摘要
未来协同自适应巡航控制(Cooperative Adaptive Cruise Control,CACC)车辆和传统车辆混合交通流的稳定性决定了CACC技术对交通拥堵、能耗排放的改善程度.鉴于此,研究不同CACC渗透率时这种混合交通流的稳定性.应用基于轨迹数据标定的IDM(Intelligent Driver Model,IDM)模型和由加州伯克利PATH实验室实车测试验证的CACC模型分别作为传统车辆跟驰模型和CACC车辆跟驰模型.依据传统车辆在扰动下的稳定性,确定高稳态速度和低稳态速度,并考虑两种车型相对数量、相对位置的随机性,设计数值仿真实验.实验结果表明,在高稳态速度下,不同CACC渗透率时混合车队均整体稳定;在低稳态速度下,当CACC渗透率较小时,车队整体不稳定,CACC渗透率需达到50%以上时,才有可能使得混合车队由不稳定转变为稳定.
The string stability of future traffic flow mixed with cooperative adaptive cruise control （CACC） and traditional vehicles will determine the improvement of CACC on traffic capacity and fuel consumptions. Therefore, this paper focuses on string stability of this mixed traffic flow for different CACC penetration ranges. Intelligent driver model （IDM） calibrated using trajectory data and CACC model validated using real vehicles by PATH laboratory of Berkeley are employed to be traditional vehicle car-following model and CACC car-following model respectively. Higher and lower equilibrium velocities are determined based on traditional vehicle stability under small perturbation and numerical simulations are designed considering the randomness of the relative quantity and positions of the two kinds of vehicles. Experimental results show that mixed traffic flow is stable under higher equilibrium velocities for different CACC penetration ranges. However, the mixed traffic flow is unstable under lower equilibrium velocities and lower CACC market penetration. CACC market penetration needs to reach at least 50% to guarantee that the mixed traffic flow can be stable under lower equilibrium velocities.
出处
《交通运输系统工程与信息》
EI
CSCD
北大核心
2017年第4期63-69,104,共8页
Journal of Transportation Systems Engineering and Information Technology
基金
国家自然科学基金(51478113
51508122)
东南大学优秀青年教师教学科研资助项目(2242015R30028)
广西科技攻关计划(15248002-10)~~
关键词
交通工程
稳定性
跟驰模型
混合交通流
协同自适应巡航控制
稳态速度
traffic engineering
string stability
car-following model
mixed traffic flow
cooperative adaptive cruise control
equilibrium velocity
作者简介
秦严严（1989-），男，江苏沛县人，博士生．
通信作者：haowang@seu．edu．cn
