A Stochastic LWR Model with Consideration of the Driver's Individual Property

In this paper,we develop a stochastic LWR model based on the influences of the driver's individual property on his/her perceived density and speed deviation.The numerical results show that the driver's individual property has great effects on traffic flow only when the initial density is moderate,i.e.,at this time,oscillating traffic flow will occur and the oscillating phenomena in the traffic system consisting of the conservative and aggressive drivers is more serious than that in the traffic system consisting of the conservative (aggressive) drivers.     

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.     

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.     

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.     

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.     

Towards the bi-directional cellular automaton model with perception ranges

The traditional cellular automaton (CA) model assumes that drivers only receive information from the preceding vehicles, e.g. the brake light information. However, in reality, drivers not only perceive information from downstream but can also get upstream information, e.g. the honk stimulation. The CA model involving traffic information from downstream and upstream is called the bi-directional CA model here. Meanwhile, with the introduction of Connected Vehicle Technologies, the perception range of drivers is expected to significantly increase which can lead to more informed driving behavior. Such an impact cannot be easily modeled by traditional one-directional CA models. In this study, the perception ranges of both the brake light effect and honk stimulation are introduced into the bi-directional CA model. Fundamental diagrams and spatial–temporal diagrams are then analyzed and two methods, i.e. the traffic flow interruption effect and microscopic analysis of time series data, are utilized to distinguish the synchronized traffic flow. Further numerical results illustrate that the perception range and slow-to-start sensitivity threshold are two important factors to reproduce the synchronized flow, and consideration of the honk information and the larger perception range both benefit the stability of traffic flow, which implies the potential significance of the application of Connected Vehicle Technologies.     

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.     

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.     

考虑驾驶员特性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SDNaSch模型的基础上,建立了一种考虑驾驶员特性的元胞自动机交通流模型(Driver-SDNaSch模型).该模型将驾驶员分为激进型、保守型和中立型三类,根据其不同的驾驶特性制定了各自的演化规则,并以此对其进行状态更新;同时考虑了前车速度为0的情况,引入安全减速概率.通过计算机对Driver-SDNaSch模型进行模拟,给出了由三类驾驶员按不同比例组成的混合交通流的速度-密度图和流量-密度图,并对此类混合交通流的特性进行了分析和讨论.与NaSch模型和SDNaSch模 关键词： 交通流 元胞自动机 驾驶员特性 计算机数值模拟     

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.     

The phase diagram and the pathway of phase transitions for traffic flow in a circular one-lane roadway

This paper demonstrates that patient driving habits lead to homogenous congested flow while impatient driving habits lead to wide-moving jam flow in the high density region based on the numerical simulation of the intelligent driver model proposed by M.Treiber [M. Treiber, A.Hennecke, D. Helbing, Phys. Rev. E 62 (2) (2000), 1805-1824]. In a circular one lane traffic system which includes homogeneous drivers, we obtain the stable condition of homogenous flow and the phase diagram of traffic flow based on the linearization analysis. The phase diagram shows three possible pathways of phase transition along with the increase of global density: from the homogenous free flow to the homogenous congested flow directly, from the homogenous free flow to the synchronized flow then to the homogenous congested flow, or from the homogenous free flow to synchronized flow then to the wide-moving jam flow. The paper also analyzes the traffic flow including heterogenous drivers, and the results indicate that homogenous congested flow will lose its stability when the proportion of impatient drivers reaches a critical value and some new kinds of traffic flow emerge: wide-moving jam flow or a mixture of synchronized flow and wide-moving jam flow.     

考虑动态车间距的一维元胞自动机交通流模型

基于NaSch元胞自动机交通流模型, 考虑司机复杂的性格特征和驾驶行为差异, 引入相邻车辆的动态车间距, 提出了一个改进的单车道元胞自动机交通流模型. 通过数值模拟得到了流量-密度关系, 在中高密度区域呈现出一种弥散分布的状态而非惟一确定的关系, 再现了交通系统中的自由流、同步流及宽幅运动阻塞, 表明道路上即使没有交通瓶颈也会出现同步流和拥挤交通, 同时揭示了在同步流中存在的车辆高速跟驰现象, 高速跟驰率与交通实测结果较为符合.     

Influence of lateral discomfort on the stability of traffic flow based on visual angle car-following model

Due to the poor road markings and irregular driving behaviors, not every vehicle is positioned in the center of the lane. The deviation from the center can cause discomfort to drivers in the neighboring lane, which is referred to as lateral discomfort (or lateral friction). Such lateral discomfort can be incorporated into the driver stimulus–response framework by considering the visual angle and its changing rate from the psychological viewpoint. In this study, a two-lane visual angle based car-following model is proposed and its stability condition is obtained through linear stability theory. Further derivations indicate that the neutral stability line of the model is asymmetry and four factors including the vehicle width and length, the lateral separation and the sensitivity regarding the changing rate of visual angle have large impacts on the stability of traffic flow. Numerical simulations further verify these theoretical results, and demonstrate that the behaviors of diverging, merging and lane changing can break the original steady state and cause traffic fluctuations. However, these fluctuations may be alleviated to some extent by reducing the lateral discomfort.     

Bifurcation analysis of visual angle model with anticipated time and stabilizing driving behavior

In the light of the visual angle model (VAM), an improved car-following model considering driver's visual angle, anticipated time and stabilizing driving behavior is proposed so as to investigate how the driver's behavior factors affect the stability of the traffic flow. Based on the model, linear stability analysis is performed together with bifurcation analysis, whose corresponding stability condition is highly fit to the results of the linear analysis. Furthermore, the time-dependent Ginzburg-Landau (TDGL) equation and the modified Korteweg-de Vries (mKdV) equation are derived by nonlinear analysis, and we obtain the relationship of the two equations through the comparison. Finally, parameter calibration and numerical simulation are conducted to verify the validity of the theoretical analysis, whose results are highly consistent with the theoretical analysis.     

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.     

A new car-following model with the consideration of the driver's forecast effect

In this Letter, we develop a new car-following model with the consideration of the driver's forecast effect (DFE). The analytical and numerical results show that the stability of traffic flow will gradually be enhanced with the increase of the forecast effect coefficient and the forecast time.     

Intelligent driving in traffic systems with partial lane discipline

It is a most common notion in traffic theory that driving in lanes and keeping lane changes to a minimum leads to smooth and laminar traffic flow, and hence to increased traffic capacity. On the other hand, there exist persistent vehicular traffic systems that are characterised by habitual disregarding of lane markings, and partial or complete loss of laminar traffic flow. Here, we explore the stability of such systems through a microscopic traffic flow model, where the degree of lane-discipline is taken as a variable, represented by the fraction of drivers that disregard lane markings completely. The results show that lane-free traffic may win over completely ordered traffic at high densities, and that partially ordered traffic leads to the poorest overall flow, while not considering the crash probability. Partial order in a lane-free system is similar to partial disorder in a lane-disciplined system in that both lead to decreased traffic capacity. This could explain the reason why standard enforcement methods, which rely on continuous increase of order, often fail to incur order to lane-free traffic systems. The results also provide an insight into the cooperative phenomena in open systems with self-driven particles.     

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。     

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.     

Density waves in a traffic flow model with reaction-time delay

Density waves are investigated analytically and numerically in the optimal velocity model with reaction-time delay of drivers. The stability condition of this model is obtained by using the linear stability theory. The results show that the decrease of reaction-time delay of drivers leads to the stabilization of traffic flow. The Burgers, Korteweg-de Vries (KdV) and modified Korteweg-de Vries (mKdV) equations are derived to describe the density waves in the stable, metastable and unstable regions respectively. The triangular shock waves, soliton waves and kink-antikink waves appearing respectively in the three distinct regions are derived to describe the traffic jams. The numerical simulations are given.