Análise comparativa das medidas de desempenho para identificação de pontos críticos: aplicação em interseções semaforizadas

• Ano de defesa: 2016
• Autor(a) principal: Xavier, Vanessa Jamille Mesquita
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Transportes; Trânsito - Sinais e sinalização; Medidas de segurança; Segurança no trânsito; Performance measures; Signalized intersections; Road safety; Methods of critical
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/28635

The overall effectiveness of the roadway safety management process relies on a robust method for identifying and ranking sites with major potential for safety improvements. In Brazil, manuals for hotspot identification are usually based only on crash frequency and crash rate as safety performance measures. The Highway Safety Manual proposes 13 performance measures for hotspot identification which require different levels of completeness and accuracy of accident data systems as well as different modeling skills from safety staff. It is common that jurisdictions in the infant stage of the roadway safety management process would apply less informative safety performance measures. This study presents a comparative analysis of safety performance measure taking into account its limitations applicability to a sample of signalized intersections from the city of Fortaleza, Brazil. Crash data as well as traffic and geometric attributes for the years of 2009, 2010 and 2011 were used to estimate safety performance measures including those involving the development and application of safety performance functions. The performance of each measure to rank the sample intersection was achieved through the rank difference between each performance measure and the excess expected average crash frequency with empirical Bayes adjustment. In addition, it has taken a temporal analysis based on consistency of performance measures during subsequent time periods. The results have suggested a reasonable matching between the excess expected average crash frequency with empirical Bayes adjustment and very simple ones.