Bifurcation and stability of an improved time-delayed fluid flow model in internet congestion control

Based on the fluid flow time-delayed model proposed by Misra et al in internet congestion control, one modified time-delayed model is presented, where the influence of the communication delay on the router queue length is investigated in detail. The main advantage of the new model is that its stability domain is larger even without an extra controller. By linear stability analysis and numerical simulation, tbe effectiveness and feasibility of the novel model in internet congestion control are verified.

Evaluating Traffic Congestion Using the Traffic Occupancy and Speed Distribution Relationship: An Application of Bayesian Dirichlet Process Mixtures of Generalized Linear Model

Accurate classification and prediction of future traffic conditions are essential for developing effective strategies for congestion mitigation on the highway systems. Speed distribution is one of the traffic stream parameters, which has been used to quantify the traffic conditions. Previous studies have shown that multi-modal probability distribution of speeds gives excellent results when simultaneously evaluating congested and free-flow traffic conditions. However, most of these previous analytical studies do not incorporate the influencing factors in characterizing these conditions. This study evaluates the impact of traffic occupancy on the multi-state speed distribution using the Bayesian Dirichlet Process Mixtures of Generalized Linear Models (DPM-GLM). Further, the study estimates the speed cut-point values of traffic states, which separate them into homogeneous groups using Bayesian change-point detection (BCD) technique. The study used 2015 archived one-year traffic data collected on Florida’s Interstate 295 freeway corridor. Information criteria results revealed three traffic states, which were identified as free-flow, transitional flow condition (congestion onset/offset), and the congested condition. The findings of the DPM-GLM indicated that in all estimated states, the traffic speed decreases when traffic occupancy increases. Comparison of the influence of traffic occupancy between traffic states showed that traffic occupancy has more impact on the free-flow and the congested state than on the transitional flow condition. With respect to estimating the threshold speed value, the results of the BCD model revealed promising findings in characterizing levels of traffic congestion.

Local Bifurcation Analysis of a Delayed Fractional-order Dynamic Model of Dual Congestion Control Algorithms

In this paper, we propose a delayed fractional-order congestion control model which is more accurate than the original integer-order model when depicting the dual congestion control algorithms. The presence of fractional orders requires the use of suitable criteria which usually make the analytical work so harder. Based on the stability theorems on delayed fractionalorder differential equations, we study the issue of the stability and bifurcations for such a model by choosing the communication delay as the bifurcation parameter. By analyzing the associated characteristic equation, some explicit conditions for the local stability of the equilibrium are given for the delayed fractionalorder model of congestion control algorithms. Moreover, the Hopf bifurcation conditions for general delayed fractional-order systems are proposed. The existence of Hopf bifurcations at the equilibrium is established. The critical values of the delay are identified, where the Hopf bifurcations occur and a family of oscillations bifurcate from the equilibrium. Same as the delay, the fractional order normally plays an important role in the dynamics of delayed fractional-order systems. It is found that the critical value of Hopf bifurcations is crucially dependent on the fractional order. Finally, numerical simulations are carried out to illustrate the main results. © 2017 Chinese Association of Automation.

Adaptive Agent Model with Hybrid Routing Selection Strategy for Improving the Road-Network Congestion Problem

This paper proposes an adaptive agent model with a hybrid routing selection strategy for studying the road-network congestion problem. We focus on improving those severely congested links. Firstly,a multi-agent system is built,where each agent stands for a vehicle,and it makes its routing selection by considering the shortest path and the minimum congested degree of the target link simultaneously. The agent-based model captures the nonlinear feedback between vehicle routing behaviors and road-network congestion status.Secondly,a hybrid routing selection strategy is provided,which guides the vehicle routes adapting to the realtime road-network congestion status. On this basis, we execute simulation experiments and compare the simulation results of network congestion distribution,by Floyd agent with shortest path strategy and our proposed adaptive agent with hybrid strategy. The simulation results show that our proposed model has reduced the congestion degree of those seriously congested links of road-network. Finally,we execute our model on a real road map. The results finds that those seriously congested roads have some common features such as located at the road junction or near the unique road connecting two areas. And,the results also show an effectiveness of our model on reduction of those seriously congested links in this actual road network. Such a bottom-up congestion control approach with a hybrid congestion optimization perspective will have its significance for actual traffic congestion control.

Analyses of unified congestion measures for interrupted traffic flow on urban roads

To study the congestion of interrupted flow on urban roads, a comprehensive evaluation method is proposed. First, based on the results of correlation analysis between different parameters of interrupted flow, the traffic parameters of interrupted traffic flow are divided into two categories： the basic parameters and the operation parameters. Polynomial regression is used to formulize the nonlinear relationships between the basic parameters and the operation parameters. Then, the congestion model incorporating both operational and volume characteristics of traffic flow is proposed. The inputs of the model are the basic parameters, while the output is a dimensionless index value between 0 and 1. Finally, the proposed methods are compared with existing evaluation measures of congestion. Results show that the proposed indices can capture the variation of both the basic parameters and the operation parameters, which is more balanced compared with the existing evaluation measures.

Practical approach to determining traffic congestion propagation boundary due to traffic incidents

A practical approach for predicting the congestion boundary due to traffic incidents was proposed. Based on the kinematic wave theory and Van Aerde single-regime flow model, a model for estimating the congestion propagation speed for the basic road segment was developed. Historical traffic flow data were used to analyze the time variant characteristics of the urban traffic flow for each road type. Then, the saturation flow rate was used for analyzing the impact of the traffic incident on the traversing traffic flow at the congestion area. The base congestion propagation speed for each road type was calculated based on field data, which were provided by the remote traffic microwave sensors(RTMS), floating car data(FCD) system and screen line survey. According to a comparative analysis of the congestion propagation speed, it is found that the expressway, major arterial, minor arterial and collector are decreasingly influenced by the traffic incident. Subsequently, the impact of turning movements at intersections on the congestion propagation was considered. The turning ratio was adopted to represent the impact of turning movements, and afterward the corresponding propagation pattern at intersections was analyzed. Finally, an implementation system was designed on a geographic information system(GIS) platform to display the characteristics of the congestion propagation over the network. The validation results show that the proposed approach is able to capture the congestion propagation properties in the actual road network.

Calibration and Evaluation of Link Congestion Functions: Applying Intrinsic Sensitivity of Link Speed as a Practical Consideration to Heterogeneous Facility Types within Urban Network

This paper explores the use of archived data to calibrate volume delay functions (VDFs) and updates their input parameters (capacity and free-flow speed) for planning applications. The sensitivity analysis of speed to change in congestion level is performed to capture functional characteristics of VDFs in modeling specific facility types. Different sensitivity characteristics shown by the VDFs indicate that each function is suitable to a particular facility type. The results of sensitivity analysis are confirmed by the root mean square percent error (RMSPE) values calculated using the Orlando Urban Area Transportation Study (OUATS) model results and observed data. The modified Davidson’s function exhibits remarkable performance in nearly all facility types. The strength of the modified Davidson’s function across a broad range of facilities can be attributed to the flexibility of its tuning parameter, μ. Fitted Bureau of Public Road (BPR) and conical delay functions show lower RMSPE for uninterrupted flow facilities (freeways/expressways, managed lanes) and higher values for toll roads (which might have partial interruptions due to toll booths) and signalized arterials. Akcelik function underperforms on freeways/expressways and managed lanes but shows some improvements for toll roads and superior results for the signalized arterials. This was a desired strength of Akcelik function when modeling link travel speed on facilities where stopped delays were encountered.

Road traffic congestion measurement considering impacts on travelers

The article intends to find a method to quantify traffic congestion＇s impacts on travelers to help transportation planners and policy decision makers well understand congestion situations. Three new congestion indicators, including transportation environment satisfaction （TES）, travel time satisfaction （TTS）, and traffic congestion frequency and feeling （TCFF）, are defined to estimate urban traffic congestion based on travelers＇ feelings. Data of travelers＇ attitude about congestion and trip information were collected from a survey in Shanghai, China. Based on the survey data, we estimated the value of the three indi- cators. Then, the principal components analysis was used to derive a small number of linear combinations of a set of variables to estimate the whole congestion status. A linear regression model was used to find out the significant variables which impact respondents＇ feelings. Two ordered logit models were used to select significant variables of TES and TTS. Attitudinal factor variables were also used in these models. The results show that attitudinal factor variables and cluster category variables are as important as sociodemographic variables in the models. Using the three congestion indicators, the government can collect travelers＇ feeling about traffic congestion and estimate the transportation policy that might be applied to cope with traffic congestion.

A Dynamic Road Incident Information Delivery Strategy to Reduce Urban Traffic Congestion

Advanced information and communication technolo-gies can be used to facilitate traffic incident management.If an incident is detected and blocks a road link,in order to reduce the incident-induced traffic congestion,a dynamic strategy to deliver incident information to selected drivers and help them make detours in urban areas is proposed by this work.Time-dependent shortest path algorithms are used to generate a subnetwork where vehicles should receive such information.A simulation approach based on an extended cell transmission model is used to describe traffic flow in urban networks where path information and traffic flow at downstream road links are well modeled.Simulation results reveal the influences of some major parameters of an incident-induced congestion dissipation process such as the ratio of route-changing vehicles to the total vehicles,operation time interval of the proposed strategy,traffic density in the traffic network,and the scope of the area where traffic incident information is delivered.The results can be used to improve the state of the art in preventing urban road traffic congestion caused by incidents.

Traffic Congestion Mechanism in Two Ramp Systems

The aim of this paper is to study traffic properties in an on/off-ramp system with a bus stop close to the on/off ramp. The location of the bus stop in the on/off-ramp （thereafter downstream or upstream case） is discussed. The simulation results show that in the two ramp systems, the reasons for traffic congestions are different. In the on-ramp system, buses and cars coming from on-ramp interweave each other, while in the off-ramp system, buses interweave with cars exiting to off-ramp. Thus, in the on-ramp （off-ramp） system, the upstream （downstream） bus stop is helpful to reduce the interweaving situation. Moreover, the negative effect will disappear when the distance between the bus stop and the on/off-ramp is more than 20 cells （i.e. 150 m）. These qualitative findings may provide some suggestions on traffic management and optimization.

Science Letters:Model for cascading failures in congested Internet

Cascading failures often occur in congested networks such as the Internet. A cascading failure can be described as a three-phase process： generation, diffusion, and dissipation of the congestion. In this account, we present a function that represents the extent of congestion on a given node. This approach is different from existing fimctions based on betweenness centrality. By introducing the concept of ＇delay time＇, we designate an intergradation between permanent removal and nonremoval. We also construct an evaluation fimction of network efficiency, based on congestion, which measures the damage caused by cascading failures. Finally, we investigate the effects of network structure and size, delay time, processing ability and packet generation speed on congestion propagation. Also, we uncover the relationship between the cascade dynamics and some properties of the network such as structure and size.

A Framework for Intelligent Decision Support System for Traffic Congestion Management System

Traffic congestion problem is one of the major problems that face many transportation decision makers for urban areas. The problem has many impacts on social, economical and development aspects of urban areas. Hence the solution to this problem is not straight forward. It requires a lot of effort, expertise, time and cost that sometime are not available. Most of the existing transportation planning software, specially the most advanced ones, requires personnel with lots practical transportation planning experience and with high level of education and training. In this paper we propose a comprehensive framework for an Intelligent Decision Support System (IDSS) for Traffic Congestion Management System that utilizes a state of the art transportation network equilibrium modeling and providing an easy to use GIS-based interaction environment. The developed IDSS reduces the dependability on the expertise and level of education of the transportation planners, transportation engineers, or any transportation decision makers.

A NEW CONGESTION CONTROL POLICY ON THE INTERNETWORKS

This paper discusses the distinction between internetworks and single network in the congestion control. It has shown the reason why all of single network’s congestion control is not suitable to internetworks. A new congestion control scheme of internetworks is presented which uses acknowledgment time-outs and the feedback signal from gateway as indications of packet loss and congestion. Using a black-box model of the internetworks, this paper derives approximate calculating formulas and proves the scheme’s special characters by computer simulation. It is shown that the presented method is better than R. Jain’s (1986).

Optimal Nonlinear Distance Toll for Cordon-Based Congestion Pricing Considering Equity Issue

In order to address the optimal distance toll design problem for cordon-based congestion pricing incorporating the issue of equity,this paper presents a toll user equilibrium( TUE) model based on a transformed network with elastic demand,to evaluate any given toll charge function. A bi-level programming model is developed for determining the optimal toll levels,with the TUE being represented at the lower level.The upper level optimizes the total equity level over the transport network,represented by the Gini coefficient,where a constraint is imposed to the total travel impedance of each OD pair after the levy. A genetic algorithm( GA) is implemented to solve the bi-level model,which is verified by a numerical example.

An Efficient Hybrid TLBO-PSO Approach for Congestion Management Employing Real Power Generation Rescheduling

In the present deregulated electricity market, power system congestion is the main complication that an independent system operator (ISO) faces on a regular basis. Transmission line congestion trigger serious problems for smooth functioning in restructured power system causing an increase in the cost of transmission hence affecting market efficiency. Thus, it is of utmost importance for the investigation of various techniques in order to relieve congestion in the transmission network. Generation rescheduling is one of the most efficacious techniques to do away with the problem of congestion. For optimizing the congestion cost, this work suggests a hybrid optimization based on two effective algorithms viz Teaching learning-based optimization (TLBO) algorithm and Particle swarm optimization (PSO) algorithm. For binding the constraints, the traditional penalty function technique is incorporated. Modified IEEE 30-bus test system and modified IEEE 57-bus test system are used to inspect the usefulness of the suggested methodology.

Numerical Simulation of Diffusion Type Traffic Flow Model Using Second-Order Lax-Wendroff Scheme Based on Exponential Velocity Density Function

In order to control traffic congestion, many mathematical models have been used for several decades. In this paper, we study diffusion-type traffic flow model based on exponential velocity density relation, which provides a non-linear second-order parabolic partial differential equation. The analytical solution of the diffusion-type traffic flow model is very complicated to approximate the initial density of the Cauchy problem as a function of x from given data and it may cause a huge error. For the complexity of the analytical solution, the numerical solution is performed by implementing an explicit upwind, explicitly centered, and second-order Lax-Wendroff scheme for the numerical solution. From the comparison of relative error among these three schemes, it is observed that Lax-Wendroff scheme gives less error than the explicit upwind and explicit centered difference scheme. The numerical, analytical analysis and comparative result discussion bring out the fact that the Lax-Wendroff scheme with exponential velocity-density relation of diffusion type traffic flow model is suitable for the congested area and shows a better fit in traffic-congested regions.

生成式大模型承载网络架构与关键技术探索

生成式大模型训练需要超大规模低时延、高带宽、高可用的网络承载底座。对生成式大模型下高性能网络基础设施的技术发展路线和实现方案进行了研究,认为商用部署时需针对不同训练阶段的工作负载和流量模式,开展定制化网络架构设计和传输协议优化。流控/拥塞控制技术、负载均衡技术、自动化运维技术和面向广域远程直接内存访问(RDMA)的确定性网络传输技术是未来的重点研究方向。

基于大数据分析的高速公路分车型拥堵态势评估

针对面向全车型的道路拥堵状态评估统一化和静态管控方法的局限性,围绕不同类型车辆的交通拥堵问题开展研究。首先,基于沈海高速公路福建段龙门架数据,采用聚类方法分析不同类型车辆在不同指标下的交通拥堵特征;其次,提出分车型数据驱动的模糊云模型,根据行业专家给出的数字特征计算不同车型下的拥堵等级隶属度;然后,选取拥堵指标作为模糊逻辑系统的输入,并采用Mamdani方法建立模糊关联矩阵,量化不同专家评价的可信度;引入Dempster-Shafter证据理论对所有专家的综合可信度进行模糊融合,根据隶属度最大原则综合评判道路交通状态;最后,验证了提出模型的精度及对车型间差异表征的准确性,分车型下的拥堵评价结果一致性达84.51%。结果表明:相比1~4型客车及小型货车,大型货车在移动过程中形成的瓶颈对高速公路上堵塞的消散表现出明显的迟滞作用;在低密度下,客车、少轴货车、多轴货车渗透率的提高对路况的影响依次提升;在高密度下,3~6轴货车渗透率的改变对拥堵状态的影响最为明显,1~4轴客车次之。分车型拥堵研究可为制订适应各类车型的主动交通管理提供定量的数据支撑,特别是在动态调控措施如错峰出行、可变限速等方面具有重要指导意义。

拥堵车源的区域多层交通网络混合路径诱导策略

为了缓解高速公路交通拥堵,利用国道和省道实现交通分流,并有针对性地实施路径诱导策略,建立了考虑拥堵车源的区域多层交通网络混合路径诱导模型。首先,构建了由国道、省道以及湖南省高速公路组成的区域多层交通网络,标定网络链接权重。然后,定位交通拥堵车源,建立了考虑拥堵车源的混合路径诱导模型,对从拥堵车源出发的车辆实施有针对性的路径诱导,在保障缓解交通拥堵效果的同时,尽可能减少对出行者的影响。研究结果表明,该模型能够实现多层网络有效分流,有效减少路网中车辆的平均出行时间。在实际应用中,可以只对少数出行者提供路径诱导信息以降低模型的实施难度,并通过调查出行者对建议路径的接受率,制定合适的路径诱导信息发布方案。

拥挤信息下基于Logit模型的公共交通 方式选择行为研究

人们对出行方式的舒适性要求越来越高,出行信息能为出行者提供有效帮助。采用正交试验对公共交通方式选择特性变量进行情景组合设计,并结合公共交通出行特征进行问卷调查设计,对提供拥挤信息条件下出行者对公共交通方式选择意愿进行调查,据此建立公共交通方式选择Logit模型。结果表明,拥挤信息对公共交通方式选择有显著影响,对公交出行选择影响较大。