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Evaluating impacts of different longitudinal driver assistance systems on reducing multi-vehicle rear-end crashes during small-scale inclement weather

机译:评估不同的纵向驾驶员辅助系统对减少小范围恶劣天气期间多车追尾事故的影响

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摘要

Multi-vehicle rear-end (MVRE) crashes during small-scale inclement (SSI) weather cause high fatality rates on freeways, which cannot be solved by traditional speed limit strategies. This study aimed to reduce MVRE crash risks during SSI weather using different longitudinal driver assistance systems (LDAS). The impact factors on MVRE crashes during SSI weather were firstly analyzed. Then, four LDAS, including Forward collision warning (FCW), Autonomous emergency braking (AEB), Adaptive cruise control (ACC) and Cooperative ACC (CACC), were modeled based on a unified platform, the Intelligent Driver Model (IDM). Simulation experiments were designed and a large number of simulations were then conducted to evaluate safety effects of different LDAS. Results indicate that the FCW and ACC system have poor performance on reducing WIRE crashes during SSI weather. The slight improvement of sight distance of FCW and the limitation of perception-reaction time of ACC lead the failure of avoiding MVRE crashes in most scenarios. The AEB system has the better effect due to automatic perception and reaction, as well as performing the full brake when encountering SSI weather. The CACC system has the best performance because wireless communication provides a larger sight distance and a shorter time delay at the sub-second level. Sensitivity analyses also indicated that the larger number of vehicles and speed changes after encountering SSI weather have negative impacts on safety performances. Results of this study provide useful information for accident prevention during SSI weather.
机译:小规模恶劣(SSI)天气期间的多车追尾(MVRE)撞车导致高速公路上的高死亡率,这是传统限速策略无法解决的。这项研究旨在使用不同的纵向驾驶员辅助系统(LDAS)降低SSI天气期间的MVRE撞车风险。首先分析了SSI天气期间MVRE坠毁的影响因素。然后,基于统一平台智能驾驶员模型(IDM),对四个LDAS进行建模,包括前向碰撞预警(FCW),自主紧急制动(AEB),自适应巡航控制(ACC)和协作ACC(CACC)。设计了仿真实验,然后进行了大量仿真以评估不同LDAS的安全效果。结果表明,FCW和ACC系统在减少SSI天气期间的WIRE崩溃方面性能较差。在大多数情况下,FCW视距的略微改善以及ACC的感知反应时间的限制导致无法避免MVRE崩溃。 AEB系统由于自动感知和反应,以及在遇到SSI天气时执行全制动,效果更好。 CACC系统具有最佳性能,因为无线通信在亚秒级提供了更大的可视距离和更短的时间延迟。敏感性分析还表明,遇到SSI天气后,车辆数量和速度变化较大,会对安全性能产生负面影响。这项研究的结果为SSI天气期间的事故预防提供了有用的信息。

著录项

  • 来源
    《Accident Analysis & Prevention》 |2017年第10期|63-76|共14页
  • 作者单位

    Southeast Univ, Sch Transportat, 2 Si Pai Lou, Nanjing 210096, Jiangsu, Peoples R China;

    Southeast Univ, Sch Transportat, 2 Si Pai Lou, Nanjing 210096, Jiangsu, Peoples R China;

    Southeast Univ, Sch Transportat, 2 Si Pai Lou, Nanjing 210096, Jiangsu, Peoples R China;

    Southeast Univ, Sch Transportat, 2 Si Pai Lou, Nanjing 210096, Jiangsu, Peoples R China;

    Southeast Univ, Sch Transportat, 2 Si Pai Lou, Nanjing 210096, Jiangsu, Peoples R China;

    Univ N Carolina, Dept City & Reg Planning, New East Bldg, Chapel Hill, NC 27599 USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Intelligent transportation system; Safety; Accident prevention; Inclement weather; Simulation;

    机译:智能交通系统;安全;事故预防;禁忌天气;模拟;

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