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A robust estimation of the effects of motorcycle autonomous emergency braking (MAEB) based on in-depth crashes in Australia

机译:基于澳大利亚深度碰撞的摩托车自主紧急制动(maEB)效果的可靠估计

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摘要

Autonomous emergency braking (AEB) is a safety system that detects imminent forward collisions and reacts by slowing down the host vehicle without any action from the driver. AEB effectiveness in avoiding and mitigating real-world crashes has recently been demonstrated. Research suggests that a translation of AEB to powered 2-wheelers could also be beneficial. Previous studies have estimated the effects of a motorcycle AEB system (MAEB) via computer simulations. Though effects of MAEB were computed for motorcycle crashes derived from in-depth crash investigation, there may be some inaccuracies due to limitations of postcrash investigation (e.g., inaccuracies in preimpact velocity of the motorcycle). Furthermore, ideal MAEB technology was assumed, which may lead to overestimation of the benefits. This study sought to evaluate the sensitivity of the simulations to variations in reconstructed crash cases and the capacity of the MAEB system in order to provide a more robust estimation of MAEB effects.First, a comprehensive classification of accidents was used to identify scenarios in which MAEB was likely to apply, and representative crash cases from those available for this study were populated for each crash scenario. Second, 100 variant cases were generated by randomly varying a set of simulation parameters with given normal distributions around the baseline values. Variants reflected uncertainties in the original data. Third, the effects of MAEB were estimated in terms of the difference in the impact speed of the host motorcycle with and without the system via computer simulations of each variant case. Simulations were repeated assuming both an idealized and a realistic MAEB system. For each crash case, the results in the baseline case and in the variants were compared. A total of 36 crash cases representing 11 common crash scenarios were selected from 3 Australian in-depth data sets: 12 cases from New South Wales, 13 cases from Victoria, and 11 cases from South Australia.The reduction in impact speed elicited by MAEB in the baseline cases ranged from 2.8 to 10.0 km/h. The baseline cases over- or underestimated the mean impact speed reduction of the variant cases by up to 20%. Constraints imposed by simulating more realistic capabilities for an MAEB system produced a decrease in the estimated impact speed reduction of up to 14% (mean 5%) compared to an idealized system.The small difference between the baseline and variant case results demonstrates that the potential effects of MAEB computed from the cases described in in-depth crash reports are typically a good approximation, despite limitations of postcrash investigation. Furthermore, given that MAEB intervenes very close to the point of impact, limitations of the currently available technologies were not found to have a dramatic influence on the effects of the system.
机译:自主紧急制动(AEB)是一种安全系统,可检测到即将发生的向前碰撞,并通过降低本车的速度做出反应,而无需驾驶员采取任何行动。最近证明了AEB在避免和减轻现实事故中的有效性。研究表明,将AEB转换为动力两轮车也可能是有益的。先前的研究已经通过计算机仿真评估了摩托车AEB系统(MAEB)的效果。尽管通过深入的撞车调查得出了MAEB对摩托车撞车的影响,但由于撞车后调查的局限性(例如摩托车的撞击前速度不正确),可能会有一些不准确之处。此外,假设使用了理想的MAEB技术,这可能会导致高估收益。这项研究旨在评估仿真对重灾事故变化的敏感性以及MAEB系统的能力,以便提供更可靠的MAEB影响评估。首先,使用事故的全面分类来识别MAEB的场景可能适用,并且针对每种崩溃场景填充了可用于该研究的典型崩溃案例。其次,通过随机改变一组模拟参数并在基线值附近具有给定的正态分布来生成100个变体情况。变量反映了原始数据中的不确定性。第三,通过每个变体情况的计算机模拟,根据有或没有该系统的主摩托车的撞击速度差异来估计MAEB的效果。假设理想化和现实的MAEB系统都重复进行仿真。对于每个崩溃案例,将比较基线案例和变体中的结果。从澳大利亚的3个深度数据集中,总共选择了代表11种常见碰撞场景的36个碰撞案例:来自新南威尔士州的12个案例,来自维多利亚州的13个案例和来自南澳大利亚州的11个案例。基线情况范围为2.8至10.0 km / h。基线案例高估或低估了变异案例的平均影响速度降低了多达20%。与理想的系统相比,通过模拟更现实的功能对MAEB系统施加的约束导致估计的冲击速度降低最多降低14%(平均5%)。基线和变体案例结果之间的微小差异表明,潜在的尽管事后调查存在局限性,但根据深入的崩溃报告中描述的案例计算出的MAEB的效果通常是一个很好的近似值。此外,由于MAEB的干预非常接近影响点,因此,目前可用技术的局限性并未对系统的效果产生重大影响。

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