Statistical classification of road pavements using near field vehicle rolling noise measurements

Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.

Size-segregated chemical composition of aerosol emissions in an urban road tunnel in Portugal

An atmospheric aerosol study was performed in 2008 inside an urban road tunnel, in Lisbon, Portugal. Using a high volume impactor, the aerosol was collected into four size fractions (PM0.5, PM0.5-1, PM1-2.5 and PM2.5-10) and analysed for particle mass (PM), organic and elemental carbon (OC and EC), polycyclic aromatic hydrocarbons (PAH), soluble inorganic ions and elemental composition. Three main groups of compounds were discriminated in the tunnel aerosol: carbonaceous, soil component and vehicle mechanical wear. Measurements indicate that Cu can be a good tracer for wear emissions of road traffic. Cu levels correlate strongly with Fe, Mn, Sn and Cr, showing a highly linear constant ratio in all size ranges, suggesting a unique origin through sizes. Ratios of Cu with other elements can be used to source apportion the trace elements present in urban atmospheres, mainly on what concerns coarse aerosol particles. (C) 2013 Elsevier Ltd. All rights reserved.

Implementation of thr INSPIRE Directive on road infrastructure in Portugal

Prémio - CEN/TC 287 AWARD FOR EXCELLENCE IN INSIRE 2012 Implementation of the INSPIRE Directive on Road Infrastructure in Portugal Inês Soares, aluna de Mestrado em engenharia civil do ISEL, Instituto Superior de Engenharia de Lisboa e Paulo Martins, e o seu orientador, receberam um prémio europeu, no dia 27 de junho, em Istambul na Turquia, numa conferência internacional organizada pela Comissão Europeia e pelo governo Turco.  A jovem portuguesa foi escolhida entre cerca de 20 candidatos de vários países. Paulo Matos Martins, professor no ISEL, além de mentor do trabalho premiado, foi orientador de mestrado da aluna e explica que se trata de um estudo sobre a aplicação da Diretiva comunitária INSPIRE à infraestrutura rodoviária nacional que contou com a estreita colaboração do InIR, Instituto da Infraestrutura Rodoviária através da coorientação da engenheira Adelaide Costa e colaboração técnica do engenheiro Rui Luso Soares.  O projeto-piloto correspondeu à criação de uma aplicação informática que permite aceder a informação geográfica harmonizada relativa à infraestrutura rodoviária nacional, de acordo com as disposições de execução INSPIRE, dando cumprimento aos requisitos impostos pela Diretiva às entidades responsáveis por este tipo de informação, entre as quais se incluem diversos organismos públicos (podendo no futuro vir a incluir as autarquias), permitindo aos decisores políticos e a todos os cidadãos o fácil acesso a informação de qualidade sobre as infraestruturas, o território e o ambiente. 

Road lane detection for autonomous robot guidance

Computational Vision stands as the most comprehensive way of knowing the surrounding environment. Accordingly to that, this study aims to present a method to obtain from a common webcam, environment information to guide a mobile differential robot through a path similar to a roadway.

A Spatial Econometrics Analysis for Road Accidents in Lisbon

This paper presents a spatial econometrics analysis for the number of road accidents with victims in the smallest administrative divisions of Lisbon, considering as a baseline a log-Poisson model for environmental factors. Spatial correlation on data is investigated for data alone and for the residuals of the baseline model without and with spatial-autocorrelated and spatial-lagged terms. In all the cases no spatial autocorrelation was detected.

Road lane detection for autonomous robot guidance

Computational Vision stands as the most comprehensive way of knowing the surrounding environment. Accordingly to that, this study aims to present a method to obtain from a common webcam, environment information to guide a mobile differential robot through a path similar to a roadway.

Processos de avaliação dos pavimentos rodoviários: Caso de estudo: reforço do pavimento em dois trechos do sublanço Enxara/Torres Vedras Sul

Relatório de Estágio Curricular para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Vias de Comunicação e Transportes