Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Applying Decision Trees and Logistic Regression to the Analysis of the Dependence of Crash Collisions on Concomitant Factors
Year:2016
Research Areas
  • Engineering
Information
Abstract
The purpose of this paper is to apply two different statistical methodologies, decision trees and logistic regression, to the analysis of the severity of road accidents along two high-use interurban freight corridors in Spain, Madrid-Irún and Barcelona-Almería. The two corridors mentioned above are part of two international rail freight Corridors across Spain and are considered as possible subjects of policy freight transport policy changes, namely the shift from road to rail to increase safety and decrease emissions [1]. The interest of the analysis relies to a certain extent in comparing the results of two different statistical approaches since decision trees are a non-parametric, machine learning sort of technique, while logistic regression is a traditional parametric approach. The study has focused on four different crash types: headon crashes, angle crashes, sideswipe crashes and rear-end crashes. The explanatory variables introduced in the models can be classified in roadway design characteristics, driver related behavior, location and state of road variables.
International
No
Congress
FUNDACIÓN GENERAL DE LA UPM
960
Place
Reviewers
Si
ISBN/ISSN
978-84-16397-46-4
Start Date
17/11/2016
End Date
18/11/2016
From page
119
To page
122
Proceedings of the First Symposium SEGVAUTO-TRIES-CM. Technologies for a Safe, Accessible and Sustainable Mobility. R&D+I in Automotive: RESULTS
Participants
  • Autor: Francisco Aparicio Izquierdo (UPM)
  • Autor: Blanca del Valle Arenas Ramirez (UPM)
  • Autor: Bahar Dadashova (Texas A)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Inv. en Seguridad e Impacto Medioambiental de Vehículos y Transportes (GIVET)
  • Centro o Instituto I+D+i: Instituto Universitario de Investigación del Automóvil (INSIA)
  • Departamento: Ingeniería Mecánica
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