Highlights This research aims to identify the affiliated factors of emergency vehicle crashes. Association rule mining was applied to analyze crashes obtained from FARS and CRSS. The fatal consequences of speeding with no seatbelt usage were evident. Emergency vehicle crashes involving pedestrians are frequent in dark-lighted conditions. The findings can guide in developing strategies to improve safety of first responders.

    Abstract Emergency vehicle crashes, involving police vehicles, ambulances, and fire trucks, pose a serious traffic safety concern causing severe injury and deaths to first responders and other road users. However, limited research is available focusing on the contributing factors and their interactions related to these crashes. This research aims to address this gap by 1) identifying patterns of emergency vehicle crashes based on severity levels in both emergency and non-emergency modes and 2) comparing the associations by response modes for the related fatal, nonfatal injury, and no-injury crashes. Two national crash databases, Fatality Analysis Reporting System (FARS) and Crash Report Sampling System (CRSS), were utilized for police-reported emergency vehicle crashes from January 2016 to February 2020. Association rule mining (ARM) was employed to reveal the association between factors that strongly contributed to these crashes. The generated rules were validated using the lift increase criterion (LIC). The results showed the complex nature of risk factors influencing the severity of emergency vehicle crashes. The fatal consequences of speeding with no seatbelt usage were evident for emergency mode, whereas none of these risky driving attributes was observed for non-emergency mode. In addition, the analysis identified the risk of fatal emergency vehicle crashes involving pedestrians in dark-lighted conditions in both response modes. Regarding nonfatal injury severity, angle collisions were more likely to occur at urban intersections during emergencies, while rear-end crashes were more frequent on segments with a posted speed limit of 40–45 mph during non-emergency incidents. The outcomes also revealed that the no-injury crashes involving fire trucks exhibited different patterns depending on the response mode. The findings of this study can guide in making effective strategies to improve safe driving behavior of first responders. The identified associations provide insights into the factors that can be controlled to ensure safe operation of emergency vehicles on the road.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Data mining approach to explore emergency vehicle crash patterns: A comparative study of crash severity in emergency and non-emergency response modes


    Contributors:


    Publication date :

    2023-07-06




    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


    MEDICAL EMERGENCY CRASH CART

    JANICK JAMES J / WELCH ROBERT J / STEELE ROBERT R et al. | European Patent Office | 2017

    Free access

    Crash detection and severity classification system implementing emergency assistance

    CALL SHAWN M / JACOB MICHAEL / CHRISTENSEN SCOTT T et al. | European Patent Office | 2016

    Free access

    Crash detection and severity classification system implementing emergency assistance

    CALL SHAWN M / JACOB MICHAEL SHAWN / CHRISTENSEN SCOTT T et al. | European Patent Office | 2019

    Free access