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针对协同自适应巡航控制(CACC)车辆市场普及过程中存在的CACC车辆、自适应巡航控制(ACC)车辆与人工驾驶汽车混合行驶的异质交通流,应用智能驾驶模型(IDM)和由加州大学伯克利分校PATH实验室实车验证的ACC模型、CACC模型分别作为人工车辆、ACC车辆和CACC车辆的跟驰模型,建立能够反映异质交通流中3种车型相互关系的解析表达。基于此,推导不同CACC车辆渗漏率p下的异质交通流基本图模型,并针对异质交通流基本图散点分布与基本路段通行能力,设计数值仿真试验。最后,针对ACC车辆和CACC车辆的期望车间时距进行参数敏感性分析。研究结果表明:建立的异质交通流解析表达与随机性仿真试验的误差小于1.5%,异质交通流基本图解析可取代基本路段通行能力的仿真试验,用于分析不同p时的异质交通流通行能力;ACC期望车间时距ta取值1.1 s时,交通流通行能力随着p的增加逐渐提升;当t_a=1.6 s,p低于30%时,异质交通流通行能力与传统人工车辆通行能力基本相当;当t_a=2.2 s,p低于40%时,异质交通流通行能力低于人工车辆通行能力;同时,CACC车辆期望车间时距tc越小,异质交通流通行能力越大;建立的异质交通流解析表达可为异质交通流其他特性的解析研究提供思路,异质交通流基本图解析结果,从通行能力的角度为ACC,CACC上层控制器设计提供期望车间时距取值的参考。
In view of the heterogeneous traffic flow of CACC vehicles, adaptive cruise control (ACC) vehicles mixed with manual driving vehicles and the application of intelligent driving model (IDM) for the popularization of cooperative adaptive cruise control (CACC) vehicles, The ACC model and CACC model verified by PATH laboratory in Berkeley are respectively used as the car-following model for artificial vehicles, ACC vehicles and CACC vehicles to establish the analytical expression reflecting the interrelationship between the three types of vehicles in heterogeneous traffic flow. Based on this, the basic model of heterogeneous traffic flow with different CACC vehicle leakage rate p is deduced. According to the scatter distribution of the basic traffic flow of heterogeneous traffic flow and the capacity of the basic section, a numerical simulation experiment is designed. Finally, parametric sensitivity analysis is performed on expected shop-floor time for ACC and CACC vehicles. The results show that the error of analytic expression and stochastic simulation of heterogeneous traffic flow is less than 1.5%. The analysis of heterogeneous traffic flow basic graph can replace the simulation test of traffic capacity of the basic segment, which can be used to analyze heterogeneous traffic at different p When ACC is expected to take shop time ta of 1.1 s, the traffic capacity gradually increases with the increase of p. When t_a = 1.6 s and p is less than 30%, the traffic flow capacity of heterogeneous traffic flow is different from that of traditional labor Vehicle traffic capacity is basically equivalent; when t_a = 2.2 s, p is less than 40%, traffic capacity of heterogeneous traffic flow is lower than traffic capacity of artificial vehicles; meanwhile, CACC vehicles expect the smaller workshop time tc, heterogeneous traffic flow capacity The established analytical expression of heterogeneous traffic flow can provide ideas for the analytical study of other characteristics of heterogeneous traffic flow and the results of the analysis of heterogeneous traffic flow basic graphs, providing the desired workshop for ACC, CACC upper controller design from the perspective of traffic capacity Reference for the value of time span.