Modeling and Profiling of Aggregated Industrial Network Traffic

The industrial network infrastructures are transforming to a horizontal architecture to enable data availability for advanced applications and enhance flexibility for integrating new technologies. The uninterrupted operation of the legacy systems needs to be ensured by safeguarding their requirements in network configuration and resource management. Network traffic modeling is essential in understanding the ongoing communication for resource estimation and configuration management. The presented work proposes a two-step approach for modeling aggregated traffic classes of brownfield installation. It first detects the repeated work-cycles and then aims to identify the operational states to profile their characteristics. The performance and influence of the approach are evaluated and validated in two experimental setups with data collected from an industrial plant in operation. The comparative results show that the proposed method successfully captures the temporal and spatial dynamics of the network traffic for characterization of various communication states in the operational work-cycles.

A novel lattice hydrodynamic model accounting for individual difference of honk effect for two-lane highway under V2X environment

In this work, the individual difference of the honk effect is explored on two lanes via traffic modeling of the lattice model under Vehicle to X (V2X) environment. We study the impact of individual difference corresponding to honk cases on traffic stability through linear stability analysis for a two-lane highway. Furthermore, the mKdV equation under the lane changing phenomena is conducted via nonlinear analysis. Simulation cases for the early time and longtime impact reveal that individual difference of driving characteristics has a distinct impact on two lanes under the whistling environment.

Traffic Data Collection and Visualization Tool for Knowledge Discovery Using Google Maps

Traffic jam is increasingly aggravating in almost every urban area. Traffic forecast, traffic modeling, visualization can help to provide appropriate route and time for traveling and thus provides a significant impact on traffic jam reduction. For traffic forecasting, modeling and visualization, city-wide traffic data collection and analysis are needed, which is still challenging in many aspects. This paper aims to develop a tool for acquiring and processing traffic data from Google Maps that can be used for forecasting, modeling, and visualization. Dhaka city is used as a case study since there is no infrastructure available for traffic data collection. The traffic flow intensity of the road is analyzed to determine the congestion of the road. The flow intensity is used for traffic modeling, visualization, traffic prediction and many more.

Three-frequency models for determining the orientation of a solid body taking into account the vibration environment

Two new three-frequency reference models of solid motion taking into account the vibrational environment are proposed. They are based on a four-frequency reference model of rotation [1], which implements rotations according to Krylov angles. For the developed models the analytical dependences for quasi-coordinates, projections of the angular velocity vector and components of the quaternion of orientation corresponding to such rotational motion are obtained. The urgency of taking into account the influence of vibration in traffic modeling on the basis of domestic and foreign literature in the field of navigation, including for the last 10 years. The main sources of vibration are described in detail and what types of oscillations they correspond to - harmonic oscillations occur in moving elements of onboard systems, such as the engine rotor, and in the engine unit and its units there are oscillations that have the character of random broadband noise. Methods of correction of such influence for increase of accuracy of definition of orientation of object are analyzed. The location of the components of the platformless inertial navigation system relative to the vibration sources is considered to be related to the strength of the influence of the vibration environment on the accuracy of the obtained data. Numerical implementations of the models are obtained and the drift error for the third-order orientation algorithm is estimated for several sets of specified parameters in a certain way. The parameters are chosen arbitrarily, but taking into account the existing restrictions on angular motion. The corresponding figures show the result for one of these sets of numerical values (which shows the result of the research in the most detail). The obtained results are compared with the corresponding results for the four-frequency rotation model [1]. The expediency of using new three-frequency models under certain conditions is shown.

Modeling and Analysis of Mixed Traffic Networks with Human-driven and Autonomous Vehicles

The emergence of connected and automated vehicles (CAV) indicates improved traffic mobility in future traffic transportation systems. This study addresses the research gap in macroscopic traffic modeling of mixed traffic networks where CAV and human-driven vehicles coexist. CAV behavior is explicitly included in the proposed traffic network model, and the vehicle number non-conservation problem is overcome by describing the approaching and departure vehicle number in discrete time. The proposed model is verified in typical CAV cooperation scenarios. The performance of CAV coordination is analyzed in road, intersection and network scenario. Total travel time of the vehicles in the network is proved to be reduced when coordination are applied. Simulation results validate the accuracy of the proposed model and the effectiveness of the proposed algorithm.

Traffic Impact Assessment for the Stadiums Hosting FIFA 2022 World Cup in Qatar: A Case Study

The State of Qatar has made extensive preparation to successfully host the upcoming FIFA 2022 World Cup, a tournament that will be held for the first time in the Middle East and the North Africa region. In preparation for this tournament, a wide-ranging operational strategy is being developed for each of the stadiums separately. This paper looks into the preparation stages of master planning and transport strategy for one of the hosting venues, which is located in Al Rayyan, Qatar. An overview of the Fédération Internationale de Football Association (FIFA) tournament, its assumptions, spatial planning, traffic modeling, Temporary Traffic Management, and the required mitigations from the transport operations perspective alongside the lessons learned are discussed in the paper.

Modeling and Prediction of Daily Traffic Patterns—WASK and SIX Case Study

The paper studies efficient modeling and prediction of daily traffic patterns in transport telecommunication networks. The investigation is carried out using two historical datasets, namely WASK and SIX, which collect flows from edge nodes of two networks of different size. WASK is a novel dataset introduced and analyzed for the first time in this paper, while SIX is a well-known source of network flows. For the considered datasets, the paper proposes traffic modeling and prediction methods. For traffic modeling, the Fourier Transform is applied. For traffic prediction, two approaches are proposed—modeling-based (the forecasting model is generated based on historical traffic models) and machine learning-based (network traffic is handled as a data stream where chunk-based regression methods are applied for forecasting). Then, extensive simulations are performed to verify efficiency of the approaches and their comparison. The proposed modeling method revealed high efficiency especially for the SIX dataset, where the average error was lower than 0.1%. The efficiency of two forecasting approaches differs with datasets–modeling-based methods achieved lower errors for SIX while machine learning-based for WASK. The average prediction error for SIX reached 3.36% while forecasting for WASK turned out extremely challenging.