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.     

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 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.     

A new car-following model with two delays

A new car-following model is proposed by taking into account two different time delays in sensing headway and velocity. The effect of time delays on the stability analysis is studied. The theoretical and numerical results show that traffic jams are suppressed efficiently when the difference between two time delays decreases and those can be described by the solution of the modified Korteweg–de Vries (mKdV) equation. Traffic flow is more stable with two delays in headway and velocity than in the case with only one delay in headway. The impact of local small disturbance to the system is also studied.     

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.     

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.     

Continuum approach to car-following models

A continuum version of the car-following Bando model is developed using a series expansion of the headway in terms of the density. This continuum model obeys the same stability criterion as its discrete counterpart. To compare both models we show that traveling wave solutions of the Bando model are very similar to those of the continuum model in the limit of small changes of headway. As the change of headway across the wave increases the solutions gradually diverge. Our transformation relating headway to density enables predictions of the global impact and characteristics of any car-following model using the analogous continuum model. In contrast, we show that the conventional continuum models which account for effects of pressure and dispersion predict behavior which is distinct from the global behavior of discrete models.     

Stabilisation analysis of multiple car-following model in traffic flow

An improved multiple car-following model is proposed by considering the arbitrary number of preceding cars, which includes both the headway and the velocity difference of multiple preceding cars. The stability condition of the extended model is obtained by using the linear stability theory. The modified Korteweg--de Vries equation is derived to describe the traffic behaviour near the critical point by applying the nonlinear analysis. Traffic flow can be also divided into three regions: stable, metastable and unstable regions. Numerical simulation is accordance with the analytical result for the model. And numerical simulation shows that the stabilisation of traffic is increasing by considering the information of more leading cars and there is unavoidable effect on traffic flow from the multiple leading cars' information.     

Analysis of car-following model considering driver’s physical delay in sensing headway

An extended car-following model is proposed by taking into account the delay of the driver’s response in sensing headway. The stability condition of this model is obtained by using the linear stability theory. The results show that the stability region decreases when the driver’s physical delay in sensing headway increases. The KdV equation and mKdV equation near the neutral stability line and the critical point are respectively derived by applying the reductive perturbation method. The traffic jams could be thus described by soliton solution and kink-antikink soliton solution for the KdV equation and mKdV equation respectively. The numerical results in the form of the space-time evolution of headway show that the stabilization effect is weakened when the driver’s physical delay increases. It confirms the fact that the delay of driver’s response in sensing headway plays an important role in jamming transition, and the numerical results are in good agreement with the theoretical analysis.     

Nonliner Analysis of a Synthesized Optimal Velocity Model for Traffic Flow

We analyze a new car-following model described by a differential-difference equation with a synthesized optimal velocity function (SOVF), which depends on the front interactions between every two adjacent vehicles instead of the weighted average headway. The model is analyzed with the use of the linear stability theory and nonlinear analysis method. The stability and neutral stability condition are obtained. We also derive the modified KdV (Korteweg-de Vries) equation and the kink-antikink soliton solution near the critical point. A simulation is conducted with integrating the differential-difference equation by the Euler scheme. The results of the numerical simulation verify the validity of the new model.     

A new car-following model with the consideration of anticipation optimal velocity

In this paper, a new anticipation optimal velocity model (AOVM) is proposed by considering anticipation effect on the basis of the full velocity difference model (FVDM) for car-following theory on single lane. The linear stability condition is derived from linear stability analysis. Starting and braking process is investigated for the car motion under a traffic signal, which shows that the results accord with empirical traffic values. Especially AOVM can avoid the disadvantage of the unrealistically high deceleration appearing in FVDM. Furthermore, numerical simulation shows that AOVM might avoid the disadvantage of negative velocity and headway that occur at small sensitivity coefficients in the FVDM since the anticipation effect is taken into account in AOVM, which means that collision disappears with the consideration of an appropriate anticipation parameter.     

Nonlinear density wave and energy consumption investigation of traffic flow on a curved road

A new car-following model is proposed based on the full velocity difference model(FVDM) taking the influence of the friction coefficient and the road curvature into account. Through the control theory, the stability conditions are obtained,and by using nonlinear analysis, the time-dependent Ginzburg-Landau(TDGL) equation and the modified Korteweg-de Vries(mKdV) equation are derived. Furthermore, the connection between TDGL and mKdV equations is also given. The numerical simulation is consistent with the theoretical analysis. The evolution of a traffic jam and the corresponding energy consumption are explored. The numerical results show that the control scheme is effective not only to suppress the traffic jam but also to reduce the energy consumption.     

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.     

Time-dependent Ginzburg-Landau equation in a car-following model considering the driver’s physical delay

In this paper, an extended car-following model considering the delay of the driver’s response in sensing headway is proposed to describe the traffic jam. It is shown that the stability region decreases when the driver’s physical delay in sensing headway increases. The phase transition among the freely moving phase, the coexisting phase, and the uniformly congested phase occurs below the critical point. By applying the reductive perturbation method, we get the time-dependent Ginzburg-Landau (TDGL) equation from the car-following model to describe the transition and critical phenomenon in traffic flow. We show the connection between the TDGL equation and the mKdV equation describing the traffic jam.     

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.     

A novel lattice model integrating the cooperative deviation of density and optimal flux under V2X environment

A novel lattice hydrodynamic model is proposed by integrating the cooperative deviation of density and optimal flux under vehicle to X (V2X) environment. According to the theoretical analysis, the stability conditions and the mKdV equations affected by the cooperative deviation of traffic information are explored. And the density wave, hysteresis loop and energy consumption of the traffic flow have been investigated via numerical simulation. The results indicate that the cooperative deviation of density and optimal flux can effectively alleviate the traffic congestion. More importantly, our new consideration can reduce fuel consumption and exhaust emission under the V2X environment.     

Numerical simulation of soliton and kink density waves in traffic flow with periodic boundaries

The soliton and kink–antikink density waves are simulated with periodic boundaries, by adding perturbation in the initial condition on single-lane road based on a car-following model. They are reproduced in the form of the space–time evolution of headway, both of which propagate backwards. It is found that the solitons appear only near the neutral stability line regardless of the boundary conditions, and they exhibit upward form when the initial headway is smaller than the safety distance, otherwise they exhibit downward form. Comparison is made between the numerical and analytical results about the amplitude of kink–antikink wave, and the underlying mechanism is analyzed. Besides, it is indicated that the maximal current of traffic flow increases with decreasing safety distance. The numerical simulation shows a good agreement with the analytical results.     

考虑双速度差效应的耦合映射跟驰模型

基于Konishi等的研究工作,提出了涉及前方两辆车车头间距的优化速度函数的耦合映射跟驰模型. 采用反馈控制方法,研究了耦合映射跟驰模型中的交通拥堵控制. 利用反馈控制理论,给出了头车速度发生变化时交通流保持稳定的条件,并与Konishi等得到的结果进行了比较. 数值模拟结果表明,所提出的模型在经典的反馈控制方法下描述的交通拥堵现象得到了有效抑制. 关键词： 交通流 耦合映射跟驰模型 优化速度函数 反馈控制     

一种新交通流跟驰模型的相变研究

本文通过数值仿真的方法研究了优化速度跟驰模型(OVM)描述由一辆预先给定速度曲线的头车运动而引起的车辆队列加速过程的性能，结果显示该模型在描述这一过程时具有某种缺陷。据此文章提出了一个新的模型，能够改进OVM的这一不足。对改进模型的线性稳定性分析表明：若稳定性条件不能满足，则随着初始均衡交通流车头间距的变化将会产生交通流的相变现象。     

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