997 resultados para Multiple-Lane Trafficways.


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Federal Highway Administration, Safety Design Division, McLean, Va.

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Federal Highway Administration, Washington, D.C.

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Federal Highway Administration, Office of Safety and Traffic Operations Research and Development, Washington, D.C.

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Federal Highway Administration, Safety Design Division, McLean, Va.

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O número de acidentes de trânsito é crescente nas últimas décadas no Brasil. Uma das principais causas de acidentes em rodovias brasileiras é o excesso de velocidade, que contribui para a possibilidade de ocorrência de acidentes. As velocidades praticadas pelos motoristas são também função dos elementos geométricos que compõem a via (raio, rampa, largura da faixa, etc). A consistência de traçado não afeta a expectativa dos motoristas e garante uma operação segura. A maioria dos motoristas consegue perceber as falhas de coordenação, mas tecnicamente, por exemplo, desconhecem a origem das mesmas. Esta pesquisa apresenta como objetivo a análise de consistência de um trecho de uma determinada rodovia do país de múltiplas faixas, com elevado índice de acidentes e alto fluxo de veículos comerciais. Os pontos com maior ocorrência de acidentes foram identificados e realizaram-se medições de velocidade para elaboração de um modelo de previsão de velocidade operacional (V85) do trecho de estudo. De posse deste modelo, procedeu-se à análise de consistência através do método dos critérios de segurança, que identificou 2 seções com problemas de consistência. Por fim, verificou-se se estas seções correspondiam aos locais de maior número de acidentes: a tangente T5 precede uma curva com alto índice de acidentes (km 511+000); o local com maior concentração de acidentes (km 514) foi classificado como RAZOÁVEL.

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Federal Highway Administration, Office of Research and Development, Washington, D.C.

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Federal Highway Administration, Office of Research, Washington, D.C.

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Federal Highway Administration, Traffic Systems Division, Washington, D.C.

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Turner-Fairbank Highway Research Center, McLean, Va.

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Federal Highway Administration, Washington, D.C.

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

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Federal Highway Administration, Washington, D.C.

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The rural two-lane highway in the southeastern United States is frequently associated with a disproportionate number of serious and fatal crashes and as such remains a focus of considerable safety research. The Georgia Department of Transportation spearheaded a regional fatal crash analysis to identify various safety performances of two-lane rural highways and to offer guidance for identifying suitable countermeasures with which to mitigate fatal crashes. The fatal crash data used in this study were compiled from Alabama, Georgia, Mississippi, and South Carolina. The database, developed for an earlier study, included 557 randomly selected fatal crashes from 1997 or 1998 or both (this varied by state). Each participating state identified the candidate crashes and performed physical or video site visits to construct crash databases with enhance site-specific information. Motivated by the hypothesis that single- and multiple-vehicle crashes arise from fundamentally different circumstances, the research team applied binary logit models to predict the probability that a fatal crash is a single-vehicle run-off-road fatal crash given roadway design characteristics, roadside environment features, and traffic conditions proximal to the crash site. A wide variety of factors appears to influence or be associated with single-vehicle fatal crashes. In a model transferability assessment, the authors determined that lane width, horizontal curvature, and ambient lighting are the only three significant variables that are consistent for single-vehicle run-off-road crashes for all study locations.

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A new community and communication type of social networks - online dating - are gaining momentum. With many people joining in the dating network, users become overwhelmed by choices for an ideal partner. A solution to this problem is providing users with partners recommendation based on their interests and activities. Traditional recommendation methods ignore the users’ needs and provide recommendations equally to all users. In this paper, we propose a recommendation approach that employs different recommendation strategies to different groups of members. A segmentation method using the Gaussian Mixture Model (GMM) is proposed to customize users’ needs. Then a targeted recommendation strategy is applied to each identified segment. Empirical results show that the proposed approach outperforms several existing recommendation methods.