The use of cardiac-based metrics to assess secondary task engagement during automated and manual driving: An experimental simulation study

Leandro Luigi Di Stasi, Francesco Angioi, Marcelo Fernandes, Giulia De Cet, M Jesus Caurcel, Kristina Stojmenova, Jaka Sodnik, Christophe Prat, Carolina Díaz Piedra
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Abstract

Most driver monitoring systems (DMS) rely on cameras facing the driver while detecting their gaze or head position. Both future automated driving (AD) in-vehicle interactions and AD vehicle interior designs (e.g., seating arrangement) might drastically reduce the effectiveness of such camera-based DMS solutions, however. Thus, alternative solutions that do not rely on cameras, and therefore compatible with upcoming AD journey experiences, are worth being investigated. Here, we studied the behavior of several cardiac-based indices. We aimed to determine the effects of engaging in non-driving-related tasks (NDRT) in a semi-dynamic driving simulator on heart rate and heart rate variability parameters (here, we report the standard deviation of R-R intervals [SDRR]). We developed a 2 (AD vs. manual driving [MD] modalities) by 2 (one-hand vs. two-hand concurrent Task modality) within-participants experimental design. Thirty-two expert drivers drove along two highway scenarios (∼ 22 minutes each) in daylight conditions. Each scenario included four distraction periods. In each distraction period, participants performed a concurrent task in addition to their main task (i.e., driving the simulator during MD, supervising the system during AD). We monitored participants’ cardiac activity and collected performance levels on the NDRT, driving performance, as well as subjective ratings of task load. Cardiac-based indices clearly differentiated Task modality, with the two-hand task inducing higher heart rate and SDRR. Driving modality (MD vs. AD) only influenced heart rate, which increased during MD. Driving performance and subjective ratings, as well as performance on the NDRT, were able to reflect the experimental manipulation, with the two-hand concurrent task (in MD) being the most disruptive and demanding condition. Overall, these findings have the potential to improve future DMS design and road safety by providing accurate measurements of driver engagement. They can be key to assess future driver-vehicle interactions using for example, non-contact, more realistic, heart-rate radar-based sensor solutions.
使用基于心脏的指标来评估自动驾驶和手动驾驶期间的次要任务参与:一项实验模拟研究
大多数驾驶员监控系统(DMS)依靠面向驾驶员的摄像头来检测他们的目光或头部位置。然而,未来的自动驾驶(AD)车内交互和AD车辆内部设计(例如,座位安排)可能会大大降低这种基于摄像头的DMS解决方案的有效性。因此,不依赖摄像头、与即将到来的AD旅行体验兼容的替代解决方案值得研究。在这里,我们研究了几个基于心脏的指标的行为。我们的目的是确定在半动态驾驶模拟器中参与非驾驶相关任务(NDRT)对心率和心率变异性参数的影响(在这里,我们报告了R-R区间的标准差[SDRR])。我们开发了一个2(单手与双手并发任务模式)的参与者实验设计2 (AD vs手动驾驶[MD]模式)。在白天,32名专家驾驶了2个高速公路场景(每个场景约22分钟)。每个场景包括四个分散注意力的阶段。在每个分心阶段,参与者在他们的主要任务之外执行一个并发任务(即,在MD期间驾驶模拟器,在AD期间监督系统)。我们监测了参与者的心脏活动,并收集了NDRT的表现水平、驾驶表现以及对任务负荷的主观评分。基于心脏的指标明显区分任务方式,双手任务诱导更高的心率和SDRR。驾驶方式(MD vs. AD)仅影响心率,在MD期间心率增加。驾驶表现和主观评分,以及NDRT的表现,能够反映实验操作,双手并发任务(在MD中)是最具破坏性和要求的条件。总的来说,这些发现有可能通过提供驾驶员参与的精确测量来改善未来DMS的设计和道路安全。它们可能是评估未来驾驶员与车辆交互的关键,例如使用非接触式、更现实的、基于心率雷达的传感器解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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