Highlights This paper examines driver injury severities in rollover crashes in New Mexico. A CART model is utilized to select the most important factors on injury severity. SVM models with polynomial and Gaussian RBF kernels are trained. The cubic SVM model is used to assess variable influences on injury severity. This study provides insights on casualty prevention in rollover crashes.

    Abstract Rollover crash is one of the major types of traffic crashes that induce fatal injuries. It is important to investigate the factors that affect rollover crashes and their influence on driver injury severity outcomes. This study employs support vector machine (SVM) models to investigate driver injury severity patterns in rollover crashes based on two-year crash data gathered in New Mexico. The impacts of various explanatory variables are examined in terms of crash and environmental information, vehicle features, and driver demographics and behavior characteristics. A classification and regression tree (CART) model is utilized to identify significant variables and SVM models with polynomial and Gaussian radius basis function (RBF) kernels are used for model performance evaluation. It is shown that the SVM models produce reasonable prediction performance and the polynomial kernel outperforms the Gaussian RBF kernel. Variable impact analysis reveals that factors including comfortable driving environment conditions, driver alcohol or drug involvement, seatbelt use, number of travel lanes, driver demographic features, maximum vehicle damages in crashes, crash time, and crash location are significantly associated with driver incapacitating injuries and fatalities. These findings provide insights for better understanding rollover crash causes and the impacts of various explanatory factors on driver injury severity patterns.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Investigating driver injury severity patterns in rollover crashes using support vector machine models


    Contributors:
    Chen, Cong (author) / Zhang, Guohui (author) / Qian, Zhen (author) / Tarefder, Rafiqul A. (author) / Tian, Zong (author)

    Published in:

    Publication date :

    2016-02-17


    Size :

    12 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    Injury Severity, Ejection, and Occupant Contacts in Passenger Car Rollover Crashes

    Compton, Charles / Huelke, Donald F. / Studer, Richard M. | SAE Technical Papers | 1985


    Injury Severity, Ejection, and Occupant Contacts in Passenger Car Rollover Crashes

    Huelke,D.F. / Compton,C. / Studer,R.M. et al. | Automotive engineering | 1985


    Passenger Car Weight and Injury Severity in Single Vehicle Non-Rollover Crashes

    Partyka, S. / Boehly, W. | British Library Conference Proceedings | 1996