混入智能车的下匝道瓶颈路段交通流建模与仿真分析

以下匝道瓶颈路段为研究背景,以手动驾驶汽车和两类智能车为研究对象,包括自适应巡航(ACC)汽车和协同自适应巡航(CACC)汽车,建立了混入智能车的混合交通流模型.在车辆的纵向控制层面,分别构建了手动驾驶汽车改进舒适驾驶元胞自动机规则和智能车的跟驰模型;基于车辆下匝道行驶特性,引入车辆感知范围R、换道控制区域LLC、换道冒险因子λ等参数,建立了控制车辆横向运动的自由换道和强制换道模型.通过对混合交通流模型进行数值仿真发现,CACC车辆混入率PCACC、车辆感知范围R、换道区域长度LLC和换道冒险程度λ均对下匝道交通系统产生影响.当CACC车辆混入率低于0.5时,CACC退化为ACC的概率增大,系统稳定性下降,交通拥堵呈恶化趋势;当CACC车辆混入率大于0.5时,车辆运行速度显著提升,拥堵消散能力提高.增大车辆感知范围、加长换道区域长度、提高换道冒险程度,都能够有效缓解改善下匝道瓶颈路段主线的拥挤状况,而对匝道运行效率影响并不明显.     

随机计及相对速度的交通流跟驰模型

从研究微观个体车辆行为出发，考虑车辆加速过程的不确定性，提出了随机计及相对速度的 交通流跟驰模型(SR-OV模型).对随机相对速度的跟驰模型的动力学方程进行稳定性分析，得 到与Bando跟驰模型不同的稳定性判据，其稳定性优于Bando模型.运用摄动理论分析交通过 程中密度波的变化，结果表明，在发生交通阻塞相变时，交通密度波以mKdV方程描述的扭结 -反扭结波演化.对随机相对速度跟驰模型进行数值模拟和分析，结果发现车流速度的变化小 于Bando模型的速度变化，而且与随机概率有关，当随机考虑相对速度的概率增大时，初始 的小扰动不会放大对车流产生影响，甚至长时间就消失，这与Bando模型完全不同.数值模拟 所得到的相图与解析解相符合,而且交通流稳定区域大于Bando模型.从车间距-速度演化图上 ，随着随机概率的增大，SR-OV模型在初始时存在的滞后现象，随着时间的增长，趋于稳定 状态后，滞后曲线收敛于一小区域，滞后效应被削弱.这完全不同于Bando模型，在Bando模 型中，滞后曲线由一点向外扩散，滞后曲线区域越来越大，车流趋于不稳定状态. 关键词： 交通流 跟驰模型 稳定性判据 相对速度     

基于驾驶员行为的元胞自动机模型研究

从研究驾驶员行为入手,分析了驾驶员行为作用机理,并结合元胞自动机(CA)模型,将与车辆自身速度、相对速度、车间距和安全车间距有关的驾驶员行为作用机理引入CA模型(简称ACA).并利用ACA模型进行微观交通仿真观察到亚稳态、相分离和回滞现象,并将ACA模型与只考虑车辆自身速度和车间距的CA模型(简称BCA)的仿真结果进行比较可得:宏观方面,从最大车流量、稳定性和堵塞消溶效率三方面进行对比,ACA模型的仿真结果显示有更高并更接近实测数据的最大流量值,有更强的稳定性,堵塞消溶的效率更高;微观方面,从车辆速度波动和车头间距波动两方面进行对比,ACA模型的仿真结果显示车辆不会骤然加速或减速,车辆能够相对均匀地分布在道路上.这些结果说明相对速度和安全间距对驾驶员行为会产生重要影响,也说明ACA模型与实际情况更符,有一定实际意义.     

随机延迟概率对交通流的影响

考虑影响随机延迟概率的几种因素：当车速预期大于车距时，车辆处于减速状态，对前车状态变化的随机延迟反应较大，具有的延迟概率较大；当车速预 期 等于车距时，车辆处于平稳跟随行驶状态，具有的延迟概率较小；当车速预期小于车距时，车辆处于加速状态，其延迟概率最小. 计算机数值模拟得到的基本图不同于NaSch模型的基 本图，在基本图上出现阻塞的范围内存在两个不同的区域，分别对应于具有不同激波速度的交通阻塞. 同时，研究了交通阻塞到消散的滞后现象. 关键词： 交通流 元胞自动机模型 基本图 交通阻塞     

速度限制对交通流的影响

运用元胞自动机模型研究单车道路面上设立限速区对交通流的影响.计算机模拟结果显示,在交通流与密度的基本图中存在饱和交通流量,其大小取决于限速区的最大速度.限速区的设立导致不同相的分离.在确定性的模型中,当车辆密度较低时,存在两种不同的自由流相;而当车辆密度较高时,出现最大交通流相和自由流相.在随机模型中,车辆密度较高时,出现最大交通流相-堵塞相-自由流.对交通流以及临界密度等量给出一些解析结果.     

考虑横向分离与超车期望的车辆跟驰模型

为了更加客观地描述实际的车辆跟驰行为, 在优化速度模型的基础上, 通过引入横向分离参数并提出超车期望和虚拟前车的概念, 建立了考虑横向分离与超车期望的车辆跟驰模型.对模型进行线性稳定性分析, 得到了模型稳定性条件, 发现车辆横向分离、超车期望和虚拟前车的位置的增加, 在车流密度较小、车速较快的情况下, 使得交通流稳定区域增大, 但在车流密度较大、车速较慢的情况下, 反而使得交通流稳定区域减小.数值模拟结果验证了模型稳定性分析的结果, 表明在交通瓶颈处等交通流密度较大、运行缓慢的区域, 为抑制交通拥堵, 应该限制车辆的横向偏移和超车行为的发生. 关键词： 交通流 车辆跟驰模型 横向分离 超车期望     

决定论性逐步加速交通流模型的渐近稳态行为

研究Nagel-Schreckenberg(NS)交通流元胞自动机模型在不考虑车辆随机延迟情况下的决定论性模型的基本图,即渐近稳态的车流平均速度作为车辆密度的函数关系．证明决定论性NS模型,在车流的自组织作用下,其渐近稳态的基本图,与决定论性Fukui-Ishibashi(FI)交通流模型的基本图完全相同．这个结果表明,若把FI交通流模型中的车辆突然加速方式（即车辆速度可以在仅仅一个时步内加速到其最高速限M或前方空距所允许的最大速度）,改变为车辆逐步加速方式（车辆速度在每一时步中最多仅能增加一个速度单位）,则车辆的自组织相互作用,并不会改变其车流的长时间渐近稳态行为． 关键词：     

中小学门口道路上学期间的一个元胞自动机模型

在已有交通流道路瓶颈、交织区和混合交通流研究的基础上,建立一个中小学门口道路区段上学期间的元胞自动机模型,对上学期间的道路交通流特性进行了模拟,对驾私家车送学生上学比例、乘校车上学比例和交警现场指挥对道路交通流的影响进行实验分析.模拟结果表明减少驾车送学生上学比例、增加乘校车学生比例、辅助以交警现场指挥,可保证交通安全,从而达到抑制交通拥堵、减少车辆总通行时间提高道路实际通行能力的目的.     

考虑自适应巡航车辆影响的上匝道系统混合交通流模型

在考虑自适应巡航(adaptive cruise control, ACC)车辆的交通流模型的基础上, 建立了考虑ACC车辆影响的上匝道系统混合交通流模型, 研究ACC车辆引入对上匝道交通系统交通流的影响. 为了描述ACC车辆和手动驾驶车辆在交通流运行中的差异, 分别构建了基于常车头时距原则的ACC 车辆跟驰子模型和手动驾驶车辆MCD元胞自动机子模型; 基于上匝道车辆合流驶入主线的需求, 建立了换道子模型, 引入了表征驾驶员换道心理的参数λ. 通过对混合交通流模型进行数值模拟发现, ACC车辆的混入可以有效改善上匝道系统交通流的运行, 降低合流等事件对于交通流运行的影响, 抑制交通拥堵的时空范围及拥堵强度, 提高交通流的平均速度和流量. 此外在混合交通流模型中, ACC车辆期望车头时距H_d的减小与换道心理参数λ 的增大均可以提高混合交通流运行的速度和流量, 而合流区长度l_w对混合交通流影响则因上匝道车辆驶入概率的不同而存在差异.     

双下匝道系统的交通流动态特征及其优化

利用多车道元胞自动机模型研究双下匝道系统的交通流动态演化特征.采用可变情报板来实现交通诱导,着重分析驾驶员选择目标匝道的决策行为及其对道路通行能力的影响.分别建立了无可变情报板的基本模型和有可变情报板的诱导模型.通过数值模拟,分别给出了相应的相图、道路通行能力、流量图和时空斑图,分析了进车概率、出车比例和出车道长度对交通行为的影响.通过对两个模型模拟结果的比较分析,发现当出车道长度较小而进车概率、出车比例都较大时,可变情报板的诱导信息能明显提高下游匝道的利用率,改善道路交通流状况,从而缓解交通拥堵.     

Stability analysis of traffic flow with extended CACC control models

To further investigate car-following behaviors in the cooperative adaptive cruise control(CACC) strategy,a comprehensive control system which can handle three traffic conditions to guarantee driving efficiency and safety is designed by using three CACC models.In this control system,some vital comprehensive information,such as multiple preceding cars' speed differences and headway,variable safety distance(VSD) and time-delay effect on the traffic current and the jamming transition have been investigated via analytical or numerical methods.Local and string stability criterion for the velocity control(VC) model and gap control(GC) model are derived via linear stability theory.Numerical simulations are conducted to study the performance of the simulated traffic flow.The simulation results show that the VC model and GC model can improve driving efficiency and suppress traffic congestion.     

Modeling the heterogeneous traffic flow considering the effect of self-stabilizing and autonomous vehicles

With the increasing maturity of automatic driving technology,the homogeneous traffic flow will gradually evolve into the heterogeneous traffic flow,which consists of human-driving and autonomous vehicles.To better study the characteristics of the heterogeneous traffic system,this paper proposes a new car-following model for autonomous vehicles and heterogeneous traffic flow,which considers the self-stabilizing effect of vehicles.Through linear and nonlinear methods,this paper deduces and analyzes the stability of such a car-following model with the self-stabilizing effect.Finally,the model is verified by numerical simulation.Numerical results show that the self-stabilizing effect can make the heterogeneous traffic flow more stable,and that increasing the self-stabilizing coefficient or historical time length can strengthen the stability of heterogeneous traffic flow and alleviate traffic congestion effectively.In addition,the heterogeneous traffic flow can also be stabilized with a higher proportion of autonomous vehicles.     

Fundamental diagram in traffic flow of mixed vehicles on multi-lane highway

We study the fundamental diagram for traffic flow of vehicular mixture on a multi-lane highway. We present the car-following model of multi-lane traffic in which slow and fast vehicles flow with changing lanes. We investigate the traffic states of the vehicular mixture under the periodic boundary. Two values of the current appear at a density and two current curves are obtained. Vehicles move with changing lanes in the traffic state of high current, while vehicles move without changing lanes in the traffic state of low current. They depend on the density, the fraction of slow vehicles, and the initial condition. In the high-current curve, the jamming transition between the free flow and the jammed state occurs at a low density. The fundamental diagrams (current-density diagrams) are shown for the single-lane, two-lane, three-lane, and four-lane traffics.     

A new dynamic model for heterogeneous traffic flow

Based on the property of heterogeneous traffic flow, we in this Letter present a new car-following model. Applying the relationship between the micro and macro variables, a new dynamic model for heterogeneous traffic flow is obtained. The fundamental diagram and the jam density of the heterogeneous traffic flow consisting of bus and car are studied under three different conditions: (1) without any restrictions, (2) under the action of the traffic control policy that restrains some private cars and (3) using bus to replace the private cars restrained by the traffic control policy. The numerical results show that our model can describe some qualitative properties of the heterogeneous traffic flow consisting of bus and car, which verifies that our model is reasonable.     

Effect of driver over-acceleration on traffic breakdown in three-phase cellular automaton traffic flow models

Based on simulations with cellular automaton (CA) traffic flow models, a generic physical feature of the three-phase models studied in the paper is disclosed. The generic feature is a discontinuous character of driver over-acceleration caused by a combination of two qualitatively different mechanisms of over-acceleration: (i) Over-acceleration through lane changing to a faster lane, (ii) over-acceleration occurring in car-following without lane changing. Based on this generic feature a new three-phase CA traffic flow model is developed. This CA model explains the set of the fundamental empirical features of traffic breakdown in real heterogeneous traffic flow consisting of passenger vehicles and trucks. The model simulates also quantitative traffic pattern characteristics as measured in real heterogeneous flow.     

考虑车与车互联通讯技术的交通流跟驰模型

基于Newell跟驰模型,建立考虑车与车互联(vehicle-to-vehicle,V2V)通讯技术的单车道跟驰模型.根据V2V技术的特征,引入参数α以表征驾驶员在收到V2V技术所提供的实时交通信息后的提前反应程度.根据线性稳定分析方法,得到V2V跟驰模型的中性稳定条件.通过计算机的模拟,研究V2V技术对交通流运行的影响,分析小扰动下V2V跟驰模型对参数变化的敏感性,研究不同α取值下交通流密度波及迟滞回环的变化.研究发现:1)与全速度差跟驰模型相比,在引入V2V后,交通流在加速起步、减速刹车及遇到突发事件时,车辆运行的安全性和舒适性均得到不同程度的提升;2)V2V跟驰模型对参数α及T的变化较为敏感,且在交通流较为拥堵时,V2V技术的引入可以提升交通流的平均速度;3)参数α的增大、T的减小可以有效提升V2V跟驰模型在不同交通环境下的运行稳定性.由于可以实时地获取交通流运行的状态并针对性地改变车辆自身的运行,V2V交通流跟驰模型提升了交通流运行的稳定性.     

Heterogeneous traffic flow modeling with drivers' timid and aggressive characteristics

The driver's characteristics(e.g., timid and aggressive) has been proven to greatly affect the traffic flow performance,whereas the underlying assumption in most of the existing studies is that all drivers are homogeneous. In the real traffic environment, the drivers are distinct due to a variety of factors such as personality characteristics. To better reflect the reality,we introduce the penetration rate to describe the degree of drivers' heterogeneity(i.e., timid and aggressive), and proceed to propose a generalized heterogeneous car-following model with different driver's characteristics. Through the linear stability analysis, the stability conditions of the proposed heterogeneous traffic flow model are obtained based on the perturbation method. The impacts of the penetration rate of drivers with low intensity, the average value and standard deviation of intensity parameters characterizing two types of drivers on the stability of traffic flow are analyzed by simulation. Results show that higher penetration of aggressive drivers contributes to traffic flow stability. The average value has a great impact on the stability of traffic flow, whereas the impact of the standard deviation is trivial.     

驾驶员预估效应下车流能耗演化机理研究

考虑实际交通中驾驶员预估效应对车辆跟驰行为的影响, 提出了一个改进跟驰模型. 采用线性稳定性理论获得了该模型的线性稳定性判据. 运用数值仿真的方法, 系统研究了驾驶员预估效应下车流的整体平均能耗和单车能耗的演化机理. 研究结果表明, 驾驶员预估效应能显著提高车流稳定性, 且随着驾驶员预估时长的增加, 车流的整体平均能量损耗和单车能量损耗将逐渐降低.     

Modeling and analysis of car-following behavior considering backward-looking effect

The car-following behavior can be influenced by its driver’s backward-looking effect.Especially in traffic congestion,if vehicles adjust the headway by considering backward-looking effect,the stability of traffic flow can be enhanced.A model of car-following behavior considering backward-looking effect was built using visual information as a stimulus.The critical stability conditions were derived by linear and nonlinear stability analyses.The results of parameter sensitivity analysis indicate that the stability of traffic flow was enhanced by considering the backward-looking effect.The spatiotemporal evolution of traffic flow of different truck ratios and varying degrees of backward-looking effect was determined by numerical simulation.This study lays a foundation for exploring the complex feature of car-following behavior and making the intelligent network vehicles control rules more consistent with human driver habits.