A methodology to estimate time varying user responses to travel time and travel time reliability in a road pricing environment

Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.

Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model

Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.

Real-Time Visual SLAM Using Pre - Existing Floor Lines as Landmarks and a Single Camera

SANTANA, Andr�� M.; SANTIAGO, Gutemberg S.; MEDEIROS, Adelardo A. D. Real-Time Visual SLAM Using Pre-Existing Floor Lines as Landmarks and a Single Camera. In: CONGRESSO BRASILEIRO DE AUTOM��TICA, 2008, Juiz de Fora, MG. Anais... Juiz de Fora: CBA, 2008.

Dithen: A Computation-as-a-Service Cloud Platform For Large-Scale Multimedia Processing

We present Dithen, a novel computation-as-a-service (CaaS) cloud platform specifically tailored to the parallel ex-ecution of large-scale multimedia tasks. Dithen handles the upload/download of both multimedia data and executable items, the assignment of compute units to multimedia workloads, and the reactive control of the available compute units to minimize the cloud infrastructure cost under deadline-abiding execution. Dithen combines three key properties: (i) the reactive assignment of individual multimedia tasks to available computing units according to availability and predetermined time-to-completion constraints; (ii) optimal resource estimation based on Kalman-filter estimates; (iii) the use of additive increase multiplicative decrease (AIMD) algorithms (famous for being the resource management in the transport control protocol) for the control of the number of units servicing workloads. The deployment of Dithen over Amazon EC2 spot instances is shown to be capable of processing more than 80,000 video transcoding, face detection and image processing tasks (equivalent to the processing of more than 116 GB of compressed data) for less than $1 in billing cost from EC2. Moreover, the proposed AIMD-based control mechanism, in conjunction with the Kalman estimates, is shown to provide for more than 27% reduction in EC2 spot instance cost against methods based on reactive resource estimation. Finally, Dithen is shown to offer a 38% to 500% reduction of the billing cost against the current state-of-the-art in CaaS platforms on Amazon EC2 (Amazon Lambda and Amazon Autoscale). A baseline version of Dithen is currently available at dithen.com.

Navega����o de rob�� m��vel em ambiente com humanos

Trabalho Final de Mestrado para obten����o do grau de Mestre em Engenharia Mec��nica

A visual system for distributed mosaics using an auvs fleet

The use of teams of Autonomous Underwater Vehicles for visual inspection tasks is a promising robotic field. The images captured by different robots can be also to aid in the localization/navigation of the fleet. In a previous work, a distributed localization system was presented based on the use of Augmented States Kalman Filter through the visual maps obtained by the fleet. In this context, this paper details a system for on-line construction of visual maps and its use to aid the localization and navigation of the robots. Different aspects related to the capture, treatment and construction of mosaics by fleets of robots are presented. The developed system can be executed on-line on different robotic platforms. The paper is concluded with a series of tests and analyses aiming at to system validation.

A Periodic State Space Model to Monthly Long-term Temperature Data

This work presents a periodic state space model to model monthly temperature data. Additionally, some issues are discussed, as the parameter estimation or the Kalman filter recursions adapted to a periodic model. This framework is applied to monthly long-term temperature time series of Lisbon.

Fatores associados e preditores de quedas em idosos domiciliados de acordo com a Classifica����o Internacional da Funcionalidade, Incapacidade e Sa��de

Objetivo geral da pesquisa foi identificar os fatores associados e preditivos de quedas em idosos domiciliados em uma cidade do Rio Grande do Sul, Brasil, considerando as caracter��sticas sociodemogr��ficas e epidemiol��gicas e utilizando-se de fatores ambientais da Classifica����o Internacional de Funcionalidade, Incapacidade e Sa��de (CIF). Objetivos espec��ficos: identificar as caracter��sticas sociodemogr��ficas e epidemiol��gicas de idosos domiciliados em uma cidade do Rio Grande do Sul, Brasil; descrever os fatores sociodemogr��ficos e epidemiol��gicos que influenciam nas quedas em idosos domiciliados; Relacionar os fatores ambientais da Classifica����o Internacional de Funcionalidade, Incapacidade e Sa��de em idosos domiciliados com riscos de quedas. Pesquisa epidemiol��gica transversal, ocorrida de junho a julho de 2013, com 167 idosos das ��reas de abrang��ncia de uma unidade b��sica de sa��de. Crit��rios de inclus��o na pesquisa: ambos os sexos, cadastrados e com resid��ncia fixa nas ��reas de abrang��ncia de uma unidade b��sica de sa��de. Crit��rios de exclus��o: idosos com altera����es cognitivas. Utilizou-se entrevista estruturada com tr��s etapas: levantamento das caracter��sticas dos idosos investigados; quest��es relacionadas ��s quedas; informa����es sobre os fatores ambientais da Classifica����o Internacional de Funcionalidade, Incapacidade e Sa��de. Os dados foram agrupados para tratamento estat��stico/descritivo. A m��dia das idades 71 anos, com desvio padr��o de 7,1. A maioria dos idosos era do sexo feminino, casados, com escolaridade de quatro e oito anos, residindo com filhos e companheiro, aposentados e com renda de um sal��rio m��nimo. As doen��as mais prevalentes foram circulat��rias, osteomusculares, e end��crinas e os idosos apresentaram pelo menos uma comorbidade. Dos 167 idosos, 65 ca��ram nos ��ltimos doze meses, no ambiente domiciliar, com preval��ncia em: banheiro, cozinha e na rua, sendo as cal��adas as mais destacadas. A maior propor����o de perman��ncia no ch��o foi de dez minutos, e a maioria dos idosos, ap��s as quedas, n��o procuraram os servi��os de sa��de. Como tratamento para as quedas, obteve-se o n��o cir��rgico. Quanto �� Classifica����o Internacional da Funcionalidade, Incapacidade e Sa��de, houve destaque para o uso de medica����es como fator influente nas quedas dos idosos domiciliados. Percebe-se a import��ncia de avalia����o constante por parte dos profissionais de sa��de sobre os idosos caidores e n��o-caidores, no sentido de identificar os fatores de riscos intr��nsecos e extr��nsecos para implementar estrat��gias de preven����o que compreendam reabilita����o da for��a muscular, equil��brio e capacidade funcional, redu����o da polifarm��cia, educa����o para o autocuidado e um olhar do enfermeiro voltado para os per��odos e locais de maior incid��ncia de quedas, melhorando desta forma a qualidade de vida dos idosos residentes em diferentes contextos. A pesquisa traz como contribui����o social um re-olhar acerca do redimensionamento do cuidado �� pessoa idosa que teve queda no pr��prio ambiente, a partir da Classifica����o Internacional de Funcionalidade, Incapacidade e Sa��de.

Real-Time Visual SLAM Using Pre - Existing Floor Lines as Landmarks and a Single Camera

SANTANA, Andr�� M.; SANTIAGO, Gutemberg S.; MEDEIROS, Adelardo A. D. Real-Time Visual SLAM Using Pre-Existing Floor Lines as Landmarks and a Single Camera. In: CONGRESSO BRASILEIRO DE AUTOM��TICA, 2008, Juiz de Fora, MG. Anais... Juiz de Fora: CBA, 2008.

A Monthly Volatility Index for the US Economy

We estimate the monthly volatility of the US economy from 1968 to 2006 by extending the coincidentindex model of Stock and Watson (1991). Our volatility index, which we call VOLINX, hasfour applications. First, it sheds light on the Great Moderation. VOLINX captures the decrease in thevolatility in the mid-80s as well as the different episodes of stress over the sample period. In the 70sand early 80s the stagflation and the two oil crises marked the pace of the volatility whereas 09/11 is themost relevant shock after the moderation. Second, it helps to understand the economic indicators thatcause volatility. While the main determinant of the coincident index is industrial production, VOLINXis mainly affected by employment and income. Third, it adapts the confidence bands of the forecasts.In and out-of-sample evaluations show that the confidence bands may differ up to 50% with respect to amodel with constant variance. Last, the methodology we use permits us to estimate monthly GDP, whichhas conditional volatility that is partly explained by VOLINX. These applications can be used by policymakers for monitoring and surveillance of the stress of the economy.

A deformation model of flexible, high area-to-mass ratio debris under perturbations and validation method

A new type of space debris was recently discovered by Schildknecht in near -geosynchronous orbit (GEO). These objects were later identified as exhibiting properties associated with High Area-to-Mass ratio (HAMR) objects. According to their brightness magnitudes (light curve), high rotation rates and composition properties (albedo, amount of specular and diffuse reflection, colour, etc), it is thought that these objects are multilayer insulation (MLI). Observations have shown that this debris type is very sensitive to environmental disturbances, particularly solar radiation pressure, due to the fact that their shapes are easily deformed leading to changes in the Area-to-Mass ratio (AMR) over time. This thesis proposes a simple effective flexible model of the thin, deformable membrane with two different methods. Firstly, this debris is modelled with Finite Element Analysis (FEA) by using Bernoulli-Euler theory called ���Bernoulli model���. The Bernoulli model is constructed with beam elements consisting 2 nodes and each node has six degrees of freedom (DoF). The mass of membrane is distributed in beam elements. Secondly, the debris based on multibody dynamics theory call ���Multibody model��� is modelled as a series of lump masses, connected through flexible joints, representing the flexibility of the membrane itself. The mass of the membrane, albeit low, is taken into account with lump masses in the joints. The dynamic equations for the masses, including the constraints defined by the connecting rigid rod, are derived using fundamental Newtonian mechanics. The physical properties of both flexible models required by the models (membrane density, reflectivity, composition, etc.), are assumed to be those of multilayer insulation. Both flexible membrane models are then propagated together with classical orbital and attitude equations of motion near GEO region to predict the orbital evolution under the perturbations of solar radiation pressure, Earth���s gravity field, luni-solar gravitational fields and self-shadowing effect. These results are then compared to two rigid body models (cannonball and flat rigid plate). In this investigation, when comparing with a rigid model, the evolutions of orbital elements of the flexible models indicate the difference of inclination and secular eccentricity evolutions, rapid irregular attitude motion and unstable cross-section area due to a deformation over time. Then, the Monte Carlo simulations by varying initial attitude dynamics and deformed angle are investigated and compared with rigid models over 100 days. As the results of the simulations, the different initial conditions provide unique orbital motions, which is significantly different in term of orbital motions of both rigid models. Furthermore, this thesis presents a methodology to determine the material dynamic properties of thin membranes and validates the deformation of the multibody model with real MLI materials. Experiments are performed in a high vacuum chamber (10-4 mbar) replicating space environment. A thin membrane is hinged at one end but free at the other. The free motion experiment, the first experiment, is a free vibration test to determine the damping coefficient and natural frequency of the thin membrane. In this test, the membrane is allowed to fall freely in the chamber with the motion tracked and captured through high velocity video frames. A Kalman filter technique is implemented in the tracking algorithm to reduce noise and increase the tracking accuracy of the oscillating motion. The forced motion experiment, the last test, is performed to determine the deformation characteristics of the object. A high power spotlight (500-2000W) is used to illuminate the MLI and the displacements are measured by means of a high resolution laser sensor. Finite Element Analysis (FEA) and multibody dynamics of the experimental setups are used for the validation of the flexible model by comparing with the experimental results of displacements and natural frequencies.

Numerical methods for solar tomography in the STEREO era

In this thesis, we propose several advances in the numerical and computational algorithms that are used to determine tomographic estimates of physical parameters in the solar corona. We focus on methods for both global dynamic estimation of the coronal electron density and estimation of local transient phenomena, such as coronal mass ejections, from empirical observations acquired by instruments onboard the STEREO spacecraft. We present a first look at tomographic reconstructions of the solar corona from multiple points-of-view, which motivates the developments in this thesis. In particular, we propose a method for linear equality constrained state estimation that leads toward more physical global dynamic solar tomography estimates. We also present a formulation of the local static estimation problem, i.e., the tomographic estimation of local events and structures like coronal mass ejections, that couples the tomographic imaging problem to a phase field based level set method. This formulation will render feasible the 3D tomography of coronal mass ejections from limited observations. Finally, we develop a scalable algorithm for ray tracing dense meshes, which allows efficient computation of many of the tomographic projection matrices needed for the applications in this thesis.

A four-dimensional analysis of the thermal structure in the Gulf of Lion

The Theoretical and Experimental Tomography in the Sea Experiment (THETIS 1) took place in the Gulf of Lion to observe the evolution of the temperature field and the process of deep convection during the 1991-1992 winter. The temperature measurements consist, of moored sensors, conductivity-temperature-depth and expendable bathythermograph surveys, ana acoustic tomography. Because of this diverse data set and since the field evolves rather fast, the analysis uses a unified framework, based on estimation theory and implementing a Kalman filter. The resolution and the errors associated with the model are systematically estimated. Temperature is a good tracer of water masses. The time-evolving three-dimensional view of the field resulting from the analysis shows the details of the three classical convection phases: preconditioning, vigourous convection, and relaxation. In all phases, there is strong spatial nonuniformity, with mesoscale activity, short timescales, and sporadic evidence of advective events (surface capping, intrusions of Levantine Intermediate Water (LIW)). Deep convection, reaching 1500 m, was observed in late February; by late April the field had not yet returned to its initial conditions (strong deficit of LIW). Comparison with available atmospheric flux data shows that advection acts to delay the occurence of convection and confirms the essential role of buoyancy fluxes. For this winter, the deep. mixing results in an injection of anomalously warm water (Delta T similar or equal to 0.03 degrees) to a depth of 1500 m, compatible with the deep warming previously reported.

Data-Driven Wildfire Propagation Modeling with FARSITE-EnKF

The goal of this study is to provide a framework for future researchers to understand and use the FARSITE wildfire-forecasting model with data assimilation. Current wildfire models lack the ability to provide accurate prediction of fire front position faster than real-time. When FARSITE is coupled with a recursive ensemble filter, the data assimilation forecast method improves. The scope includes an explanation of the standalone FARSITE application, technical details on FARSITE integration with a parallel program coupler called OpenPALM, and a model demonstration of the FARSITE-Ensemble Kalman Filter software using the FireFlux I experiment by Craig Clements. The results show that the fire front forecast is improved with the proposed data-driven methodology than with the standalone FARSITE model.

Evaluating tests for convergence of economic series using Monte Carlo methods with an application to real GDP's per head.

Doutoramento em Economia.