交通流瓶颈效应的运动学描述.

采用一个推广的LWR模型研究交通瓶颈效应.通过求解流通量间断的Riemann问题,得到关于模型解结构的解析结果,由此导出了描述在瓶颈上游车流的排队现象及其队列长度和高度(密度)的一个典型解,并能够构造模型方程的一种δ-映射算法.更有意义的是,表明了通过采用三角形基本图,这一运动学模型能够描述时走时停波.通过数值模拟,验证丁数值结果与解析结果的一致性,从而支撑了文章的理论结果.     

各向异性交通流动力学模型的波动特性

对姜锐等人最近提出的一种新的交通流动力学模型的波动特性进行了分析.该模型中,不存在大于宏观车流速度的特征速度,从而满足交通流各向异性的要求.线性稳定性分析发现,新模型在一定条件下保持稳定,文中给出了稳定条件判定标准.分析指出,这一模型的波由一阶波和二阶波两种层次构成,既允许交通光滑波的存在,也充许交通激波的存在,但是其激波条件与其它相关模型有明显区别.正是这种区别,使得新模型在处理某些交通问题(如车辆倒退现象)上更加符合实际车流情况.     

一种确定信号交叉口拥堵的概率统计预警模型

研究信号交叉口的运行效率及车辆服务水平对于城市交通建设与发展具有重要的意义。本文针对信号交叉口各入口方向上车流的运行特性,从概率统计的角度研究各入口方向上通过信号交叉口车流的统计模型,并在此基础上得到了一种用于定时信号交叉口拥堵的概率统计实时交通状况预警判断模型。     

Ad Hoc网络马氏模型路由维护的性能分析

Ad Hoc网络可以用许多数学模型来描述.本文以DSR协议为基础,把每条链边的长度看作是一个生灭过程,建立了马氏模型.在此模型中,我们考虑了空间可重用和请求分组带有跳限的情形.基于马氏模型,本文引入了链边Υ-时有效的概念,推导了链边有效的概率,得出了路由有效的条件概率和路由的平均恢复次数.     

一个供需不确定性下的多模式非线性互补分配模型

交通需求和供给不确定是现实交通网络中常见的现象.提出一个供需不确定条件下非对称影响的多模式交通分配模型.提出的模型以条件概率的形式生成不同供需变动情景下的交通流模式,构成一个非线性互补模型,模型中获得的交通流模式,可以用来估计交通网络失效的损失指标和交通网络可靠性衡量指标,不同风险态度的出行者可借助指标来选择可靠性高的路段或避开效率损失高路段.使用一个算例来表明提出模型的适用性和有效性.结果表明,提出的模型能更好的反映不确定性条件下的多种模式交通流演变情况,反映不同的供需变动情景以及不同的出行模式对均衡流模式的影响,进而提高交通网络中用户的出行可靠度.     

一种确定加速车道长度的概率统计模型

加速车道有利于次要道路上的车流平顺地汇入高速公路的车流 ,加速车道长度的确定是加速车道设计的核心内容。本文针对加速车道车流的运行特性 ,从概率统计角度研究了加速车道上车辆汇入高速公路车流的概率 ,并在此基础上得到了一种用于确定加速车道长度的实用模型     

混凝土材料的粘塑性损伤本构模型

基于不可逆热力学,引入运动硬化、等向硬化和损伤内变量,构造了相应的自由能函数和流动势函数,推导出了混凝土材料的粘塑性损伤本构模型．数值模拟的结果表明,该模型能够避开屈服面和破坏准则的基本假设来描述混凝土材料的以下特性:压缩载荷作用下的体积膨胀现象;应变率敏感性;峰值后由损伤和破坏引起的应力软化和刚度退化现象A·D2由于此模型避开了根据各种变形阶段选择与其相应的本构模型的繁琐计算,因此更便于纳入复杂工况下应力分析有限元程序中．     

多等级交通流LWR模型中的非线性波描述与WENO数值逼近

证明了交通流多等级LWR(Lighthill-Whitham-Richards)模型的双曲性质,并根据交通流的特征给出关于其非线性波的描述,主要包括车流通过激波和稀疏波时密度和速度的单调性变化．由于方程组没有显式的特征分解,所以引入具有高分辨和高精度的WENO(weighted essentially non~oscillatory)格式作数值模拟,得到与理论描述完全一致的数值结果．     

具有内生寿命模型中的多重增长路径与分歧

本文将S-形生存概率函数引入Chakraborty内生寿命模型,研究模型的动态特征.文中证明描述模型的离散动力系统至少存在一个非零平衡,至多存在三个非零平衡点,并在给的参数下出现鞍结点分歧.在出现三个非零平衡点的情形下,较高人均资本处的平衡处的生存概率较高,而较低人均资本处的生存概率较低,这两个平衡点是稳定的;处于这两个平衡点之间的平衡点是不稳定的.此时,模型描述的经济具有多重增长路径,并出现"贫困陷阱".     

时间序列非线性门限模型——模拟非平稳动态数据的一种有效工具

<正> 时间序列非线性门限模型,是1977年由英国曼彻斯特大学理工学院数学系汤家豪博士首次提出来的.这一模型的基本思想是利用逐段线性化手段来处理非线性系统.由于门限的控制作用,保证了递推的稳定性,并对于非线性随机系统引入了极限环概念.更有实用价值的是,门限模型可以有效地描述非线性振动现象,可以解释自然界各种类型的稳定循环,且能反映出类似跳共振的突变.本文着重介绍门限模型的形式、建立模型的方法和应用实例.对于有关的理论,读者如有兴趣,可以参阅文献[2].     

Modeling the asymmetry in traffic flow (a): Microscopic approach

The asymmetric characteristic of a vehicle’s ability in deceleration and acceleration, as well as its impact to micro- and macroscopic traffic flow has caused increased attention from both theoretical and practical sides. However, how to realistically model this property remains a challenge to researchers. This paper is one of the two studies on this topic, which is focused on the modeling at the microscopic level from the investigation of car-following behavior. The second part of the study [H. Liu, H. Xu, H. Gong, Modeling the asymmetry in traffic flow (b): macroscopic approach, Appl. Math. Model. (submitted for publication)] is focused on the modeling of this asymmetric property from the macroscopic scale. In this paper, we first present an asymmetric full velocity difference car-following approach, in which a higher order differential equation is developed to take into account the effect of asymmetric acceleration and deceleration in car-following. Then, efforts are dedicated to calibrate the sensitivity coefficients from field data to complete the theoretical approach. Using the data recorded from the main lane traffic and ramp traffic of a segment of the US101 freeway, the two sensitivity coefficients have been successfully calibrated from both congested and light traffic environments. The experimental study reveals that in the studied traffic flow, the intensity of positive velocity difference term is significantly higher than the negative velocity difference term, which agrees well with the results from studies on vehicle mechanics.     

Analytical studies on the instabilities of heterogeneous intelligent traffic flow

It has been widely reported in literature that a small perturbation in traffic flow such as a sudden deceleration of a vehicle could lead to the formation of traffic jams without a clear bottleneck. These traffic jams are usually related to instabilities in traffic flow. The applications of intelligent traffic systems are a potential solution to reduce the amplitude or to eliminate the formation of such traffic instabilities. A lot of research has been conducted to theoretically study the effect of intelligent vehicles, for example adaptive cruise control vehicles, using either computer simulation or analytical method. However, most current analytical research has only applied to single class traffic flow. To this end, the main topic of this paper is to perform a linear stability analysis to find the stability threshold of heterogeneous traffic flow using microscopic models, particularly the effect of intelligent vehicles on heterogeneous (or multi-class) traffic flow instabilities. The analytical results will show how intelligent vehicle percentages affect the stability of multi-class traffic flow.     

A dynamical systems approach based on averaging to model the macroscopic flow of freeway traffic

The flow of traffic exhibits distinct characteristics under different conditions, reflecting the congestion during peak hours and relatively free motion during off-peak hours. This requires one to use different mathematical equations to describe the diverse traffic characteristics. Thus, the flow of traffic is best described by a hybrid system, namely different governing equations for the different regimes of response, and it is such a hybrid approach that is investigated in this paper. Existing models for the flow of traffic treat traffic as a continuum or employ techniques similar to those used in the kinetic theory of gases, neither of these approaches gainfully exploit the hybrid nature of the problem. Spurious two-way propagation of disturbances that are physically unacceptable are predicted by continuum models for the flow of traffic. The number of vehicles in a typical section of the highway does not justify its being modeled as a continuum. It is also important to recognize that the basic premises of kinetic theory are not appropriate for the flow of traffic (see [S. Darbha, K.R. Rajagopal, Limit of a collection of dynamical systems: an application to modeling the flow of traffic, Mathematical Models and Methods in Applied Sciences 12 (10) (2002) 1381–1399] for a rationale for the same). A model for the flow of traffic that does not treat traffic as a continuum or use notions from kinetic theory is developed here and corroborated with real-time data collected on US 183 in Austin, Texas. Predictions based on the hybrid system model seem to agree reasonably well with the data collected on US 183.     

A new cellular automaton model for traffic flow

Establishment of effective traffic models to reveal fundamental traffic characteristics is an essential requirement in the design, planning and operation of transportation systems. In 1992 Nagel and Schreckenberg presented a cellular automaton model describing traffic flow of N cars on a single lane and applied it in the famous project TRANSIMS on transportation simulation. In this paper, the author proposes a new model for the same problem and gives a comparison of simulation results with the former ones. The comparison shows that the new model works better under the condition of high traffic density.     

Instability of cooperative adaptive cruise control traffic flow: A macroscopic approach

This paper proposes a macroscopic model to describe the operations of cooperative adaptive cruise control (CACC) traffic flow, which is an extension of adaptive cruise control (ACC) traffic flow. In CACC traffic flow a vehicle can exchange information with many preceding vehicles through wireless communication. Due to such communication the CACC vehicle can follow its leader at a closer distance than the ACC vehicle. The stability diagrams are constructed from the developed model based on the linear and nonlinear stability method for a certain model parameter set. It is found analytically that CACC vehicles enhance the stabilization of traffic flow with respect to both small and large perturbations compared to ACC vehicles. Numerical simulation is carried out to support our analytical findings. Based on the nonlinear stability analysis, we will show analytically and numerically that the CACC system better improves the dynamic equilibrium capacity over the ACC system. We have argued that in parallel to microscopic models for CACC traffic flow, the newly developed macroscopic will provide a complete insight into the dynamics of intelligent traffic flow.     

Stability analysis of dynamic collaboration model with control signals on two lanes

In this paper, the influence of control signals on the stability of two-lane traffic flow is mainly studied by applying control theory with lane changing behaviors. We present the two-lane dynamic collaboration model with lateral friction and the expressions of feedback control signals. What is more, utilizing the delayed feedback control theory to the two-lane dynamic collaboration model with control signals, we investigate the stability of traffic flow theoretically and the stability conditions for both lanes are derived with finding that the forward and lateral feedback signals can improve the stability of traffic flow while the backward feedback signals cannot achieve it. Besides, direct simulations are conducted to verify the results of theoretical analysis, which shows that the feedback signals have a significant effect on the running state of two vehicle groups, and the results are same with the theoretical analysis.     

主路多车道无信号交叉口混合交通流的通行能力

Highway capacity is defined as maximum volume of traffic flow through the particular highway section under given traffic conditions,road conditions and so on.Highway construction and management is judged by capacity standard.The reasonable scale and time of highway construction,rational network structure and optimal management mode of highway network can be determined by analyzing the fitness between capacity and traffic volume.All over the world,highway capacity is studied to different extent in different country. Based on the gap acceptance theory,the mixed traffic flow composed of two representative vehicle types heavy and light vehicles is analyzed with probability theory.Capacity model of the minor mixed traffic flows crossing m major lanes,on which the traffic flows fix in with M3 distributed headway,on the unsignalized intersection is set up,and it is an extension of minor lane capacity theory for one vehicle-type and one major-lane traffic flow.     

基于粒子群的模糊神经网络的短时交通流量组合预测

为了进一步提高短时交通流量预测的精度,提出了一种粒子群算法的模糊神经网络组合预测模型,模糊神经网络融合了神经网络的学习机制和模糊系统的语言推理能力等优点,弥补各自不足,将自回归求和滑动平均(ARIMA)和灰色Verhulst模型进行初步预测,并将两种初步预测的结果作为模糊神经网络的输入,构建基于改进模神经网络的组合预测模型,在此基础上进行训练和预测,其中模糊神经网络的相关参数由改进粒子群来优化,利用本方法来对南京市汉中路短时交通流量进行预测,结论表明:方法充分发挥了单一模型的优势,比单一的预测模型更加精确,是短时交通流量预测的一个有效方法。     

基于交通流的多模糊时间窗车辆路径优化

研究了基于交通流的多模糊时间窗车辆路径问题,考虑了实际中不断变化的交通流以及客户具有多个模糊时间窗的情况,以最小化配送总成本和最大化客户满意度为目标,构建基于交通流的多模糊时间窗车辆路径模型。根据伊藤算法的基本原理,设计了求解该模型的改进伊藤算法,结合仿真算例进行了模拟计算,并与蚁群算法的计算结果进行了对比分析,结果表明,利用改进伊藤算法求解基于交通流的多模糊时间窗车辆路径问题,迭代次数小,效率更高,能够在较短的时间内收敛到全局最优解,可以有效的求解多模糊时间窗车辆路径问题。     

Reconstructing freeway travel times with a simplified network flow model alternating the adopted fundamental diagram

The present study summarises the travel time reconstruction performance of a network flow model by explicitly analysing the adopted fundamental diagram relation under congested and un-congested traffic patterns. The incorporated network flow model uses a discrete meso-simulation approach in which the anisotropic property of traffic flow and the uniform acceleration of vehicle packets are explicitly considered. The flow performances on link-route dynamics have been derived by reasonably alternating the adopted two-phase, i.e., congested and un-congested, fundamental relation of traffic flow. The linear speed–density relation with the creeping speed assumption is substituted with the triangular flow–density relation in order to investigate the performance of the network flow model in varying flow patterns. Applying the anisotropic mesoscopic model, the measure of travel time is obtained as a link performance from a simplified dynamic network loading process. Travel time reconstruction performance of the network flow model is sought considering the actual measures that are obtained by a probe vehicle, in addition to reconstructions by a macroscopic network flow model. The main improvements on travel time reconstruction process are encountered in terms of the computation load within the explicit analyses by the alternation of adopted two-phase fundamental diagram. Although the accuracies of the flow model with the adoption of two different fundamental diagrams are hard to differentiate, the computational burden of the simulation process by the triangular fundamental diagram is found to be considerably different.