~61.7%, 29.7%~57.4%, 52.7%~90.8%, and 13.9%~81.3%. Moreover, sensitivity experiments with disturbance intensity and actual working condition tests consistently demonstrate the same trend. In addition, the proposed policy suppresses the emergency safety mode intervention and improves the smoothness of acceleration control. Phase transition analysis indicates that the delay-compensated MPC, while mitigating congestion nuclei, reduces two safety risk indicators by 50.4% and 53.3% compared to the typical linear controller.

Key words: intelligent transportation, safety optimization control, model predictive control, connected vehicle platoon, acceptable spacing policy

中图分类号:

U491

杨海飞, 唐勇, 郭延永, 李红伟, 赵恩泽. 可接受间距策略下网联车辆队列安全优化控制方法[J]. 交通运输系统工程与信息, 2025, 25(6): 50-61.

YANG Haifei, TANG Yong, GUO Yanyong, LI Hongwei, ZHAO Enze. Safety Optimization Control for Connected Vehicle Platoon Under Acceptable Spacing Policy[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(6): 50-61.

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http://www.tseit.org.cn/CN/Y2025/V25/I6/50

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可接受间距策略下网联车辆队列安全优化控制方法

Safety Optimization Control for Connected Vehicle Platoon Under Acceptable Spacing Policy

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