Optimal traffic networks topology: A complex networks perspective

We investigate and analyse an optimal traffic network structure for resisting traffic congestion with different volumes of traffic. For this aim, we introduce a cost function and user-equilibrium assignment (UE) which ensures the flow balance on traffic systems. Our finding is that an optimal network is strongly dependent on the total system flow. And the random network is most desirable when the system flow is small. But for the larger volume of traffic, the network with power-law degree distribution is the optimal one. Further study indicates, for scale-free networks, that the degree distribution exponent has large effects on the congestion of traffic network. Therefore, the volume of traffic and characteristic of network determine the optimal network structure so as to minimize the side-effect produced by traffic congestion.     

Congestion analysis of traffic networks with direction-dependant heterogeneity

Traffic flow directionality and network weight asymmetry are widespread notions in traffic networks. This paper investigates the influence of direction-dependant heterogeneity on traffic congestion. To capture the effect of the link directionality and link weight asymmetry, the heterogeneity indexes of complex networks and the traffic flow model are introduced. The numerical results show that the critical value of heterogeneity determines congestion transition processes. The congestion degree increases with heterogeneity when the network heterogeneity is at a subcritical region. A network is more tolerant of congestion if the heterogeneity of the network is smaller or larger than the critical value. Furthermore, when heterogeneity reaches the critical value, the average number of accumulated vehicles arrives at the maximum and the traffic flow is under a serious congestion state. A significant improvement on the tolerance to congestion of traffic networks can be made if the network heterogeneity is controlled within a reasonable range.     

Study on the Reduced Traffic Congestion Method Based on Dynamic Guidance Information

This paper studies how to generate the reasonable information of travelers' decision in real network. This problem is very complex because the travelers' decision is constrained by different human behavior. The network conditions can be predicted by using the advanced dynamic OD(Origin-Destination, OD) estimation techniques. Based on the improved mesoscopic traffic model, the predictable dynamic traffic guidance information can be obtained accurately.A consistency algorithm is designed to investigate the travelers' decision by simulating the dynamic response to guidance information. The simulation results show that the proposed method can provide the best guidance information. Further,a case study is conducted to verify the theoretical results and to draw managerial insights into the potential of dynamic guidance strategy in improving traffic performance.     

Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory: A brief review

It is explained why the set of the fundamental empirical features of traffic breakdown (a transition from free flow to congested traffic) should be the empirical basis for any traffic and transportation theory that can be reliably used for control and optimization in traffic networks. It is shown that the generally accepted fundamentals and methodologies of the traffic and transportation theory are not consistent with the set of the fundamental empirical features of traffic breakdown at a highway bottleneck. To these fundamentals and methodologies of the traffic and transportation theory belong (i) Lighthill–Whitham–Richards (LWR) theory, (ii) the General Motors (GM) model class (for example, Herman, Gazis et al. GM model, Gipps’s model, Payne’s model, Newell’s optimal velocity (OV) model, Wiedemann’s model, Bando et al. OV model, Treiber’s IDM, Krauß’s model), (iii) the understanding of highway capacity as a particular (fixed or stochastic) value, and (iv) principles for traffic and transportation network optimization and control (for example, Wardrop’s user equilibrium (UE) and system optimum (SO) principles). Alternatively to these generally accepted fundamentals and methodologies of the traffic and transportation theory, we discuss the three-phase traffic theory as the basis for traffic flow modeling as well as briefly consider the network breakdown minimization (BM) principle for the optimization of traffic and transportation networks with road bottlenecks.     

The maximization of the network throughput ensuring free flow conditions in traffic and transportation networks: Breakdown minimization (BM) principle versus Wardrop’s equilibria

We have revealed general physical conditions for the maximization of thenetwork throughput at which free flow conditions are ensured, i.e., traffic breakdowncannot occur in the whole traffic or transportation network. A physical measure of thenetwork – network capacity is introduced that characterizes generalfeatures of the network with respect to the maximization of the network throughput. Thenetwork capacity allows us also to make a general proof of the deterioration of trafficsystem occurring when dynamic traffic assignment is performed in a network based on theclassical Wardrop’ user equilibrium (UE) and system optimum (SO) equilibrium.     

有业务量疏导能力的WDM网格网阻塞性能分析

提出一个新分析模型来计算有业务量疏导能力的波分复用(WDM)网格网的呼叫阻塞概率,WDM网络中的业务量疏导定义为复用、解复用和交换低速率业务量到高容量光路的行为.该模型首先把原始网络分解为单个子系统,然后再对这些子系统进行独立分析,最后对这些子系统的结果进行适当组合得到整个网络的解.同时,模型考虑了链路负载和链路阻塞事件之间的相关性.仿真结果表明该模型给出的结果较准确.     

Effects of the cascading failures on scale-free traffic networks

In this paper, we consider the artificial scale-free traffic network with dynamic weights (cost) and focus on how the removal strategies (flow-based removal, betweenness-based removal and mix-based removal) affect the damage of cascading failures based on the user-equilibrium (UE) assignment, which ensures the balance of flow on the traffic network. Experiment simulation shows that different removal strategies can bring large dissimilarities of the efficiency and damage after the intentional removal of an edge. We show that the mix-based removal of a single edge might reduce the damage of cascading failures and delay the breakdown time, especially for larger reserve capacity coefficient α. This is particularly important for real-world networks with a highly hetereogeneous distribution of flow, i.e., traffic and transportation networks, logistics networks and electrical power grids.     

网络交通流动态演化的混沌现象及其控制

本文以含2条平行路径的交通网络为例, 探讨了网络交通流逐日动态演化问题. 首先, 建立了动态系统模型来刻画网络交通流的演化过程, 动态系统模型的不动点就是随机用户平衡解, 证明了平衡解存在且唯一. 然后, 根据非线性动力学理论, 推导出了网络交通流演化的稳定性条件. 其次, 通过数值实验, 分析了网络交通流的演化特征, 发现了在一定条件下流量的周期振荡和混沌现象. 最后, 以OD需求为控制变量推导出了网络交通流混沌控制的方法.     

An optimal network for passenger traffic

The optimal solution of an inter-city passenger transport network has been studied using Zipf’s law for the city populations and the Gravity law describing the fluxes of inter-city passenger traffic. Assuming a fixed value for the cost of transport per person per kilometer we observe that while the total traffic cost decreases, the total wiring cost increases with the density of links. As a result the total cost to maintain the traffic distribution is optimal at a certain link density which vanishes on increasing the network size. At a finite link density the network is scale-free. Using this model the air-route network of India has been generated and an one-to-one comparison of the nodal degree values with the real network has been made.     

A dynamic model for traffic network flow

Concerning the link properties in traffic networks, we introduce a dynamic equation of road flow into each link, and thereby propose a dynamic model for network flow. Using this model, we investigate the evolutions of inflow, outflow and flow on each link caused by a small perturbation of the network inflow under different route choice rules. Numerical results show that the dynamic model can reasonably capture the basic characteristics of network flow.     

A weighted network evolution with traffic flow

In this paper, we propose a simple weighted network model that generalizes the complex network model evolution with traffic flow previously presented to investigate the relationship between traffic flow and network structure. In the model, the nodes in the network are represented by the traffic flow states, the links in the network are represented by the transform of the traffic flow states, and the traffic flow transported when performing the transform of the traffic flow states is considered as the weight of the link. Several topological features of this generalized weighted model, such as the degree distribution and strength distribution, have been numerically studied. A scaling behavior between the strength and degree s∼klogk is obtained. By introducing some constraints to the generalized weighted model, we study its subnetworks and find that the scaling behavior between the strength and degree is conserved, though the topology properties are quite sensitive to the constraints.     

Outage probability and ergodic capacity analysis of satellite–terrestrial NOMA system with mixed RF/mmWave relaying

This paper investigates the performance of hybrid radio frequency/millimeter wave (RF/mmWave) satellite–terrestrial relay network with non-orthogonal multiple access (NOMA) scheme. In particular, the satellite network operates at the Ka-band while the mmWave band is adopted at decode-and-forward (DF) relay–destination link. The blockage effect in mmWave communication is considered to deduce the ordered probability density function (PDF) of the user equipment (UE) distance. However, the randomness of the UEs’ location and the random beamforming design cause the difficulty of the performance analysis. Herein, we provide a closed-form approximation for the outage probability. Moreover, the system diversity order is derived from the asymptotic expressions of the outage probability at high signal-to-noise ratio (SNR) slopes. Besides, approximate ergodic capacity performances of the multi-UEs are evaluated with numerical integration. Simulations are applied to demonstrate the accuracy of the theoretical analysis and show that the performance of the ordered selection NOMA scheme outperforms the orthogonal multiple access scheme and random selection scheme.     

Blocking in wavelength-routed all-optical WDM network with wavelength conversion

The blocking probability in wavelength-routed all optical networks is very important measure of performance of the network, which can be affected by many factors such as network topology, traffic load, number of links, algorithms employed and whether wavelength conversion is available or not. In this paper, we have proposed a mathematical model to reduce the blocking probability of the WDM optical network for wavelength-convertible networks. The model can be used to evaluate the blocking performance of any network topology also it can be useful to improve its blocking performance of the given network topology. The blocking probability variation of the network for a particular load (per link) has been studied based on the load variation and total number of wavelengths used in the network. This model gives good results for high load (per link).     

面向成本-收益好的无标度耦合网络构建方法

较大平均路径长度的网络会带来较大的网络延迟, 难以支持时间敏感业务与应用. 通过增加连接可以降低源和目的节点之间的跳数, 进而降低网络平均延迟, 使得更加快速地传播信息, 但是增加连接的同时也增加了网络构建成本. 分层网络是研究网络耦合的一个有效方法, 但目前网络构建过程中将每层网络分别处理并认为每层网络之间没有强相关性. 本文提出了一种面向成本-收益的无标度网络动态构建方法. 此方法将网络分为多层, 基于连续论在高层网络中添加连接, 使得网络演化为无标度网络. 此连续过程包括节点度增加过程和局部网络半径增长两个连续过程, 在增加连接的过程中引入表征网络构建成本和收益的成本-收益指标. 模拟结果表明引入成本-收益指标的无标度耦合网络构建方法能够在合理范围内有效降低网络平均路径长度, 提升网络性能, 并且本文给出了耦合网络的动态业务性能, 通过调整高层网络避免网络拥塞.     

Topological Effects on the Performance of Transportation Networks

We investigate the influence of the network topology on the performance （characterized by the total system cost and maximal tratffic volume） of transportation networks, where the weights are not static （constant）, but dynamic （a function of the flow on the link）. Four classes of networks are used in the simulation, including regular networks, random networks, small-world networks and scale-free networks. The initial simulation results show that topologies play important roles on the performance of transportation networks, and random networks have better performance than other networks. Also, we find that there are distinct difference of the link flow distribution for various networks in both the distribution function form and the span between the minimum and the maximum of the link flow, explaining the difference of the performance among distinct networks. These findings will be useful in network design problems of transportation systems.     

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     

一种有效提高无标度网络负载容量的管理策略

现有研究表明明显的社团结构会显著降低网络的传输性能. 本文基于网络邻接矩阵的特征谱定义了链路对网络社团特性的贡献度, 提出一种通过逻辑关闭或删除对网络社团特性贡献度大的链路以提高网络传输性能的拓扑管理策略, 即社团弱化控制策略(CWCS 策略). 在具有社团结构的无标度网络上分别进行了基于全局最短路径路由和局部路由的仿真实验, 并与关闭连接度大的节点之间链路的HDF 策略进行了比较. 仿真实验结果显示, 在全局最短路径路由策略下, CWCS策略能更有效地提高网络负载容量, 并且网络的平均传输时间增加的幅度变小. 在局部路由策略下, 当调控参数0<α<2, 对网络负载容量的提升优于HDF策略. 关键词： 复杂网络 社团特性 负载容量 拓扑管理     

中国铁路客运网网络性质的研究

中国铁路客运系统可以采用两种不同的网络构建方式来描述. 一种是以铁路的站点作为“节点”，并以轨道作为“边”，这样生成的网络称为铁路地理网. 统计显示该网络的平均群聚系数〈C〉近似为零，故该网络为树状网络. 另一种是以站点作为“节点”，任意两个站点间只要有同一列车在这两个站点停靠，就可以认为这两个站点间有连线，这样生成的网络称为车流网. 统计显示该网络有较大的平均群聚系数和较小的平均网络距离〈d〉，而且该网络节点的度分布基本上服从无标度幂律分布，故车流网为具有无标度性质的小世界网络. 关键词： 铁路地理网 车流网 小世界 无标度分布     

决定论性逐步加速交通流模型的渐近稳态行为

研究Nagel-Schreckenberg(NS)交通流元胞自动机模型在不考虑车辆随机延迟情况下的决定论性模型的基本图,即渐近稳态的车流平均速度作为车辆密度的函数关系．证明决定论性NS模型,在车流的自组织作用下,其渐近稳态的基本图,与决定论性Fukui-Ishibashi(FI)交通流模型的基本图完全相同．这个结果表明,若把FI交通流模型中的车辆突然加速方式（即车辆速度可以在仅仅一个时步内加速到其最高速限M或前方空距所允许的最大速度）,改变为车辆逐步加速方式（车辆速度在每一时步中最多仅能增加一个速度单位）,则车辆的自组织相互作用,并不会改变其车流的长时间渐近稳态行为． 关键词：     

RAT selection for IoT devices in HetNets: Reinforcement learning with hybrid SMDP algorithm

Due to the increasing deployment of heterogeneous networks (HetNets), the selection of which radio access technologies (RATs) for Internet of Things (IoT) devices such as user equipments (UEs) has recently received extensive attention in mobility management research. Most of existing RAT selection methods only optimize the selection strategies from the UE side or network side, which results in heavy network congestion, poor user experience and system utility degradation. In this paper the UE side and the network side are considered comprehensively, based on the game theory (GT) model we propose a reinforcement learning with assisted network information algorithm to overcome the crucial points. The assisted information is formulated as a semi-Markov decision process (SMDP) provided for UEs to make accurate decisions, and we adopt the iteration approach to reach the optimal policy. Moreover, we investigate the impacts of different parameters on the system utility and handover performance. Numerical results validate that our proposed algorithm can mitigate unnecessary handovers and improve system throughputs.