WiFi and LTE Coexistence in the Unlicensed Spectrum

Today, smart-phones have revolutionized wireless communication industry towards an era of mobile data. To cater for the ever increasing data traffic demand, it is of utmost importance to have more spectrum resources whereby sharing under-utilized spectrum bands is an effective solution. In particular, the 4G broadband Long Term Evolution (LTE) technology and its foreseen 5G successor will benefit immensely if their operation can be extended to the under-utilized unlicensed spectrum. In this thesis, first we analyze WiFi 802.11n and LTE coexistence performance in the unlicensed spectrum considering multi-layer cell layouts through system level simulations. We consider a time division duplexing (TDD)-LTE system with an FTP traffic model for performance evaluation. Simulation results show that WiFi performance is more vulnerable to LTE interference, while LTE performance is degraded only slightly. Based on the initial findings, we propose a Q-Learning based dynamic duty cycle selection technique for configuring LTE transmission gaps, so that a satisfactory throughput is maintained both for LTE and WiFi systems. Simulation results show that the proposed approach can enhance the overall capacity performance by 19% and WiFi capacity performance by 77%, hence enabling effective coexistence of LTE and WiFi systems in the unlicensed band.

Impact of a program for the prevention of traffic accidents in a Southern Brazilian city: a model for implementation in a developing country

Background: Traffic accidents constitute the main cause of death in the first decades of life. Traumatic brain injury is the event most responsible for the severity of these accidents. The SBN started an educational program for the prevention of traffic accidents, adapted from the American model ""Think First"" to the Brazilian environment, since 1995, with special effort devoted to the prevention of TBI by using seat belts and motorcycle helmets. The objective of the present study was to set up a traffic accident prevention program based on the adapted Think First and to evaluate its impact by comparing epidemiological variables before and after the beginning of the program. Methods: The program was executed in Maringa city, from September 2004 to August 2005, with educational actions targeting the entire population, especially teenagers and young adults. The program was implemented by building a network of information facilitators and multipliers inside the organized civil society, with widespread population dissemination. To measure the impact of the program, a specific software was developed for the storage and processing of the epidemiological variables. Results: The results showed a reduction of trauma severity due to traffic accidents after the execution of the program, mainly TBI. Conclusions: The adapted Think First was systematically implemented and its impact measured for the first time in Brazil, revealing the usefulness of the program for reducing trauma and TBI severity in traffic accidents through public education and representing a standardized model of implementation in a developing country. (C) 2009 Elsevier Inc. All rights reserved.

A Model of Video Traffic Transmission in IP Networks

Telecommunications and network technology is now the driving force that ensures continued progress of world civilization. Design of new and expansion of existing network infrastructures requires improving the quality of service(QoS). Modeling probabilistic and time characteristics of telecommunication systems is an integral part of modern algorithms of administration of quality of service. At present, for the assessment of quality parameters except simulation models analytical models in the form of systems and queuing networks are widely used. Because of the limited mathematical tools of models of these classes the corresponding parameter estimation of parameters of quality of service are inadequate by definition. Especially concerning the models of telecommunication systems with packet transmission of multimedia real-time traffic.

Advances in Model-Based Traffic Vision

Model based vision allows use of prior knowledge of the shape and appearance of specific objects to be used in the interpretation of a visual scene; it provides a powerful and natural way to enforce the view consistency constraint. A model based vision system has been developed within ESPRIT VIEWS: P2152 which is able to classify and track moving objects (cars and other vehicles) in complex, cluttered traffic scenes. The fundamental basis of the method has been previously reported. This paper presents recent developments which have extended the scope of the system to include (i) multiple cameras, (ii) variable camera geometry, and (iii) articulated objects. All three enhancements have easily been accommodated within the original model-based approach

Cellular automaton model for molecular traffic jams

We consider the time evolution of an exactly solvable cellular automaton with random initial conditions both in the large-scale hydrodynamic limit and on the microscopic level. This model is a version of the totally asymmetric simple exclusion process with sublattice parallel update and thus may serve as a model for studying traffic jams in systems of self-driven particles. We study the emergence of shocks from the microscopic dynamics of the model. In particular, we introduce shock measures whose time evolution we can compute explicitly, both in the thermodynamic limit and for open boundaries where a boundary-induced phase transition driven by the motion of a shock occurs. The motion of the shock, which results from the collective dynamics of the exclusion particles, is a random walk with an internal degree of freedom that determines the jump direction. This type of hopping dynamics is reminiscent of some transport phenomena in biological systems.

Explaining car drivers' intention to prevent road-traffic noise: An application of the Norm Activation Model

Strengthening car drivers’ intention to prevent road-traffic noise is a first step toward noise abatement through voluntary change of behavior. We analyzed predictors of this intention based on the norm activation model (i.e., personal norm, problem awareness, awareness of consequences, social norm, and value orientations). Moreover, we studied the effects of noise exposure, noise sensitivity, and noise annoyance on problem awareness. Data came from 1,002 car drivers who participated in a two-wave longitudinal survey over 4 months. Personal norm had a large prospective effect on intention, even when the previous level of intention was controlled for, and mediated the effect of all other variables on intention. Almost 60% of variance in personal norm was explained by problem awareness, social norm, and biospheric value orientation. The effects of noise sensitivity and noise exposure on problem awareness were small and mediated by noise annoyance. We propose four communication strategies for strengthening the intention to prevent road-traffic noise in car drivers.

Comparison of dynamic effects of high-speed traffic load on ballasted track using a simplified two-dimensional and full three-dimensional model.

The vertical dynamic actions transmitted by railway vehicles to the ballasted track infrastructure is evaluated taking into account models with different degree of detail. In particular, we have studied this matter from a two-dimensional (2D) finite element model to a fully coupled three-dimensional (3D) multi-body finite element model. The vehicle and track are coupled via a non-linear Hertz contact mechanism. The method of Lagrange multipliers is used for the contact constraint enforcement between wheel and rail. Distributed elevation irregularities are generated based on power spectral density (PSD) distributions which are taken into account for the interaction. The numerical simulations are performed in the time domain, using a direct integration method for solving the transient problem due to the contact nonlinearities. The results obtained include contact forces, forces transmitted to the infrastructure (sleeper) by railpads and envelopes of relevant results for several track irregularities and speed ranges. The main contribution of this work is to identify and discuss coincidences and differences between discrete 2D models and continuum 3D models, as wheel as assessing the validity of evaluating the dynamic loading on the track with simplified 2D models

Multi-resolution model-based traffic sign detection and tracking

In this paper we propose an innovative approach to tackle the problem of traffic sign detection using a computer vision algorithm and taking into account real-time operation constraints, trying to establish intelligent strategies to simplify as much as possible the algorithm complexity and to speed up the process. Firstly, a set of candidates is generated according to a color segmentation stage, followed by a region analysis strategy, where spatial characteristic of previously detected objects are taken into account. Finally, temporal coherence is introduced by means of a tracking scheme, performed using a Kalman filter for each potential candidate. Taking into consideration time constraints, efficiency is achieved two-fold: on the one side, a multi-resolution strategy is adopted for segmentation, where global operation will be applied only to low-resolution images, increasing the resolution to the maximum only when a potential road sign is being tracked. On the other side, we take advantage of the expected spacing between traffic signs. Namely, the tracking of objects of interest allows to generate inhibition areas, which are those ones where no new traffic signs are expected to appear due to the existence of a TS in the neighborhood. The proposed solution has been tested with real sequences in both urban areas and highways, and proved to achieve higher computational efficiency, especially as a result of the multi-resolution approach.

A Knowledge Model for Automatic Configuration of Traffic Messages

This paper describes a knowledge model for a configuration problem in the do-main of traffic control. The goal of this model is to help traffic engineers in the dynamic selection of a set of messages to be presented to drivers on variable message signals. This selection is done in a real-time context using data recorded by traffic detectors on motorways. The system follows an advanced knowledge-based solution that implements two abstract problem solving methods according to a model-based approach recently proposed in the knowledge engineering field. Finally, the paper presents a discussion about the advantages and drawbacks found for this problem as a consequence of the applied knowledge modeling ap-proach.

Additional traffic assignment options for the TASSIM model. Phase I. Final report.

Transportation Department, Washington, D.C.

Integrated traffic simulation model - phase I. Volume 4: revisions to the UTCS-1 traffic simulation model to enhance operational efficiency. Final report.

Federal Highway Administration, Washington, D.C.

A new continuum model for traffic flow. Final report.

Transportation Department, Office of University Research, Washington, D.C.

Integrated traffic simulation model, phase, I. Volume 1: executive summary. Final report.

Federal Highway Administration, Washington, D.C.

Integrated traffic simulation model - phase I. Volume 2: design of the TRAF system (TOS). Final report.

Federal Highway Administration, Washington, D.C.

FHWA highway traffic noise prediction model. Final report.

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