混合交通流时间序列的去趋势波动分析

应用去趋势波动分析法研究交通流时间序列的复杂性,探讨了混合交通流时间序列演变行为的标度指数.根据标度指数的变化特征,进而揭示交通流时间序列所具有的长程相关性和短程相关性.通过分析发现,存在一密度ρ,当ρ₁<ρ<ρ₂时,交通流时间序列具有长程相关性;而当ρ<ρ₁或ρ>ρ₂时,交通流时间序列具有短程相关性,即密度的变化影响着标度指数的变化.另外分析了在不同慢车比率条件下时间序列的标度指数,发现慢车比率的变化 关键词： 混合交通流 去趋势波动分析 时间序列 长程相关     

交通流突变点的无标度特征分析

交通流时间序列在不同时间尺度上具有不同的波动特征.为了分析交通流的突变特征,以一段实际的交通流量序列为研究对象进行实证研究.采用小波变换的方法求得交通流在不同尺度上的突变点,按照小波函数过零点数目将交通流的尺度划分为若干层次,并分析了交通流突变的层次性.计算表明:以突变点数目为测度时,在一定的尺度范围内,交通流在突变层次上的突变点数目满足自相似性特征.因此,交通流的突变在不同尺度上具有无标度性.     

Self-similarity of electrostatic fluctuations in a linear magnetised plasma system

In this Letter the long-range time correlations present in the fluctuation data in presence of electrostatic instability in a magnetised dc discharge plasma is presented. The electrostatic instability is generated due to the effect of crossed electric and magnetic field (E×B flow) and has intermediate frequency ranging from 50 to 100 MHz. Hurst exponent, the self-similarity parameter is calculated with the help of different statistical methods suggested by many researchers to determine the long-range time correlation present in fluctuation dynamics in the plasma column. The fluctuation in the ion saturation current is measured by a Langmuir probe for the study and the measurement is done both radially and axially in the plasma system. Estimated results clearly expose the self-similar character of the fluctuations with self-similarity parameters having values from 0.65 to 0.90 through the presence of long-range time correlation.     

短时交通流复杂动力学特性分析及预测

为揭示短时交通流的内在动态特性,利用非线性方法对交通流混沌特性进行识别,为短时交通流的预测提供基础.基于混沌理论对交通流时间序列进行相空间重构,利用C-C算法计算时间延迟和嵌入维数,采用Grassberger-Procaccia算法计算吸引子关联维数,通过改进小数据量法计算最大Lyapunov指数来判别交通流时间序列的混沌特性.针对局域自适应预测方法在交通流多步预测中预测器系数无法调节的问题,提出了交通流多步自适应预测方法.通过实测数据计算,结果表明:2,4和5 min三种统计尺度的交通流时间序列均具有混沌特性;改进的小数据量法能够准确地计算出最大Lyapunov指数;构建的交通流多步自适应预测模型能够有效地预测交通流量的变化.为智能交通系统诱导和控制提供了依据.     

混合状态下城市快速路交通流短时预测

建立交通流短时预测状态空间模型, 研究混合状态下城市快速路交通流短时预测. 结合城市快速路自由流状态、拥挤流状态和阻塞流状态下交通流参数的时间和空间分布特性, 基于交通流守恒方程和速度动态模型, 借鉴偏微分方程组求解时空离散的思想, 建立三种状态下交通流短时预测模型; 同时考虑进出口匝道、车道数变更以及道路坡度等因素的影响, 将交通流短时预测模型转化为交通流短时预测状态空间模型, 实现混合状态下交通流短时预测. 研究表明, 该方法能够实现混合状态下道路网内的交通流短时预测, 预测精度可达90.23%. 相同条件下, 经典自回归滑动平均模型的预测精度仅为81%. 关键词： 交通流短时预测 自由流状态 拥挤流状态 阻塞流状态     

Numerical study of urban traffic flow with dedicated bus lane and intermittent bus lane

Based on the cellular automaton traffic flow model and the concept of public transport priority, a two-lane traffic model with an intermittent bus lane is proposed and the properties of urban traffic flow are studied. The cases of traffic with a dedicated bus lane (DBL), an intermittent bus lane (IBL) and an ordinary two-lane traffic are simulated, and comparisons in the form of the fundamental diagrams and the velocity-density profiles are made between them. It is shown that the DBL has the advantage of freeing buses from traffic interference and also has the disadvantage of disrupting traffic, the IBL is more efficient in improving the bus flow than ordinary two-lane traffic and maintaining the car flow at a higher level at the same time than the DBL, while the ordinary two-lane traffic suppresses public transportation and is not advantageous in easing urban traffic congestion. Also it is indicated that the DBL is only appropriate for low traffic flow in a two-lane traffic system, and this limitation can be partly overcome by opening the bus lane to general traffic intermittently when the bus lane is not in use by buses.     

Fluctuations in airport arrival and departure traffic: A network analysis

Air traffic is a typical complex system,in which movements of traffic components(pilots,controllers,equipment,and environment),especially airport arrival and departure traffic,form complicated spatial and temporal dynamics.The fluctuations of airport arrival and departure traffic are studied from the point of view of networks as the special correlation between different airports.Our collected flow volume data on the time-dependent activity of US airport arrival and departure traffic indicate that the coupling between the average flux and the fluctuation of an individual airport obeys a certain scaling law with a wide variety of scaling exponents between 1/2 and 1.These scaling phenomena can explain the interaction between the airport internal dynamics(e.g.queuing at airports,a ground delay program and following flying traffic) and a change in the external(network-wide) traffic demand(e.g.an increase in traffic during peak hours every day),allowing us to further understand the mechanisms governing the collective behaviour of the transportation system.We separate internal dynamics from external fluctuations using a scaling law which is helpful for us to systematically determine the origin of fluctuations in airport arrival and departure traffic,uncovering the collective dynamics.Hot spot features are observed in airport traffic data as the dynamical inhomogeneity in the fluxes of individual airports.The intrinsic characteristics of airport arrival and departure traffic under severe weather is discussed as well.     

结合可视图的多状态交通流时间序列特性分析

交通流时间序列的研究主要采用数据挖掘和机器学习的方法,这些"黑箱"挖掘方法很难直观反映序列特性.为增强交通流时间序列及其特征分析的可视化性,结合可视图理论来构建交通流时间序列的关联网络,从复杂网络角度实现交通流时间序列的特性分析.在网络构建的过程中,考虑到不同交通状态下交通流表征具有的差异性,首先利用交通流参量的相关性对交通流状态进行分类,然后构建不同交通状态下的时间序列复杂网络,并对这些网络的特征属性给出统计分析,如度分布、聚类系数、网络直径、模块化等.研究表明,可视图法可为交通流时间序列映射到网络提供有效途径,并且不同状态下交通流时间序列构建的复杂网络的模块化、聚类系数和度分布等统计特征呈现一定的变化规律,为交通流运行态势的研究提供了可视化的分析角度.     

An improved cellular automaton model considering the effect of traffic lights and driving behaviour

This paper proposes an improved cellular automaton model to describe the urban traffic flow with the consideration of traffic light and driving behaviour effects. Based on the model,the characteristics of the urban traffic flow on a single-lane road are investigated under three different control strategies,i.e.,the synchronized,the green wave and the random strategies. The fundamental diagrams and time-space patterns of the traffic flows are provided for these strategies respectively. It finds that the dynamical transition to the congested flow appears when the vehicle density is higher than a critical level. The saturated flow is less dependent on the cycle time and the strategies of the traffic light control,while the critical vehicle density varies with the cycle time and the strategies. Simulated results indicate that the green wave strategy is proven to be the most effective one among the above three control strategies.     

基于能力区域的交通状态预测方法

交通状态预测是交通流诱导和交通信息发布系统的重要依据.本文提出了一种基于能力区域的城市快速路交通状态预测方法,该方法通过构建神经网络分类器的能力区域,根据样本数据与交通状态类簇之间的空间距离,预测道路交通状态等级.神经网络分类器的能力区域能够有效融合时间、空间等多种特征,并且不需要考虑各特征之间的相关性,具有很强的适应性.实验结果表明,与经典的预测方法相比,其预测误差明显降低,均等系数增大,基于能力区域的方法预测交通状态具有较高的准确性.     

基于多重分形去趋势波动分析法的交通流多重分形无标度区间自动识别方法

无标度区间是时间序列在统计意义上存在分形自相似性的尺度范围,是交通流多重分形特征研究中的重要组成部分.为解决交通流多重分形研究中多重分形去趋势波动分析法(multi-fractal detrended fluctuation analysis,MF-DFA)缺乏有效识别无标度区间方法的问题,本文在分析算法过程中交通流波动函数对数曲线突变点性质的基础上,结合传统无标度区间识别方法的构建思想,建立基于MF-DFA算法的无标度区间自动识别方法.以北京市二环快速路外环方向的部分道路为例开展实例研究,通过与传统无标度区间识别方法的结果对比,验证新方法的有效性.研究结果表明:本文方法能自动识别交通流多重分形无标度区间,且稳定性好;案例研究可知交通流短时间内波动较小、自相似性较强,随着研究时间段变长、交通流波动逐渐变大,自相似性逐渐消失,进一步解释了交通流无标度区间的有限性.     

A prediction method for road traffic noise generated from arbitrary non-poisson type traffic flow based on an approach equivalent to that for a standard poisson type traffic flow

In order to establish a prediction method for road traffic noise generated from actual traffic flow of an arbitrary non-Poisson type, a new approach equivalent to that for an idealized Poisson type traffic flow is proposed for practical use. This prediction method is able to treat any kind of road traffic noise fluctuation generated from actual non-Poisson type traffic flow, once information has been obtained on the wave form of the level time pattern observed when one vehicle passes directly in front of an observation point. The validity of the proposed prediction method has been experimentally confirmed by applying it to actually observed road traffic noise data.     

基于模糊神经网络的短时交通流预测方法研究

为满足交通控制和诱导系统的实时性需求,减少交通拥挤状况,降低交通事故突发频率,需要对短时交通流进行预测。当前的短时交通流预测方法是采用K-近邻的非参数回归对其进行预测,预测过程中没有将预测模型中关键因素对交通流的影响进行详细的说明,导致预测结果不准确,存在短时交通流预测误差较大的问题。为此,提出一种基于模糊神经网络的短时交通流预测方法。该方法首先以历史短时交通流数据样本序列为基础,将提取的关联维数作为短时交通流的混沌特征量,然后以该特征量为依据,对短时交通流数据进行聚类,使相同的短时交通流聚合类样本比不同的交通流聚合类样本更为贴近,采用高斯过程回归对短时交通流预测模型进行建设,建设过程中利用差分方法对短时交通流预测序列进行平稳化操作之后,对短时交通流预测模型进行训练,将GPR模型引入至短时交通流预测过程中,得到交通流预测方差估计值,并确定交通流预测值置信区间,由此实现短时交通流的预测。由此实现短时交通流的预测。实验结果证明,所提方法可以准确地预测交通运输系统的实时状况,为车辆行驶的最佳路线进行了有效引导,减少了自然影响方面和人为因素对短时交通流预测结果的干扰,为交通部门对交通路况的控制管理提供了依据。     

The effect of stochastic accelerating and delay probability with the velocity and the gap between vehicles on traffic flow

This paper proposes a new combined cellular automaton (CA) model considering the driver behavior of stochastic acceleration and delay with the velocity of the preceding vehicle and the gap between the successive vehicles based on the WWH model and the noise-first NaSch model. It introduces the delay probability varying with the gap, adds the anticipation headway and increases the acceleration with a certain probability. Through these simulations, not only can the metastable state and start--stop wave be obtained but also the synchronized flow which the wide moving jam results in. Moreover, the effect of stochastic acceleration and delay on traffic flow is discussed by analyzing the correlation of traffic data. This indicates that synchronized flow easily emerges in the critical area between free flow and synchronized flow when acceleration and delay are synchronized or their probability is close to 0.5.     

计算机网络的长程相关特性

针对一种计算机网络模型，利用节点排队长度累计量的均方涨落函数，研究了网络节点在时间上的长程相关特性.结果表明，随着负载的增加，网络节点数据包排队长度在时间上由自由流状态的不相关或短程相关逐渐演变为临界和拥塞时的长程相关，关联范围逐渐增大，长程关联特性开始显现.在自由流状态时，节点的不相关或短程相关，并且有一致的数值为0.5的幂指数这一典型特征.而在临界状态时，节点数据包排队长度长程相关，有大于0.5的幂指数为特征.并且随网络规模的增大，节点间的群体作用逐渐显著，幂指数呈下降趋势. 关键词： 计算机网络 相变 长程相关 幂律     

道路交通的流体物理模型与粒子仿真方法

针对受多种因素影响的复杂道路交通系统问题,基于颗粒动力学理论,结合传统的Lighthill-WhithamRichards物理模型,建立道路交通系统的流体物理模型,采用无网格粒子与网格相结合的方法进行数值仿真,并应用于典型道路交通问题的求解.在新模型中,将车辆比拟为硬颗粒,车辆的跟车比拟为颗粒间的碰撞相互作用,已知道路情况对驾驶员操作车辆的影响比拟为流-粒两相系统中的外部流体驱动力作用,不同车道间车辆的影响比拟为颗粒间的黏性作用,从而在颗粒动力学理论的基础上,推导建立了道路交通系统拟流体模型;引入光滑离散颗粒流体动力学(SDPH)对车辆系统模型进行离散,建立"SDPH车辆"与真实车辆之间的一一对应关系,再结合有限体积方法,对道路交通构建的双流体模型进行求解,建立求解交通流体物理模型的新型仿真方法.最后,采用所建立的模型和方法对车辆汇入以及机非混合对交通系统的影响过程进行了数值仿真,所得结果与实测值符合较好,表明新的模型和方法有效性好、可靠性高,为道路交通问题的解决提供了一条全新的途径.     

宏观交通流模型的能耗研究

本文在几种典型的宏观交通流模型的基础上,导出能量耗散的计算公式,宏观交通流模型能耗不同于元胞自动机交通模型,其能耗不仅考虑车流速度减少,而且还要计及通过路段的车流通量引起的能耗.通过对满足黎曼初始条件的道路能耗和道路交通瓶颈处能耗的计算和理论分析,表明交通拥堵处,能量耗散比较高,而且能量耗散的变化也能反映交通拥堵产生及消散的情况.     

智能交通系统的元胞自动机交通流模型

在Nagel-Schreckenberg(NS)模型的基础上，提出一种可应用智能交通系统（ITS）信息的新的交通流元胞自动机模型. 其中考虑了有效间距及刹车灯的作用，并引入了可变安全间距的新概念. 数值模拟表明：对于这种改进的ITS元胞自动机模型，道路交通量有了显著提高，体现了智能交通的优越性——有效地扩大交通流量，减少阻塞生成. 当考虑快车和慢车的混合交通流时，发现即使少量的慢车也会导致交通流量大幅度下降，说明了严格实施快慢道行驶的必要性. 关键词： 交通流 智能交通系统（ITS） 元胞自动机模型 刹车灯 可变安全间距     

城市道路U形转向交通流特性模拟分析

以NaSch模型为基础建立设置U形转向的路段交通流模型,对其特性进行模拟分析. 结果表明,U形转向路口对交通流影响显著,会导致在较小进车概率时发生自由流状态到拥挤状态的相变,相应的临界流量也随之降低. 设置双U形转向系统的相变、临界流量等交通流特性与单转向系统具有明显差异,其系统效率较高. 在实际交通规划与管理时应避免设置单转向系统,以减小U形转向的负面影响. 关键词： 交通流 元胞自动机 U形转向 相变     

Dynamic noise modeling at roundabouts

Modeling spatial and temporal noise variations at roundabouts is a tedious task. Indeed, noise levels are strongly influenced by the complex vehicle interactions taking place at the entries. An accurate modeling of the merging process and its impact on vehicle kinematics, waiting time at the yield signs and queue length dynamics is therefore required. Analytical noise prediction models disregard those impacts since they are based on average flow demand patterns and pre-defined kinematic profiles. The only way to capture all traffic dynamics impacts on noise levels is to combine a traffic simulation tool with noise emission laws and a sound propagation model. Yet, such existing dynamic noise prediction packages fail in representing vehicle interactions when the roundabout is congested and are difficult to calibrate due to their numerous parameters. A new traffic simulation tool, specifically developed for roundabouts, is therefore proposed in this paper. It has few easy-to-calibrate parameters and can be readily combined with noise emission and propagation laws. The obtained noise package is able to produce relevant dynamic noise contour maps which can support noise emission assessment of local traffic management policies. Results are validated against empirical data collected on a French suburban roundabout on two different peak periods.