The lower extremities of cyclists are the most vulnerable body parts in vehicle-bicycle traffic accidents. However, few studies have been conducted on the effects of vehicle front-end profile parameters on cyclist lower extremity injuries by using real accident data. This paper aimed to explore the correlation between the cyclist’s severe lower extremity injury (AIS2+) risk and impact speed, vehicle front-end profile variables, and cyclist parameters via using real cyclist accidents. A subsample of 390 cyclist accident cases with lower extremity injuries was selected from the German In-Depth Accident Study (GIDAS) to conduct statistical analysis. Furthermore, an independent samples t-test was performed to analyse the associations between the selected predictive parameters and the risk of cyclists with AIS2+ lower extremity injuries. Finally, the risk function for cyclists with AIS2+ lower extremity injuries was developed by using the logistic regression method. The research results indicated that vehicle impact speed, lower bumper height (LBH), bumper depth (BD), cyclist age, and weight were statistically significant factors for cyclists with AIS2+ lower extremity injuries. The higher vehicle speed, higher LBH and BD corresponded to a greater likelihood of the cyclist suffering an AIS2+ lower extremity injury. These findings contribute to developing more effective safety measures for vehicle front designs and establishing regulations to protect the lower extremities of cyclists.


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    Titel :

    A study on the cyclist lower extremity injury risk by using German in-depth accident data


    Weitere Titelangaben:

    B. Wang et al.
    International Journal of Crashworthiness


    Beteiligte:
    Wang, Bingyu (Autor:in) / Zou, Jun (Autor:in) / Meng, Xiange (Autor:in) / Han, Yong (Autor:in) / Wu, He (Autor:in) / Otte, Dietmar (Autor:in) / Peng, Qian (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    02.09.2024


    Format / Umfang :

    9 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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