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Driving behaviors associated with emergency service vehicle crashes in the US fire service

机译:与紧急服务车辆相关的驾驶行为在美国消防服务中崩溃

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摘要

Objective: Emergency service vehicle incidents are a leading cause of firefighter fatalities and are also hazardous to civilian road users. Modifiable driving behaviors may be associated with emergency service vehicle incidents. The goal of this study was to use telematics to identify driving behaviors associated with crashes in the fire service. Methods: Forty-three emergency service vehicles in 2 fire departments were equipped with telematics devices (12 in Department A and 31 in Department B). The devices collected vehicle coordinates, speed, and g forces, which were monitored for exceptions to driving rules established by the fire departments regarding speeding, harsh braking, and hard cornering. Fire department administrative reports were used to identify vehicles involved in crashes and merged with daily telematics data. Penalized logistic regression was used to identify driving rules associated with crashes. Least absolute shrinkage and selection operator (LASSO) regression was used to generate a telematics-based risk index for emergency service vehicle incidents. Results: Nearly 1.1 million km of driving data and 44 crashes were recorded among the 2 departments during the study. Harsh braking was associated with increased odds of crash in Department A (odds ratio [OR] = 2.22; 95% confidence interval [CI], 1.09-4.51) and Department B (OR = 1.55; 95% CI, 1.12-2.15). For every kilometer of nonemergency speeding, the odds of crash increased by 35% in Department A (OR = 1.35; 95% CI, 1.03-1.77) and by over 2-fold in Department B (OR = 2.09; 95% CI, 1.19-3.66). In Department B, hard cornering (OR = 1.14; 95% CI, 1.03-1.26) and emergency speeding (OR = 1.65; 95% CI, 1.06-2.57) were also associated with increased odds of crash. The final LASSO risk index model had a sensitivity of 73% and specificity of 57%. Conclusions: Harsh braking and excessive speeding were driving behaviors most associated with crash in the fire service. Telematics may be a useful tool for monitoring driver safety in the fire service.
机译:目的:紧急服务车辆事件是消防员死亡事故的主要原因,对民用道路使用者也有害。可修改的驾驶行为可能与紧急服务车辆事件相关联。本研究的目标是使用远程学习,以确定与消防服务中崩溃相关的驾驶行为。方法:2辆消防部门的四十三辆紧急服务车辆配备了远程信息处理装置(Department A和Department B 31)。该器件收集了车辆坐标,速度和G部门,这些速度和G部队被监测到了消防部门建立的关于超速,苛刻制动和硬转弯的驾驶规则的例外。消防部门行政报告用于识别涉及崩溃的车辆,并与日常远程信息处理数据合并。惩罚的后勤回归用于确定与崩溃相关的驾驶规则。最不绝对的收缩和选择运营商(套索)回归用于生成基于远程服务车辆事件的远程风险指标。结果:在研究期间,2个部门之间录制了近110万公里的驾驶数据和44辆崩溃。苛刻的制动与部门A的崩溃几率增加有关(差距[或] = 2.22; 95%置信区间[CI],1.09-4.51)和部门B(或= 1.55; 95%CI,1.12-2.15)。对于每公里的非动力超速,崩溃的几率在部门A(或= 1.35; 95%CI,1.03-1.77)和部门B(或= 2.09; 95%CI,1.19中)增加了35% -3.66)。在部门B中,硬转弯(或= 1.14; 95%CI,1.03-1.26)和紧急加速(或= 1.65; 95%CI,1.06-2.57)也与崩溃的增加有关。最终套索风险指数模型的敏感性为73%,特异性为57%。结论:苛刻的制动和过度超速的推动在消防服务中大多数与撞击相关的行为。远程信息处理可能是监控消防服务中的驱动程序安全的有用工具。

著录项

  • 来源
    《Traffic Injury Prevention》 |2018年第8期|共7页
  • 作者单位

    Univ Arizona Dept Epidemiol &

    Biostat Mel &

    Enid Zuckerman Coll Publ Hlth 1295 N Martin Ave Campus POB 245210 Drachman Hall Tucson AZ 85724 USA;

    Univ Arizona Dept Epidemiol &

    Biostat Mel &

    Enid Zuckerman Coll Publ Hlth 1295 N Martin Ave Campus POB 245210 Drachman Hall Tucson AZ 85724 USA;

    Univ Arizona Dept Epidemiol &

    Biostat Mel &

    Enid Zuckerman Coll Publ Hlth 1295 N Martin Ave Campus POB 245210 Drachman Hall Tucson AZ 85724 USA;

    Johns Hopkins Bloomberg Sch Publ Hlth Johns Hopkins Ctr Injury Res &

    Policy Baltimore MD USA;

    Univ Arizona Mel &

    Enid Zuckerman Coll Publ Hlth Dept Community Environm &

    Policy Tucson AZ 85724 USA;

    Northwestern Univ Dept Ophthalmol Feinberg Sch Med Chicago IL 60611 USA;

    Seattle Fire Dept Seattle WA USA;

    Univ Arizona Mel &

    Enid Zuckerman Coll Publ Hlth Dept Community Environm &

    Policy Tucson AZ 85724 USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 特种医学;
  • 关键词

    Emergency vehicles; driving behaviors; firefighters; crash prevention; telematics; risk index;

    机译:应急车辆;驾驶行为;消防队员;防止碰撞;远程信息处理;风险指数;

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