混有协同自适应巡航控制车辆的异质交通流稳定性解析与基本图模型

针对传统车辆和协同自适应巡航控制(cooperative adaptive cruise control,CACC)车辆构成的异质交通流,研究其稳定性与基本图模型.应用实车测试验证的CACC模型和智能驾驶员模型(intelligent driver model)分别作为CACC车辆和传统车辆的跟驰模型,建立异质流稳定性解析框架,研究不同平衡态速度、不同CACC车辆比例时的异质流稳定性.推导异质流基本图模型,并进行数值仿真实验.研究结果表明,在传统车辆稳定的速度范围,异质流处于稳定状态.在传统车辆不稳定的速度范围,CACC车辆比例增加以及平衡态速度远离9.6—18.6 m/s速度范围,均能够改善异质流的不稳定性.通行能力随着CACC车辆比例的增加而提高.此外,CACC模型的期望车间时距越大,异质流稳定域越大,但通行能力降低.因此,恒定车间时距CACC控制策略下的期望车间时距取值应权衡异质流稳定域和通行能力两个方面的影响.     

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.     

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.     

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.     

Simulation study on ramp inflow for hybrid autonomous driving

In view of the complexity of the ramp traffic system on the expressway and the diversity of hybrid automatic driving, the safety distance of vehicles and the corresponding car following model are analyzed based on the combination of driver’s personality characteristics and the characteristics of different automatic driving levels of the vehicle–road​ coordination system, and the risk model is established to screen the potentially dangerous vehicles in the ramp merging process. Based on game theory, this paper constructs a ramp coordination and merging control model suitable for hybrid automatic driving. The model takes the safety benefit and efficiency benefit as the objective function, predicts the benefit value under different strategies and makes the optimal strategy under the current conditions. The proposed model is verified by the joint simulation of Python and sumo. the simulation results show that the average number of combined vehicles is 1.91 times higher, the combined position is 50.11% earlier and the average driving time is 28.35% less than that without control strategy and there is obvious advantage when the density is high compared with vehicles without control strategy.     

Analysis of Phase Transition in Traffic Flow based on a New Model of Driving Decision

Different driving decisions will cause different processes of phase transition in traffic flow.To reveal the inner mechanism, this paper built a new cellular automaton (CA) model,based on the driving decision (DD). In the DD model, a driver's decision is divided intothree stages: decision-making, action, and result. The acceleration is taken as a decisionvariable and three core factors, i.e. distance between adjacent vehicles, their own velocity,and the preceding vehicle's velocity, are considered. Simulation results show that the DDmodel can simulate the synchronized flow effectively and describe the phase transitionin traffic flow well. Further analyses illustrate that various density will cause the phasetransition and the random probability will impact the process. Compared with the traditional NaSch model, the DD model considered the preceding vehicle's velocity, the deceleration limitation, and a safe
distance, so it can depict closer to the driver preferences on pursuing safety, stability and fuel-saving and has strong theoreticalinnovation for future studies.     

Analysis of stability and density waves of traffic flow model in an ITS environment

By introducing relative velocities of arbitrary number of cars ahead into the full velocity difference models (FVDM), we present a forward looking relative velocity model (FLRVM) of cooperative driving control system. To our knowledge, the model is an improvement over the similar extension in the forward looking optimal velocity models (FLOVM), because it is more reasonable and realistic in implement of incorporating intelligent transportation system in traffic. Then the stability criterion is investigated by the linear stability analysis with finding that new consideration theoretically lead to the improvement of the stability of traffic flow, and the validity of our theoretical analysis is confirmed by direct simulations. In addition, nonlinear analysis of the model shows that the three waves: triangular shock wave, soliton wave and kink-antikink wave appear respectively in stable, metastable and unstable regions. These correspond to the solutions of the Burgers equation, Korteweg-de Vries (KdV) equation and modified Korteweg-de Vries (mKdV) equation.     

A quantum mechanics-based approach to model incident-induced dynamic driver behavior

A better understanding of the psychological factors influencing drivers, and the resulting driving behavior responding to incident-induced lane traffic phenomena while passing by an incident site is vital to the improvement of road safety. This paper presents a microscopic driver behavior model to explain the dynamics of the instantaneous driver decision process under lane-blocking incidents on adjacent lanes. The proposed conceptual framework decomposes the corresponding driver decision process into three sequential phases: (1) initial stimulus, (2) glancing-around car-following, and (3) incident-induced driving behavior. The theorem of quantum mechanics in optical flows is applied in the first phase to explain the motion-related perceptual phenomena while vehicles approach the incident site in adjacent lanes, followed by the incorporation of the effect of quantum optical flows in modeling the induced glancing-around car-following behavior in the second phase. Then, an incident-induced driving behavior model is formulated to reproduce the dynamics of driver behavior conducted in the process of passing by an incident site in the adjacent lanes. Numerical results of model tests using video-based incident data indicate the validity of the proposed traffic behavior model in analyzing the incident-induced lane traffic phenomena. It is also expected that such a proposed quantum-mechanics based methodology can throw more light if applied to driver psychology and response in anomalous traffic environments in order to improve road safety.     

考虑驾驶心理的城市双车道交通流元胞自动机模型

采用双车道元胞自动机模型,分析了考虑驾驶心理的城市道路交通流特性.针对驾驶员在城市道路行驶时在换道与减速制动方面的不同心理,分别引入了反映驾驶心理的选择换道概率P_s与安全参数λ.通过计算机模拟,给出了不同选择换道概率与安全参数条件下的车辆速度、密度与流量间的关系,并分析了不同驾驶心理对于交通系统的影响.研究发现:选择换道概率对交通流的速度影响并不明显,但选择换道概率的增大会导致速度的方差增大而降低行车安全;而安全参数的增大可以获得更快的平均车速和更大的交通 关键词： 元胞自动机 驾驶心理 选择换道概率 计算机模拟     

A new car-following model with consideration of the traffic interruption probability

In this paper, we present a new car-following model by taking into account the effects of the traffic interruption probability on the car-following behaviour of the following vehicle. The stability condition of the model is obtained by using the linear stability theory. The modified Korteweg--de Vries (KdV) equation is constructed and solved, and three types of traffic flows in the headway sensitivity space---stable, metastable, and unstable---are classified. Both the analytical and simulation results show that the traffic interruption probability indeed has an influence on driving behaviour, and the consideration of traffic interruption probability in the car-following model could stabilize traffic flow.     

A refined cellular automaton model to rectify impractical vehicular movement behavior

When implementing cellular automata (CA) into a traffic simulation, one common defect yet to be rectified is the abrupt deceleration when vehicles encounter stationary obstacles or traffic jams. To be more in line with real world vehicular movement, this paper proposes a piecewise-linear movement to replace the conventional particle-hopping movement adopted in most previous CA models. Upon this adjustment and coupled with refined cell system, a new CA model is developed using the rationale of Forbes’ et al. car-following concept. The proposed CA model is validated on a two-lane freeway mainline context. It shows that this model can fix the unrealistic deceleration behaviors, and thus can reflect genuine driver behavior in the real world. The model is also capable of revealing Kerner’s three-phase traffic patterns and phase transitions among them. Furthermore, the proposed CA model is applied to simulate a highway work zone wherein traffic efficiency (maximum flow rates) and safety (speed deviations) impacted by various control schemes are tested.     

驾驶员属性对信号灯路口交通流的影响研究

采用元胞自动机模型研究信号灯路口的交通流特性,系统地分析了与性别、驾驶经验、性格等驾驶员属性相关的驾驶行为对交通流的影响.数值模拟发现,技术生疏或紧张驾驶、急躁行驶等驾驶行为更易引发自由流到阻塞流的相变,是路口通行低效率及事故隐患的重要原因,信号周期是影响流量与个人通行时间公平的主要因素.     

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.     

提高道路交通系统的驾驶安全

道路交通系统是一个复杂的系统，其中包含了人的直接参与。在该系统中，人的因素起了重要的作用。本文中，在道路系统路面的某一点设计了一种类型控制信号，该点被称为信号点。在控制信号的作用下，当车辆经过信号点的时候，车辆需要降低速度。其目的在于能够通过控制信号控制交通流的状态，使其由无序变为有序，从而提高道路系统的交通安全。应用双车道的确定性NaSch模型进行仿真模拟，结果表明不仅交通流的状态能够由无序变为有序，而且交通流的状态是安全的。     

A new continuum model with driver's continuous sensory memory and preceding vehicle's taillight

Car taillights are ubiquitous during the deceleration process in real traffic, while drivers have a memory for historical information. The collective effect may greatly affect driving behavior and traffic flow performance. In this paper, we propose a continuum model with the driver's memory time and the preceding vehicle's taillight. To better reflect reality, the continuous driving process is also considered. To this end, we first develop a unique version of a car-following model. By converting micro variables into macro variables with a macro conversion method, the micro car-following model is transformed into a new continuum model. Based on a linear stability analysis, the stability conditions of the new continuum model are obtained. We proceed to deduce the modified KdV-Burgers equation of the model in a nonlinear stability analysis, where the solution can be used to describe the propagation and evolution characteristics of the density wave near the neutral stability curve. The results show that memory time has a negative impact on the stability of traffic flow, whereas the provision of the preceding vehicle's taillight contributes to mitigating traffic congestion and reducing energy consumption.     

Analyses of a heterogeneous lattice hydrodynamic model with low and high-sensitivity vehicles

Basic lattice model is extended to study the heterogeneous traffic by considering the optimal current difference effect on a unidirectional single lane highway. Heterogeneous traffic consisting of low- and high-sensitivity vehicles is modeled and their impact on stability of mixed traffic flow has been examined through linear stability analysis. The stability of flow is investigated in five distinct regions of the neutral stability diagram corresponding to the amount of higher sensitivity vehicles present on road. In order to investigate the propagating behavior of density waves non linear analysis is performed and near the critical point, the kink antikink soliton is obtained by driving mKdV equation. The effect of fraction parameter corresponding to high sensitivity vehicles is investigated and the results indicates that the stability rise up due to the fraction parameter. The theoretical findings are verified via direct numerical simulation.     

考虑驾驶方式改变的一维元胞自动机交通流模型

在一维元胞自动机交通流WWH模型和SDNS模型的基础上,建立了考虑驾驶方式改变的元胞自动机模型（Change-CA模型）.具体描述为驾驶员可根据交通环境选择不同的驾驶方式在道路上驾车行驶,以各自的演化规则进行状态更新,同时定义了驾驶方式更新原则.通过计算机数值模拟,发现驾驶方式可变时,模型模拟得到的混合交通流流量较大;保守型驾驶方式对交通流变化的影响随改变概率增大而减少.并且在演化过程中,驾驶方式改变频率的变化趋势与改变概率、安全概率密切相关.与NS模型和SDNS模型相比,Change-CA模型减少了车流 关键词： 交通流 元胞自动机 驾驶方式 计算机数值模拟     

Stabilization strategy of a car-following model with multiple time delays of the drivers

An extended car-following model with multiple delays is constructed to describe driver's driving behavior. Through stability analysis, the stability condition of this uncontrolled model is given. To dampen the negative impact of the driver's multiple delays (i.e., stability condition is not satisfied), a novel control strategy is proposed to assist the driver in adjusting vehicle operation. The control strategy consists of two parts:the design of control term as well as the design of the parameters in the term. Bifurcation analysis is performed to illustrate the necessity of the design of parameters in control terms. In the course of the design of parameters in the control term, we improve the definite integral stability method to reduce the iterations by incorporating the characteristics of bifurcation, which can determine the appropriate parameters in the control terms more quickly. Finally, in the case study, we validate the control strategy by utilizing measured data and configuring scenario, which is closer to the actual traffic. The results of validation show that the control strategy can effectively stabilize the unstable traffic flow caused by driver's delays.     

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.