Variable bit rate video traffic modeling by multiplicative multifractal model

Multiplicative multifractal process could well modal video traffic. The multiplier distributions in the multiplicatire multifractal model for video traffic are investigated and it is found that Gaussian is not suitable for describing the multipliers on the small time scales. A new statistical distribution-symmetric Pareto distribution is introduced. It is applied instead of Gaussian for the multipliers on those scales. Based on that, the algorithm is updated so that symmetric pareto distribution and Gaussian distribution are used to model video traffic but on different time scales. The simulation results demonstrate that the algorithm could model video traffic more accurately.

Traffic Modeling in WCDMA System Level Simulations

Traffic modeling is a crucial element in WCDMA system levelsimulations. A clear understanding of the nature of traffic in theWCDMA system and subsequent selection of an appropriate randomtraffic model are critical to the success of the modeling enterprise.The resultant performance will evidently be of a function that ourdesign has been well adapted to the traffic, channel and usermobility models, and these models are also accurate. In this article,our attention will be focused on modeling voice and WWW data trafficwith the SBBP model and Victor model respectively.

Continuum modeling for two-lane traffic flow with consideration of the traffic interruption probability

Considering the effects that the probability of traffic interruption and the friction between two lanes have on the car-following behaviour, this paper establishes a new two-lane microscopic car-following model. Based on this microscopic model, a new macroscopic model was deduced by the relevance relation of microscopic and macroscopic scale parameters for the two-lane traffic flow. Terms related to lane change are added into the continuity equations and velocity dynamic equations to investigate the lane change rate. Numerical results verify that the proposed model can be efficiently used to reflect the effect of the probability of traffic interruption on the shock, rarefaction wave and lane change behaviour on two-lane freeways. The model has also been applied in reproducing some complex traffic phenomena caused by traffic accident interruption.

Traffic Modeling and Analysis of Cellular Networks with Dynamic Channel Allocation

Dynamic channel allocation can reduce the blocking probability of cellular networks. This paper aims atestimating the blocking probability for cellular networki with dynamic channel allocation. Traffic analysis modelsare presented to evaluate performance of cellular networkS, The blocking probabilities versus traffic offered to eachcell are analyzed and simulated Comparisons between analysis and simulation results are made.

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.

A genetic resampling particle filter for freeway traffic-state estimation

On-line estimation of the state of traffic based on data sampled by electronic detectors is important for intelligent traffic management and control. Because a nonlinear feature exists in the traffic state, and because particle filters have good characteristics when it comes to solving the nonlinear problem, a genetic resampling particle filter is proposed to estimate the state of freeway traffic. In this paper, a freeway section of the northern third ring road in the city of Beijing in China is considered as the experimental object. By analysing the traffic-state characteristics of the freeway, the traffic is modeled based on the second-order validated macroscopic traffic flow model. In order to solve the particle degeneration issue in the performance of the particle filter, a genetic mechanism is introduced into the resampling process. The realization of a genetic particle filter for freeway traffic-state estimation is discussed in detail, and the filter estimation performance is validated and evaluated by the achieved experimental data.

Cellular automata model for traffic flow with safe driving conditions

In this paper, a recently introduced cellular automata （CA） model is used for a statistical analysis of the inner micro-scopic structure of synchronized traffic flow. The analysis focuses on the formation and dissolution of clusters or platoons of vehicles, as the mechanism that causes the presence of this synchronized traffic state with a high flow. This platoon formation is one of the most interesting phenomena observed in traffic flows and plays an important role both in manual and automated highway systems （AHS）. Simulation results, obtained from a single-lane system under periodic boundary conditions indicate that in the density region where the synchronized state is observed, most vehicles travel together in pla- toons with approximately the same speed and small spatial distances. The examination of velocity variations and individual vehicle gaps shows that the flow corresponding to the synchronized state is stable, safe and highly correlated. Moreover, results indicate that the observed platoon formation in real traffic is reproduced in simulations by the relation between vehicle headway and velocity that is embedded in the dynamics definition of the CA model.

An Intrusion Alarming System Based on Self-Similarity of Network Traffic

Intrusion detection system ean make effective alarm for illegality of networkusers, which is absolutely necessarily and important to build security environment of communicationbase service According to the principle that the number of network traffic can affect the degree ofself-similar traffic, the paper investigates the variety of self-similarity resulted fromunconventional network traffic. A network traffic model based on normal behaviors of user isproposed and the Hursl parameter of this model can be calculated. By comparing the Hurst parameterof normal traffic and the self-similar parameter, we ean judge whether the network is normal or notand alarm in time.

A new traffic model with the consideration of coupling effect with two lanes

This paper introduces a new two-lane high-order continuum model by embedding the two delay time scales con- tinuum traffic model presented by Xue （2003 Phys. Rev. E 68 066123） into the multi-lane model proposed by Daganzo （1997 Transpn. Res. B 31 83） with the consideration of the coupling effect between the vehicles of two lanes in instantaneous traffic situation and lane-change effect. In the novel model, the coupling effect of two lanes and phenomena of lane change, which were not discussed in Daganzo＇s model and Xue＇s model, are taken into account. Numerical simulation shows that it is in accordance with real traffic flow. This obviously indicates that the new phenomenon and behaviour are analogous results as single lane presented by Xue, and the proposed model is more reasonable on two lanes. Furthermore, the generation rate between two lanes is also investigated. The results show that the formation and diffusion of traffic shock wave can be better simulated on two lanes.

A new traffic model on compulsive lane-changing caused by off-ramp

In the field of traffic flow studies, compulsive lane-changing refers to lane-changing （LC） behaviors due to traffic rules or bad road conditions, while free LC happens when drivers change lanes to drive on a faster or less crowded lane. LC studies based on differential equation models accurately reveal LC influence on traffic environment. This paper presents a second-order partial differential equation （PDE） model that simulates both compulsive LC behavior and free LC behavior, with lane-changing source terms in the continuity equation and a lane-changing viscosity term in the momentum equation. A specific form of this model focusing on a typical compulsive LC behavior, the ＇off-ramp problem＇, is derived. Numerical simulations are given in several cases, which are consistent with real traffic phenomenon.

Modelling vehicular interactions for heterogeneous traffic flow using cellular automata with position preference

This paper proposes and validates a modified cellular automata model for determining interaction rate （i.e. number of car-following/overtaking instances） using traffic flow data measured in the field. The proposed model considers lateral position preference by each vehicle type and introduces a position preference parameter fl in the model which facilitates gradual drifting towards preferred position on road, even if the gap in front is sufficient. Additionally, the model also improves upon the conven- tional model by calculating safe front and back gap dynamically based on speed and deceleration properties of leader and follower vehicles. Sensitivity analysis was carried out to determine the effect of β on vehicular interac- tions and the model was calibrated and validated using interaction rates observed in the field. Paired tests were conducted to determine the determining interaction rates validity of the model in Results of the simulations show that there is a parabolic relationship between area occupancy and interaction rate of different vehicle types. The model performed satisfactorily as the simulated interaction rate between different vehicle types were found to be statistically similar to those observed in field. Also, as expected, the interaction rate between light motor vehicles （LMVs） and heavy motor vehicles （HMVs） were found to be higher than that between LMVs and three wheelers because LMVs and HMVs share the same lane. This could not be done using conventional CA models as lateral movement rules were dictated by only speeds and gaps. So, in conventional models, the vehicles would end up in positions which are not realistic. The position preference parameter introduced in this model motivates vehicles to stay in their preferred positions. This study demonstrates the use of interaction rate as a measure to validate micro- scopic traffic flow models.

Robust identification for multi_section freeway traffic models

Since it is difficult to fit measured parameters using the conventional traffic model, a new traffic density and average speed model is introduced in this paper. To determine traffic model structures accurately, a model identification method for uncertain nonlinear system is developed. To simplify uncertain nonlinear problem, this paper presents a new robust criterion to identify the multi-section traffic model structure of freeway efficiently. In the new model identification criterion, numerically efficient U-D factofization is used to avoid computing the determinant values of two complex matrices. By estimating the values of U-D factor of data matrix, both the upper and lower bounds of system uncertainties are described. Thus a model structure identification algorithm is proposed. Comparisons between identification outputs and simulation outputs of traffic states show that the traffic states can be accurately predicted by means of the new traffic models and the structure identification criterion.

Solitary wave solution to Aw-Rascle viscous model of traffic flow

A traveling wave solution to the Aw-Rascle traffic flow model that includes the relaxation and diffusion terms is investigated. The model can be approximated by the well-known Kortweg-de Vries （KdV） equation. A numerical simulation is conducted by the first-order accurate Lax-Friedrichs scheme, which is known for its ability to capture the entropy solution to hyperbolic conservation laws. Periodic boundary conditions are applied to simulate a lengthy propagation, where the profile of the derived KdV solution is taken as the initial condition to observe the change of the profile. The simulation shows good agreement between the approximated KdV solution and the numerical solution.

DYNAMIC RESOURCE ALLOCATION SCHEME UNDER TRAFFIC CONDITION IN SATELLITE SYSTEMS

As the traffic distribution in China mainland is far from uniform, a new traffic model in China mainland is presented on the basis of per-capita Gross Domestic Product (GDP) and density of population. Based on this characteristic traffic model, a new Traffic Dependent Dynamic Channel Allocation and Reservation (TDDCAR) technique is proposed, the simulation model is built, and the strategies' performance is evaluated through computer simulation. The simulation results show that, compared to the conventional Fixed Channel Allocation (FCA), TDDCAR estimates the traffic conditions in every spot beam and frequently adjusts the traffic according to current traffic conditions. It has achieved a significant improvement in new call blocking probability, handover blocking probability, and fair index, particularly, in heavy traffic conditions. The building of traffic model in China mainland and the analysis of the simulation results has been a key foundation for the study of resource allocation schemes in the future.

Asymptotic solution of a wide moving jam to a class of higher-order viscous traffic flow models

The boundary-layer method is used to study a wide moving jam to a class of higher-order viscous models. The equations for characteristic parameters are derived to determine the asymptotic solution. The sufficient and essential conditions for the wide moving jam formation are discussed in detail, respectively, and then used to prove or disprove the existence of the wide moving jam solutions to many well-known higher-order models. It is shown that the numerical results agree with the analytical results.

A weighted mean velocity feedback strategy in intelligent two-route traffic systems

Information feedback strategies can influence the traffic efficiency of intelligent traffic systems greatly.Based on the more practical symmetrical two-route scenario with one entrance and one exit,an improved weighted mean velocity feedback strategy（WMVFS） is proposed,which is not sensitive to the precision of global position system（GPS） devices.The applicability of WMVFS to different weight factors,aggressive probabilities,densities of dynamic vehicles,and different two-route scenarios（symmetrical scenario and asymmetrical scenario with a speed limit bottleneck） is analyzed.Results show that WMVFS achieves the best performance compared with three other information feedback strategies when considering the traffic flux and stability.

Scheduling of high-speed rail traffic based on discrete-time movement model

In this paper, a new simulation approach for solving the mixed train scheduling problem on the high-speed double-track rail line is presented. Based on the discrete-time movement model, we propose control strategies for mixed train movement with different speeds on a high-speed double-track rail line, including braking strategy, priority rule, travelling strategy, and departing rule. A new detailed algorithm is also presented based on the proposed control strategies for mixed train movement. Moreover, we analyze the dynamic properties of rail traffic flow on a high-speed rail line. Using our proposed method, we can effectively simulate the mixed train schedule on a rail line. The numerical results demonstrate that an appropriate decrease of the departure interval can enhance the capacity, and a suitable increase of the distance between two adjacent stations can enhance the average speed. Meanwhile, the capacity and the average speed will be increased by appropriately enhancing the ratio of faster train number to slower train number from 1.

A new traffic model with a lane-changing viscosity term

In this paper, a new continuum traffic flow model is proposed, with a lane-changing source term in the continuity equation and a lane-changing viscosity term in the acceleration equation. Based on previous literature, the source term addresses the impact of speed difference and density difference between adjacent lanes, which provides better precision for free lane-changing simulation; the viscosity term turns lane-changing behavior to a ＂force＂ that may influence speed distribution. Using a flux-splitting scheme for the model discretization, two cases are investigated numerically. The case under a homogeneous initial condition shows that the numerical results by our model agree well with the analytical ones; the case with a small initial disturbance shows that our model can simulate the evolution of perturbation, including propagation,dissipation, cluster effect and stop-and-go phenomenon.

ONE-DIMENSIONAL CELLULAR AUTOMATON MODEL OFTRAFFIC FLOW BASED ON CAR-FOLLOWING IDEA

An improved one-dimensional CA ( Cellular Automaton) traffic model was proposed to describe the highway traffic under the periodic boundary conditions. This model was based on the idea of the car-following model, which claims that the motion of a vehicle at one time step depends on both its headway and the synchronous motion of the front vehicle, thus including indirectly the influence of its sub-neighboring vehicle. It? addition, the so-called safety distance was introduced to consider the deceleration behavior of vehicles and the stochastic factor was taken into account by introducing the deceleration probability. Meanwhile, the conditional deceleration in the model gives a better description of the phenomena observed on highways. It is found that there exists the metastability and hysteresis effect of traffic flow in the neighborhood of critical density under different initial conditions. Since this model gives a reasonable depiction of the motion of a single vehicle, it is easy to be extended to the case of traffic flow tinder the control of traffic lights in cities.

Steady state speed distribution analysis for a combined cellular automaton traffic model

Cellular Automaton （CA） based traffic flow models have been extensively studied due to their effectiveness and simplicity in recent years. This paper develops a discrete time Markov chain （DTMC） analytical framework for a Nagel-Schreckenberg and Fukui Ishibashi combined CA model （W^2H traffic flow model） from microscopic point of view to capture the macroscopic steady state speed distributions. The inter-vehicle spacing Maxkov chain and the steady state speed Markov chain are proved to be irreducible and ergodic. The theoretical speed probability distributions depending on the traffic density and stochastic delay probability are in good accordance with numerical simulations. The derived fundamental diagram of the average speed from theoretical speed distributions is equivalent to the results in the previous work.