Measuring the Potential to Reduce Crash Frequency of Urban Segments by a Probabilistic Approach

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2013

Autores

Sara Ferreira (Autor) FEUP; António Fidalgo Couto (Autor) FEUP

Ata de Conferência Internacional

Título: Road Safety and Simulation

Páginas: 0-13

Road Safety and Simulation International Conference

Roma, Italy, 22 a 25 de Outubro de 2013

Indexação

ISI Proceedings

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia civil

CORDIS: Ciências Tecnológicas > Engenharia > Engenharia civil

Outras Informações

Abstract (EN): This paper presents a probabilistic approach to measure the potential to reduce crash frequency of urban segments. This new approach leads to a hotspot definition and identification using a probabilistic model defining the dependent variable as an indicator of a discrete choice. A binary choice model is used considering a binary dependent variable that differentiates a hotspot from a safe site set by the number of crashes per kilometre. The explanatory variables to set similar segments are based on average annual daily traffic, segment length, density of minor intersections. A threshold value for the number of crashes per kilometre is set to distinguish hotspots from safe sites. Based on this classification, a binary model is applied that allows the construction of an ordered site list using the probability of a site being a hotspot. A demonstration of the proposed methodology is provided using simulated data. For the simulation design, urban segment data from Porto, Portugal, covering a five-year period are used. The results of the binary model show a good fit. To evaluate and compare the probabilistic method with other used methods described in the Highway Safety Manual, measures are used to test the performance of each method in terms of its power to detect the “true” hotspots. As already demonstrated through the application of the binary model to urban intersections, the test results indicate that the binary model performs better than the other two models. The gains of using this method are the simplicity, the reliability, and the efficiency.

Idioma: Inglês

Tipo (Avaliação Docente): Científica