Multivariate Modelling of Pedestrian Fatality Risk Through on the Spot Accident Investigation

Badea Romero, Alexandro; Furones Crespo, Arturo; Páez Ayuso, Francisco Javier y González Fernández, María Camino (2010). Multivariate Modelling of Pedestrian Fatality Risk Through on the Spot Accident Investigation. "International Journal of Automotive Technology", v. 11 (n. 5); pp. 711-720. ISSN 1229-9138. https://doi.org/10.1007/s12239-010-0084-3.

Descripción

Título: Multivariate Modelling of Pedestrian Fatality Risk Through on the Spot Accident Investigation
Autor/es:
  • Badea Romero, Alexandro
  • Furones Crespo, Arturo
  • Páez Ayuso, Francisco Javier
  • González Fernández, María Camino
Tipo de Documento: Artículo
Título de Revista/Publicación: International Journal of Automotive Technology
Fecha: Octubre 2010
Volumen: 11
Materias:
Palabras Clave Informales: On the spot accident investigation - Pedestrian safety - Accident reconstruction - Multivariate model
Escuela: E.T.S.I. Industriales (UPM)
Departamento: Ingeniería de Organización, Administración de Empresas y Estadística
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Pedestrians are the most vulnerable users of public roads and represent one of the largest groups of road casualties; their death rate around the world due to vehicle-pedestrian collisions is high and tending to rise. In Spain, as in other countries of the European Union, steps have been taken to reduce the number and consequences of such accidents, with encouraging results in recent years. A key to countering this concern is the accident research activity that has obtained remarkable achievements in different fields, especially when multidisciplinary approaches are taken. This paper describes the development of a multivariate model that is able to detect the most influential parameters on the consequences of vehicle-pedestrian collision and to quantify their impact on pedestrian fatality risk. First, an accident database containing detailed information and parameters of vehicle-pedestrian collisions in Madrid has been developed. The accidents were investigated on the spot by INSIA accident investigation teams and analyzed using advanced reconstruction techniques. The model was then developed with two components: (1) a classification tree that characterizes and selects the explanatory variables, identifying their interactions, and (2) a binary logistic regression to quantify the influence of each variable and interaction resulting from the classification tree. The whole model represents an important tool for identifying, quantifying and predicting the potential impact of measures aimed at reducing injuries in vehicle-pedestrian collisions.

Más información

ID de Registro: 8387
Identificador DC: http://oa.upm.es/8387/
Identificador OAI: oai:oa.upm.es:8387
Identificador DOI: 10.1007/s12239-010-0084-3
URL Oficial: http://www.springerlink.com/content/a164471v8lkl2070/
Depositado por: Memoria Investigacion
Depositado el: 26 Ago 2011 10:11
Ultima Modificación: 21 Abr 2017 14:00
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