Given the lack of protective structural barriers and advanced restraints, motorcyclists are vulnerable road users. In 2020 in the United States, motorcycle-involved fatalities occurred 28 times more frequently per vehicle mile traveled than passenger car occupant fatalities, causing 5,579 motorcycle-related fatalities—the highest number of motorcyclists killed since 1975. By identifying patterns and relationships between key contributing factors, strategies for reducing motorcycle crashes can be developed. In addition to current efforts, additional research must be conducted using innovative avenues, with increased funding. Bayesian networks can better discover the relationships between potential speed compliance variables. This study used six years (2014 to 2019) of motorcycle crash data in Louisiana to determine the conditional probabilities of the influential factors. In addition to the high contribution of alcohol involvement, two-way undivided roadways, 35 to 44 year-old drivers involved in improper driving behaviors, and crash types are the underlying factors associated with a considerable increase in motorcycle crash severity. The findings of this study can also be used for decision making and strategy development for motorcycle safety.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Bayesian Network for Motorcycle Crash Severity Analysis


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2023-04-04




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Motorcycle Crash Severity Estimation for Effective Emergency Response

    Rao, Aditya N / Notani, Vipul / Muralidharan, Vishal | British Library Conference Proceedings | 2022



    Motorcycle Crash Severity Estimation for Effective Emergency Response

    Rao, Aditya N / Notani, Vipul / Muralidharan, Vishal | SAE Technical Papers | 2022


    Comparison of moped, scooter and motorcycle crash risk and crash severity

    Blackman, Ross A. / Haworth, Narelle L. | Elsevier | 2013