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Efficacy of automatic emergency braking among risky drivers using counterfactual simulations from the SHRP 2 naturalistic driving study

机译:使用SHRP 2自然驾驶研究的危险驾驶员自动应急制动的功效

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Motor vehicle crashes remain a significant problem in the US and worldwide. Automatic emergency braking (AEB) is designed to mitigate the most common crash mode: rear-end striking crashes. However, assessing the efficacy of AEB in real-world crash scenarios is challenging given that avoided crashes are rarely documented except during naturalistic driving studies. In the absence of such data, AEB can be evaluated in real-world crash scenarios by retrospectively adding AEB to naturalistic crashes using counterfactual simulations. AEB was retrospectively applied to rear-end striking crashes (n = 40) from the SHRP 2 database among teen (16-19 yrs), young adult (20-24 yrs), adult (35-54 yrs), and older (70 + yrs) drivers. Real-world AEB deceleration profiles from IIHS AEB tests were paired with SHRP 2 vehicles based on vehicle make and class. AEB onset for SHRP 2 crashes was based on a brake threat number (BTN) algorithm. AEB curves were adjusted to match the speed of the vehicle at AEB onset. AEB deceleration curves were scaled based on road surface conditions. Driver reaction was accounted for by beginning the deceleration curve at the current driver-initiated braking level. Overall, AEB was found to be very effective, preventing 83% (n = 33) of rear-end striking crashes. However, AEB was less effective for crashes that occurred at higher speeds and during inclement weather conditions. These data provide a counterfactual evaluation of AEB that can be used by OEMs to prioritize AEB optimization for higher speed crashes and sub-optimal road conditions.
机译:机动车崩溃仍然是美国和全球的重要问题。自动应急制动(AEB)旨在减轻最常见的碰撞模式:后端打击崩溃。然而,评估AEB在现实世界的碰撞方案中的功效是挑战,因为除了在自然驾驶研究中,避免崩溃很少被记录。在没有这样的数据的情况下,可以通过回顾性地将AEB添加到使用反事实模拟的自然崩溃中的实际碰撞方案中评估AEB。 AEB回顾性地从青少年(16-19岁),年轻成人(20-24 YRS),成人(35-54 YRS)和更老的SHRP 2数据库中的后端撞击崩溃(n = 40)。 + YRS)司机。 IIHS AEB测试的现实世界AEB减速概况与基于车辆制作和班级的SHRP 2车辆配对。 SHRP 2崩溃的AEB发作基于制动威胁号(BTN)算法。调整AEB曲线以使车辆在AEB发作时的速度匹配。 AEB减速曲线基于路面条件缩放。通过在当前驾驶员发起的制动水平处开始减速曲线来占驾驶员反应。总体而言,发现Aeb是非常有效的,防止83%(n = 33)的后端撞击碰撞。然而,AEB对在更高速度和恶劣天气条件下发生的崩溃的崩溃效果较小。这些数据提供了可由OEM使用的AEB的反事实评估,以优先考虑AEB优化以获得更高的速度崩溃和次优道条件。

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