• español 
    • español
    • English
    • français
  • FacebookPinterestTwitter
  • español
  • English
  • français
Ver ítem 
  •   DIGIBUG Principal
  • 1.-Investigación
  • Departamentos, Grupos de Investigación e Institutos
  • Grupo: Transporte y Seguridad (TEP246)
  • TEP246 - Artículos
  • Ver ítem
  •   DIGIBUG Principal
  • 1.-Investigación
  • Departamentos, Grupos de Investigación e Institutos
  • Grupo: Transporte y Seguridad (TEP246)
  • TEP246 - Artículos
  • Ver ítem
JavaScript is disabled for your browser. Some features of this site may not work without it.

Injury severity models for motor vehicle accidents: a review

[PDF] 2013 Transport-ICE RANDA.pdf (266.1Kb)
Identificadores
URI: http://hdl.handle.net/10481/24455
ISSN: 0965-092X
ISSN: 1751-7710
Exportar
RISRefworksMendeleyBibtex
Estadísticas
Ver Estadísticas de uso
Metadatos
Mostrar el registro completo del ítem
Autor
Mujalli, Randa Oqab; Oña López, Juan José De
Editorial
Thomas Telford
Materia
Traffic accident
 
Models
 
Review
 
Severity
 
Fecha
2013
Referencia bibliográfica
Mujalli, R.O.; de Oña, J. Injury severity models for motor vehicle accidents: a review. Proceedings of the Institution of Civil Engineers- Transport, (2013). [http://hdl.handle.net/10481/24455]
Patrocinador
TRYSE Research Group, Department of Civil Engineering, University of Granada, Spain
Resumen
Modelling of traffic accidents injury severity is a complex task. In the last few years the number and variety of studies that analyse injury severity of traffic accidents have increased considerably. In this paper 19 modelling techniques used to model injury severity of traffic accidents where at least a 4-wheeled vehicle is involved have been analysed. The analysis and the comparison between models was performed based on seven criteria (modelling technique, number of records, number of variables, area type, features, injury level and model fit). In general, it is not possible to recommend a method that could be identified as the best one. Each modelling technique has its own limitations and characteristics, awareness of which will help analysts to decide the best method to be used in each particular modelling problem. However, some general conclusions can be established: in most cases the results of models’ fits are found to be satisfactory, though not excellent; in the case of data mining models, accuracy improves with balanced datasets; and no correlation was found to exist between the number of accident records and the number of analysed variables.
Colecciones
  • TEP246 - Artículos

Mi cuenta

AccederRegistro

Listar

Todo DIGIBUGComunidades y ColeccionesPor fecha de publicaciónAutoresTítulosMateriaFinanciaciónPerfil de autor UGREsta colecciónPor fecha de publicaciónAutoresTítulosMateriaFinanciación

Estadísticas

Ver Estadísticas de uso

Servicios

Pasos para autoarchivoAyudaLicencias Creative CommonsSHERPA/RoMEODulcinea Biblioteca UniversitariaNos puedes encontrar a través deCondiciones legales

Contacto | Sugerencias