Intelligent scheduling for in-car notifications

Jonathan Wright, Q. Stafford-Fraser, M. Mahmoud, P. Robinson, Eduardo Dias, L. Skrypchuk
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引用次数: 3

Abstract

The process of driving a car involves a cognitive load that varies over time. Additional load comes from secondary factors not directly associated with the driving process, including navigation devices, entertainment systems and the car's own warnings. In this paper, we present a framework for intelligent scheduling of in-car notifications based on the driver's estimated cognitive load. As the single channel for communication, it reschedules the notifications using a priority queue, and relays them to the driver based on the urgency of the notification and the overall estimated cognitive load being experienced by the driver at any given moment. We evaluate our system using a dataset collected from a car's CAN bus during multiple on-road trials and show that our proposed approach reduces the number of simultaneous calls on the driver's attention during the driving task. We also demonstrate that our intelligent scheduling significantly reduces the maximum cognitive load experienced by the driver and the frequency with which high loads occur.
智能调度车内通知
驾驶汽车的过程涉及到随时间变化的认知负荷。额外的负荷来自与驾驶过程没有直接关系的次要因素,包括导航设备、娱乐系统和汽车自身的警告。在本文中,我们提出了一个基于驾驶员估计认知负荷的车载通知智能调度框架。作为通信的单一通道,它使用优先级队列重新调度通知,并根据通知的紧迫性和驾驶员在任何给定时刻所经历的总体估计认知负荷将通知转发给驾驶员。我们使用在多次道路试验中从汽车CAN总线收集的数据集来评估我们的系统,并表明我们提出的方法减少了驾驶任务中驾驶员注意的同时呼叫数量。我们还证明,我们的智能调度显着降低了驾驶员所经历的最大认知负荷和高负荷发生的频率。
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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