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首页> 外文期刊>Journal of Safety Research >Population distributions of time to collision at brake application during car following from naturalistic driving data
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Population distributions of time to collision at brake application during car following from naturalistic driving data

机译:根据自然驾驶数据得出的在汽车刹车时碰撞时间的总体分布

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Problem: Forward collision warning (FCW) systems are designed to mitigate the effects of rear-end collisions. Driver acceptance of these systems is crucial to their success, as perceived "nuisance" alarms may cause drivers to disable the systems. In order to make customizable FCW thresholds, system designers need to quantify the variation in braking behavior in the driving population. The objective of this study was to quantify the time to collision (TTC) that drivers applied the brakes during car following scenarios from a large scale naturalistic driving study (NDS). Methods: Because of the large amount of data generated by NDS, an automated algorithm was developed to identify lead vehicles using radar data recorded as part of the study. Using the search algorithm, all trips from 64 drivers from the 100-Car NDS were analyzed. A comparison of the algorithm to 7135 brake applications where the presence of a lead vehicle was manually identified found that the algorithm agreed with the human review 90.6% of the time. Results: This study examined 72,123 trips that resulted in 2.6 million brake applications. Population distributions of the minimum, 1st and 10th percentiles were computed for each driver in speed ranges between 3 and 60 mph in 10 mph increments. As speed increased, so did the minimum TTC experience by drivers as well as variance in TIC. Younger drivers (18-30) had lower ITC at brake application compared to older drivers (30-51 +), especially at speeds between 40 mph and 60 mph. Discussion: This is one of the first studies to use large scale NDS data to quantify braking behavior during car following. The results of this study can be used to design and evaluate FCW systems and calibrate traffic simulation models. (C) 2015 National Safety Council and Elsevier Ltd. All rights reserved.
机译:问题:前向碰撞警告(FCW)系统旨在减轻追尾事故的影响。驾驶员对这些系统的接受对于其成功至关重要,因为感知到的“烦人”警报可能会导致驾驶员禁用系统。为了制定可定制的FCW阈值,系统设计人员需要量化驾驶人群中制动行为的变化。这项研究的目的是量化根据大型自然驾驶研究(NDS)的场景,驾驶员在汽车行驶过程中踩刹车时的碰撞时间(TTC)。方法:由于NDS会生成大量数据,因此开发了一种自动算法,可以使用记录在研究中的雷达数据来识别领先的车辆。使用搜索算法,分析了来自100辆汽车NDS的64位驾驶员的所有行程。将算法与7135个制动应用程序进行了比较,在该应用程序中手动识别了领先车辆的存在,发现该算法90.6%的时间与人工检查一致。结果:这项研究检查了72,123次行程,产生了260万次制动。计算每个驾驶员在3至60 mph之间的速度范围(以10 mph的增量)的最小,第一和第十个百分位的人口分布。随着速度的提高,驾驶员的最低TTC体验以及TIC的差异也随之增加。与年龄较大的驾驶员(30-51 +)相比,年龄较小的驾驶员(18-30)在制动时的ITC较低,尤其是在40 mph至60 mph的速度下。讨论:这是最早使用大规模NDS数据来量化汽车追随过程中制动行为的研究之一。这项研究的结果可用于设计和评估FCW系统并校准交通仿真模型。 (C)2015国家安全委员会和Elsevier Ltd.保留所有权利。

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