交通流双车跟驰模型与数值仿真

基于全速度差(FVD)模型，考虑双前车信息的影响，提出了交通流双车跟驰模型.通过线性稳定性分析，得到了改进模型的稳定性条件. 与FVD模型对比研究表明，改进模型的稳定区域有明显增加.数值模拟结果表明，改进模型通过调节次近邻前车信息，可以避免FVD模型中因为反应系数较小时出现负速度的缺陷.同时也表明次近邻前车对交通流存在不可忽视的影响. 关键词： 交通流 双车跟驰模型 模拟     

多前车速度差的车辆跟驰模型的稳定性与孤波

通过线性稳定性分析,得到了多前车速度差模型的稳定性条件, 并发现通过调节多前车信息,使交通流的稳定区域明显扩大. 通过约化摄动方法 研究了该模型的非线性动力学特性:在稳定流区域,得到了描述密度波的Burgers方程;在交 通流的不稳定区域内,在临界点附近获得了描述车头间距的修正的Korteweg-de Vries (modified Korteweg-de Vries, mKdV)方程; 在亚稳态区域内,在中性稳定曲线附近获得了描述车头间距 的KdV方程. Burgers的孤波解、mKdV方程的扭结-反扭结波解及KdV方程的 孤波解描述了交通流堵塞现象.     

最相邻后车综合信息对交通流不稳定性的影响分析

基于抑制交通流不稳定性所需的条件,分析司机后视获得的最相邻后车综合信息对交通流不稳定性的影响. 在司机关注前车信息概率大于关注后车信息概率与司机敏感系数大于0的现实条件下,解析分析以及仿真分析得到了以下结论:1)最相邻后车车头距信息减小了交通流的不稳定性,且关注概率越大,减小作用越大;跟驰车与最相邻后车的速度差信息增加了交通流的不稳定性,且关注概率越大,增加作用越大. 2)最相邻后车综合信息对交通流的不稳定性的减小作用大于增加作用,即最相邻后车综合信息减小了交通流的不稳定性. 3)司机距离差敏感系数越大,最相邻后车综合信息对交通流的不稳定性减小作用越大. 4)司机速度差敏感系数越大,最相邻后车综合信息对交通流的不稳定性增加作用越大. 关键词： 交通堵塞 交通流不稳定性 最相邻后车综合信息 跟驰模型     

弯道交通流跟驰建模与稳定性分析

为发现弯道道路条件下交通流的演化特性及稳定条件,在全速度差最优模型的基础上,研究了弯道情况下的交通流跟驰模型表达式,并以状态空间法和控制系统的稳定性判据对其进行了稳定性分析,得到弯道情况下交通流的稳定条件,最后进行了数值模拟,验证了模型稳定条件的正确性.研究结果表明在相同的初始交通流密度情况下,弯道道路随着道路弧度的增大,交通流稳定性逐渐降低.     

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     

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.     

考虑最邻近前车综合信息的反馈控制跟驰模型

拥堵控制中, 通过车辆运行状态感知与控制的交互融合, 实现对车辆有效控制的过程, 具有信息物理融合系统的典型特征. 本文基于Konishi等的研究工作, 从交通信息系统与交通物理系统融合的角度, 进一步考虑优化速度差和安全间距对车流的影响, 在耦合映射跟驰模型中, 提出了一种考虑最邻近前车综合信息的交通拥堵反馈控制方案. 运用反馈控制理论, 给出了头车速度发生变化时交通流保持稳定的条件, 并与前人工作进行了比较. 理论分析与数值模拟结果一致表明, 耦合映射跟驰模型在本文提出的控制方案下能更有效地抑制交通拥堵. 关键词： 交通流 交通拥堵控制 耦合映射跟驰模型 信息物理融合系统     

考虑延迟概率因素对混合车辆敏感驾驶交通流模型的研究

在交通流NS模型的基础上，考虑混合车辆之间存在的速度差异，不同车辆的驾驶员在对前车的敏感驾驶随机减速行为过程中其延迟概率是不同的，从而提出了一维多速混合车辆敏感驾驶元胞自动机交通流模型. 通过计算机数值模拟得到了混合车辆在不同参数下的 基本图.结果表明，与NS模型、SDNS模型相比，道路交通流量有较大的提高，而且还展现出 了亚稳态、相分离等复杂的实际交通行为现象.结合实际情况，对混合交通的特性进行了分析和讨论. 关键词： 元胞自动机 混合交通流模型 亚稳态 相分离 计算机模 拟     

基于智能交通系统的耦合映射跟驰模型和交通拥堵控制

基于智能交通诱导信息，提出一种改进的耦合映射跟驰模型，用于描述单车道的交通流动力学特性及其拥堵控制.利用反馈控制理论，给出了在头车速度发生变化时交通流保持稳定的条件.分析结果表明，考虑前方更多车辆的信息对交通流有致稳作用，亦即稳定性条件明显减弱.数值模拟证实了理论分析的正确性，通过与他人相关工作的比较得知，考虑智能交通诱导信息能够更有效地抑制交通拥堵. 关键词： 交通流 智能交通系统 耦合映射跟驰模型 交通拥堵控制     

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。     

Multiple car-following model of traffic flow and numerical simulation

On the basis of the full velocity difference (FVD) model,an improved multiple car-following (MCF) model is proposed by taking into account multiple information inputs from preceding vehicles.The linear stability condition of the model is obtained by using the linear stability theory.Through nonlinear analysis,a modified Korteweg-de Vries equation is constructed and solved.The traffic jam can thus be described by the kink-antikink soliton solution for the mKdV equation.The improvement of this new model over the previous ones lies in the fact that it not only theoretically retains many strong points of the previous ones,but also performs more realistically than others in the dynamical evolution of congestion.Furthermore,numerical simulation of traffic dynamics shows that the proposed model can avoid the disadvantage of negative velocity that occurs at small sensitivity coefficients λ in the FVD model by adjusting the information on the multiple leading vehicles.No collision occurs and no unrealistic deceleration appears in the improved model.     

An asymmetric full velocity difference car-following model

This paper presents a car-following model that considers the asymmetric characteristic of the velocity differences of the vehicles in a traffic stream. The problems of the prevalent general force (GF) model and the full velocity difference (FVD) model were solved. Furthermore, the optimal velocity (OV) model, the GF model, and the FVD model are proved to be the special cases of the proposed asymmetric full velocity difference (AFVD) model. The mathematical model is presented, followed by simulation analysis which demonstrates the properties of the AFVD model.     

Three-lane changing behaviour simulation using a modified optimal velocity model

In real urban traffic, roadways are usually multilane and are divided into fast, medium and slow lanes according to different velocity restrictions. Microscopic modelling of single lane has been studied widely using discrete cellular automata and continuous optimal velocity models. In this paper, we extend the continuous single-lane models (OV model and FVD model) to simulate the lane-changing behaviour on an urban roadway that consists of three lanes. Considering headway difference, velocity difference, safety distance, and the probability of lane-changing intention, a comprehensive lane-changing rule set is constructed. We analyse the fundamental diagram and reveal the “faster-is-slower” effect in urban traffic induced by lane-changing behaviour. We also investigate the effect of lane-changing behaviour on the distribution of vehicles, velocity, flow and headway. Asymmetrical phenomenon with symmetrical rules on urban roadway and density inversion on the slow lane were also found. The simulation results indicate that lane-changing behaviour is not advisable on crowded urban roadway. It is hoped that information from this study may be useful for traffic control and individual moving strategy on urban roadway.     

Visual angle model for car-following theory

The vast majority of car-following models are lack of the consideration of human drivers’ characteristics. Based on the fact that each driver of a following vehicle perceives closing-in or shying-away a leading vehicle in front of him/her, primarily due to changes in the apparent size of the leading vehicle, we improved the full velocity difference (FVD) model and presented a visual angle car-following model. This model is in view of the stimulus-response framework and uses the visual angle and the change rate of the visual angle as stimulus. Results from linear analysis showed that the neutral stability line is asymmetry and the width of the leading vehicle has a great impact on the stability of traffic flow. Numerical simulations obtained the same results as theoretical analysis clearly such as density wave, shrinking hysteresis, asymmetry and wide scattering. Thus, the introducing of the visual angle can explain some complex nature of traffic flow and contribute to the design of more realistic car-following 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 in 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.     

The effect of ACC vehicles to mixed traffic flow consisting of manual and ACC vehicles

This paper studies the effect of adaptive cruise control （ACC） system on traffic flow by using simulations. The multiple headway and velocity difference （MHVD） model is used to depict the motion of ACC vehicles, and the simulation results are compared with the optimal velocity （OV） model which is used to depict the motion of manual vehicles. Compared the cases between the manual and the ACC vehicle flow, the fundamental diagram can be classified into four regions： I, II, III, IV. In low and high density the flux of the two models is the same; in region II the free flow region of the MHVD model is enlarged, and the flux of the MHVD model is larger than that of the OV model; in region III serious jams occur in the OV model while the ACC system suppresses the jams in the MHVD model and the traffic flow is in order, but the flux of the OV model is larger than that of the MHVD model. Similar phenomena also appeared in mixed traffic flow which consists of manual and ACC vehicles. The results indicate that ACC vehicles have significant effect on traffic flow. The improvement induced by ACC vehicles decreases with the increasing proportion of ACC vehicles.     

Nonlinear analysis of an improved continuum model considering mean-field velocity difference

Based on the velocity gradient model, an extended continuum model with consideration of the mean-field velocity difference is proposed in this paper. By using the linear stability theory, the linear stability criterion of the new model is gained, which proved that mean-field velocity difference has significant influence on stability of traffic flow. The KdV–Burgers equation is derived by using non-linear analysis method and the evolution of density wave near the neutral stability line is explored. Numerical simulations are carried out how mean-field velocity difference affect the stability of traffic flow, and energy consumption is also studied for this new macro model. At the same time, complicated traffic phenomena such as local cluster effects, shock waves and rarefaction waves can be reproduced in the new model by numerical simulation. Numerical results are consistent with the theoretical analysis, which indicates that the mean-field velocity difference not only suppresses traffic jam, but also depresses energy consumption.     

The stability analysis of the full velocity and acceleration velocity model

The stability analysis is one of the important problems in the traffic flow theory, since the congestion phenomena can be regarded as the instability and the phase transition of a dynamical system. Theoretically, we analyze the stable conditions of the full velocity and acceleration difference model (FVADM), which is proposed by introducing the acceleration difference term based on the previous car-following models (the optimal velocity model and the full velocity difference model, OVM and FVDM). By numerical simulations, it is found that when the traffic flow is unstable, the traffic jam in the FVADM is weaker than that in the FVDM. Also it is observed that the spreading speed of the jam is slower in the FVADM than that in the FVDM and the fluctuations of vehicles in the FVADM are smaller than those in the FVDM. Therefore, the acceleration difference term has strong effects on traffic dynamics and plays an important role in stabilizing the traffic flow.