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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/5269

    Título
    Cyclist Injury Severity in Spain: A Bayesian Analysis of Police Road Injury Data Focusing on Involved Vehicles and Route Environment
    Autor
    Aldred, Rachel
    García Herrero, SusanaAutoridad UBU Orcid
    Anaya Boig, Esther
    Herrera, Sixto
    Mariscal Saldaña, Miguel ÁngelAutoridad UBU Orcid
    Publicado en
    International Journal of Environmental Research and Public Health. 2020, V. 17, n. 2, 96
    Editorial
    MDPI
    Fecha de publicación
    2019-12
    DOI
    10.3390/ijerph17010096
    Resumen
    This study analyses factors associated with cyclist injury severity, focusing on vehicle type, route environment, and interactions between them. Data analysed was collected by Spanish police during 2016 and includes records relating to 12,318 drivers and cyclist involving in collisions with at least one injured cyclist, of whom 7230 were injured cyclists. Bayesian methods were used to model relationships between cyclist injury severity and circumstances related to the crash, with the outcome variable being whether a cyclist was killed or seriously injured (KSI) rather than slightly injured. Factors in the model included those relating to the injured cyclist, the route environment, and involved motorists. Injury severity among cyclists was likely to be higher where an Heavy Goods Vehicle (HGV) was involved, and certain route conditions (bicycle infrastructure, 30 kph zones, and urban zones) were associated with lower injury severity. Interactions exist between the two: collisions involving large vehicles in lower-risk environments are less likely to lead to KSIs than collisions involving large vehicles in higher-risk environments. Finally, motorists involved in a collision were more likely than the injured cyclists to have committed an error or infraction. The study supports the creation of infrastructure that separates cyclists from motor tra c. Also, action needs to be taken to address motorist behaviour, given the imbalance between responsibility and risk.
    Palabras clave
    Cycling
    Road safety
    Injured cyclist
    Bayesian network
    Data mining
    Materia
    Transportes
    Transportation
    URI
    http://hdl.handle.net/10259/5269
    Versión del editor
    http://dx.doi.org/10.3390/ijerph17010096
    Aparece en las colecciones
    • Artículos IOI
    Atribución 4.0 Internacional
    Documento(s) sujeto(s) a una licencia Creative Commons Atribución 4.0 Internacional
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    Nombre:
    Aldred-ijerph_2020.pdf
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    656.5Kb
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