考虑减缓交通振荡的混合队列控制方法  

Mixed platoon control method considering traffic oscillation mitigation

作　　者：董长印 熊卓智 李霓 王丰[3,4,5] 张家瑞 王昊 DONG Chang-yin;XIONG Zhuo-zhi;LI Ni;WANG Feng;ZHANG Jia-rui;WANG Hao(School of Aeronautics,Northwestern Polytechnical University,Xi'an 710072,Shaanxi,China;National Key Laboratory of Aircraft Configuration Design,Northwestern Polytechnical University,Xi'an 710072,Shaanxi,China;Collaborative Innovation Center of Modern Urban Traffic Technologies,Southeast University,Nanjing 211189,Jiangsu,China;Jiangsu Key Laboratory of Urban ITS,Southeast University,Nanjing 211189,Jiangsu,China;School of Transportation,Southeast University,Nanjing 211189,Jiangsu,China)

机构地区：[1]西北工业大学航空学院,陕西西安710072 [2]西北工业大学飞行器基础布局全国重点实验室,陕西西安710072 [3]东南大学现代城市交通技术协同创新中心,江苏南京211189 [4]东南大学江苏省城市智能交通重点实验室,江苏南京211189 [5]东南大学交通学院,江苏南京211189

出　　处：《交通运输工程学报》2024年第6期212-229,共18页Journal of Traffic and Transportation Engineering

基　　金：国家重点研发计划(2022ZD0115600);国家自然科学基金项目(52302405,52072067,52372398);江苏省自然科学基金项目(BK20210249);国家资助博士后研究人员计划(GZC20230431)。

摘　　要：构建了一种混合队列中人工驾驶汽车(HDV)和智能网联汽车(CAV)的信息交互形式,基于此为CAV设计了反馈前馈控制器,并针对其中的控制参数提出了以减缓交通振荡为目标的优化方法;创建了由混合队列构成的环形封闭系统,其中CAV可间隔HDV进行车间通信;基于对HDV跟驰行为及其不确定性的建模,采用三阶车辆动力学模型、定时距规则以及反馈前馈控制器对CAV的控制策略进行设计;利用新一代仿真数据集和快速傅里叶变换分析了HDV速度波动的主要频率范围,构建了CAV对速度波动抑制程度的指标;在考虑HDV行为不确定性的前提下,针对此频率构造了同时优化弦稳定性水平与抑制速度波动的目标函数;基于实车轨迹数据,在考虑不同市场渗透率和CAV空间分布的情形下,对控制方法进行多维仿真评价。分析结果显示:相比于参考策略,CAV自身平均加速度波动减小10.9%~14.1%,最大速度波动减小7.8%~10.8%,碰撞减速度减小1.8%~21.6%,油耗降低2.9%~3.9%;对于整个混合车队,当CAV为均匀分布时,舒适、稳定、安全、节能等方面均有提升,并且在30%~60%的中等市场渗透率下提升效果显著。可见,控制方法可以有效抑制速度波动,大幅度提升CAV减缓交通振荡的能力。An information interaction form between human-driven vehicle(HDV)and connected automated vehicle(CAV)in a mixed platoon was established,based on which a feedback feedforward controller was designed for CAVs.Besides,an optimization method targeting the control parameters of CAVs was proposed to mitigate traffic oscillations.A circular closed system with a mixed platoon was formulated,where CAVs can transfer information through vehicle-to-vehicle communication spaced by HDVs.Based on the modelling of HDV car-following behaviors and their uncertainty,a third-order vehicle dynamics model,constant time gap policy,and feedback feedforward controller were used to design the control strategy for CAVs.A new generation of simulation data and fast Fourier transform were used to analyze the predominant frequency range of speed fluctuation of HDVs,and an index of the suppression degree of CAVs to speed fluctuation was constructed.By considering the uncertainty of HDV behaviors,an objective function was constructed for this frequency range to simultaneously optimize the string stability and suppress speed variation.Based on the real vehicle trajectory data,the control method was evaluated with simulations from multiple dimensions under the scenarios of different market penetration rates and spatial distributions of CAVs.Analysis results show that compared with reference strategies,the average acceleration variation of the individual CAV reduces by 10.9%-14.1%,and the maximum speed variation reduces by 7.8%-10.8%.The deceleration rate to avoid the crash reduces by 1.8%-21.6%,and the fuel consumption reduces by 2.9%-3.9%.For the whole mixed platoon,the comfort,stability,safety,and energy saving all improve when CAVs are uniformly distributed.The improvement effect is significant under the medium market penetration rate of 30%-60%.So,the control method can effectively suppress speed variation and substantially improve the ability of CAVs to mitigate traffic oscillations.

关 键 词：车辆控制 智能网联汽车 混合队列控制 交通振荡 协同自适应巡航控制 弦稳定性 

分 类 号：U491.2[交通运输工程—交通运输规划与管理]