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     

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     

高速跟驰交通流动力学模型研究

为研究道路交通中的高速跟驰物理现象,针对高速跟驰车辆特点,综合考虑了驾驶员换道决策行为以及随机慢化等因素,结合前景理论等方法,提出了一种用于模拟道路交通流中高速跟驰物理现象的动力学模型(简称HCCA模型).通过计算机数值模拟,研究了高速跟驰交通流物理现象演化机理及高速跟驰特性.结果表明:与对称的双车道元胞自动机动力学模型相比,本文建立的HCCA动力学模型能够再现道路高速跟驰物理现象,并得到了道路小间距高速跟驰率超过7%的结果与实测结果相符合,最后模拟得到了丰富的交通物理现象,再现了自由流、同步流及运动阻塞等复杂交通物理现象.     

考虑前后车效应的反馈控制跟驰模型

本文中,在优化速度模型的基础上,提出一个计及跟随车与当前车车头间距的跟驰模型.从控制论角度出发,对模型进行稳定性分析,得到了模型的稳定性条件.同时,在新模型中引入了反馈控制信息,考虑当前车与前后方车辆之间的速度差.对模型进行线性分析后得到小扰动不会导致交通堵塞的条件.在开放边界条件下,对两个模型进行数值模拟,结果表明在控制信号下,车辆速度波动明显减小,拥堵现象得到有效缓解.从而证实反馈控制信号对缓解交通拥堵的重要作用.     

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     

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.     

智能交通环境下多信息反馈效应的跟驰模型研究综述

智能交通环境下,驾驶员可实时获取前方多辆车行驶状态信息,并根据反馈信息合理调整自身车辆运行状态,以期实现前后多车协同行驶的目标。本文简要回顾了跟驰模型近70年的发展历程,重点聚焦理论驱动跟驰模型,系统梳理了智能交通环境下多信息反馈效应跟驰模型的相关研究,给出了不同信息反馈作用下各模型的具体表征及其特性,归纳出多信息反馈效应跟驰模型动力学方程的一般形式。最后展望了该模型未来的发展趋势,为进一步完善跟驰理论及模型提供有益的参考。     

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     

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     

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.     

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.     

A control method applied to mixed traffic flow for the coupled-map car-following model

In light of previous work [Phys. Rev. E 60 4000 （1999）], a modified coupled-map car-following model is proposed by considering the headways of two successive vehicles in front of a considered vehicle described by the optimal velocity function. The non-jam conditions are given on the basis of control theory. Through simulation, we find that our model can exhibit a better effect as p = 0.65, which is a parameter in the optimal velocity function. The control scheme, which was proposed by Zhao and Gao, is introduced into the modified model and the feedback gain range is determined. In addition, a modified control method is applied to a mixed traffic system that consists of two types of vehicle. The range of gains is also obtained by theoretical analysis. Comparisons between our method and that of Zhao and Gao are carried out, and the corresponding numerical simulation results demonstrate that the temporal behavior of traffic flow obtained using our method is better than that proposed by Zhao and Gao in mixed traffic systems.     

A control method for congested traffic in the coupled map car-following model

Based on the pioneer work of Konishi et al, a new control method is presented to suppress the traffic congestion in the coupled map (CM) car-following model under an open boundary. A control signal concluding the velocity differences of the two vehicles in front is put forward. The condition under which the traffic jam can be contained is analyzed. The results are compared with that presented by Konishi et al [Phys. Rev. 1999 E 60 4000--4007]. The simulation results show that the temporal behavior obtained by our method is better than that by the Konishi's et al. method, although both the methods could suppress the traffic jam. The simulation results are consistent with the theoretical analysis.     

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.     

Simulating train movement in railway traffic using a car-following model

Based on a car-following model, in this paper, we propose a new traffic model for simulating train movement in railway traffic. In the proposed model, some realistic characteristics of train movement are considered, such as the distance headway and the safety stopping distance. Using the proposed traffic model, we analyse the space-time diagram of traffic flow, the trajectory of train movement, etc. Simulation results demonstrate that the proposed model can be successfully used for simulating the train movement. Some complex phenomena can be reproduced, such as the complex acceleration and deceleration of trains and the propagation of train delay.     

Analysis of the stability and density waves for traffic flow

In this paper, the optimal velocity model of traffic is extended to take into account the relative velocity. The stability and density waves for traffic flow are investigated analytically with the perturbation method. The stability criterion is derived by the linear stability analysis. It is shown that the triangular shock wave, soliton wave and kink wave appear respectively in our model for density waves in the three regions: stable, metastable and unstable regions. These correspond to the solutions of the Burgers equation, Korteweg－de Vries equation and modified Korteweg－de Vries equation. The analytical results are confirmed to be in good agreement with those of numerical simulation. All the results indicate that the interaction of a car with relative velocity can affect the stability of the traffic flow and raise critical density.     

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.