936 resultados para On-Road


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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. 

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Proceedings IGLC-19, July 2011, Lima, Perú

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Introduction Occupational therapists could play an important role in facilitating driving cessation for ageing drivers. This, however, requires an easy-to-learn, standardised on-road evaluation method. This study therefore investigates whether use of P-drive' could be reliably taught to occupational therapists via a short half-day training session. Method Using the English 26-item version of P-drive, two occupational therapists evaluated the driving ability of 24 home-dwelling drivers aged 70 years or over on a standardised on-road route. Experienced driving instructors' on-road, subjective evaluations were then compared with P-drive scores. Results Following a short half-day training session, P-drive was shown to have almost perfect between-rater reliability (ICC2,1=0.950, 95% CI 0.889 to 0.978). Reliability was stable across sessions including the training phase even if occupational therapists seemed to become slightly less severe in their ratings with experience. P-drive's score was related to the driving instructors' subjective evaluations of driving skills in a non-linear manner (R-2=0.445, p=0.021). Conclusion P-drive is a reliable instrument that can easily be taught to occupational therapists and implemented as a way of standardising the on-road driving test.

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Vehicles running over vertebrates has been an increasing challenge to the local conservation of some herpetofauna. The Amphisbaenidae are fossorial reptiles which are poorly known ecologically. Biological and natural history data were obtained from three specimens of Amphisbaenia alba that were found dead along 8320 km survey of highways. The rarity of road kill and the importance of the species conservation are discussed.

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This paper presents the results of applying DRAG methodology to the identification of the main factors of influence on the number of injury and fatal accidents occurring on Spain’s interurban network. Nineteen independent variables have been included in the model grouped together under ten categories: exposure, infrastructure, weather, drivers, economic variables, vehicle stock, surveillance, speed and legislative measures. Highly interesting conclusions can be reached from the results on the basis of the different effects of a single variable on each of the accident types according to severity. The greatest influence revealed by the results is exposure, which together with inexperienced drivers, speed and an ageing vehicle stock, have a negative effect, while the increased surveillance on roads, the improvement in the technological features of vehicles and the proportion of high capacity networks have a positive effect, since the results obtained show a significant drop in accidents.

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The paper presents the main elements of a project entitled ICT-Emissions that aims at developing a novel methodology to evaluate the impact of ICT-related measures on mobility, vehicle energy consumption and CO2 emissions of vehicle fleets at the local scale, in order to promote the wider application of the most appropriate ICT measures. The proposed methodology combines traffic and emission modelling at micro and macro scales. These will be linked with interfaces and submodules which will be specifically designed and developed. A number of sources are available to the consortium to obtain the necessary input data. Also, experimental campaigns are offered to fill in gaps of information in traffic and emission patterns. The application of the methodology will be demonstrated using commercially available software. However, the methodology is developed in such a way as to enable its implementation by a variety of emission and traffic models. Particular emphasis is given to (a) the correct estimation of driver behaviour, as a result of traffic-related ICT measures, (b) the coverage of a large number of current vehicle technologies, including ICT systems, and (c) near future technologies such as hybrid, plug-in hybrids, and electric vehicles. The innovative combination of traffic, driver, and emission models produces a versatile toolbox that can simulate the impact on energy and CO2 of infrastructure measures (traffic management, dynamic traffic signs, etc.), driver assistance systems and ecosolutions (speed/cruise control, start/stop systems, etc.) or a combination of measures (cooperative systems).The methodology is validated by application in the Turin area and its capacity is further demonstrated by application in real world conditions in Madrid and Rome.

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In this study, a method for vehicle tracking through video analysis based on Markov chain Monte Carlo (MCMC) particle filtering with metropolis sampling is proposed. The method handles multiple targets with low computational requirements and is, therefore, ideally suited for advanced-driver assistance systems that involve real-time operation. The method exploits the removed perspective domain given by inverse perspective mapping (IPM) to define a fast and efficient likelihood model. Additionally, the method encompasses an interaction model using Markov Random Fields (MRF) that allows treatment of dependencies between the motions of targets. The proposed method is tested in highway sequences and compared to state-of-the-art methods for vehicle tracking, i.e., independent target tracking with Kalman filtering (KF) and joint tracking with particle filtering. The results showed fewer tracking failures using the proposed method.

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The assessment on introducing Longer and Heavier Vehicles (LHVs) on the road freight transport demand is performed in this paper by applying an integrated modeling approach composed of a Random Utility-Based Multiregional Input-Output model (RUBMRIO) and a road transport network model. The approach strongly supports the concept that changes in transport costs derived from the LHVs allowance as well as the economic structure of regions have both direct and indirect effects on the road freight transport system. In addition, we estimate the magnitude and extent of demand changes in the road freight transportation system by using the commodity-based structure of the approach to identify the effect on traffic flows and on pollutant emissions over the whole network of Spain by considering a sensitivity analysis of the main parameters which determine the share of Heavy-Goods Vehicles (HGVs) and LHVs. The results show that the introduction of LHVs will strengthen the competitiveness of the road haulage sector by reducing costs, emissions, and the total freight vehicles required.

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Vision-based object detection from a moving platform becomes particularly challenging in the field of advanced driver assistance systems (ADAS). In this context, onboard vision-based vehicle verification strategies become critical, facing challenges derived from the variability of vehicles appearance, illumination, and vehicle speed. In this paper, an optimized HOG configuration for onboard vehicle verification is proposed which not only considers its spatial and orientation resolution, but descriptor processing strategies and classification. An in-depth analysis of the optimal settings for HOG for onboard vehicle verification is presented, in the context of SVM classification with different kernels. In contrast to many existing approaches, the evaluation is realized in a public and heterogeneous database of vehicle and non-vehicle images in different areas of the road, rendering excellent verification rates that outperform other similar approaches in the literature.

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National Highway Traffic Safety Administration, Washington, D.C.

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"December 1994."

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National Highway Traffic Safety Administration, Crash Avoidance Division, Washington, D.C.

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Federal Highway Administration, Office of Safety and Traffic Operations Research and Development, McLean, Va.