Spare visual capacity and driver inattention in lateral vehicle control

IF 4.4 2区 工程技术 Q1 PSYCHOLOGY, APPLIED Transportation Research Part F-Traffic Psychology and Behaviour Pub Date : 2025-02-01 DOI:10.1016/j.trf.2025.01.043
Abhishek Sarkar, Tuomo Kujala
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Abstract

Drivers often possess spare visual capacity (SVC), which allows them to occasionally shift their gaze from the road for both driving-task related and non-related reasons without significantly compromising safety. This creates the need to quantify SVC from a normative perspective to understand its limits in a context-sensitive manner, which can help in the timely detection of potential driver inattention and the prevention of possible mishaps. We developed a mathematical formula that generates situational estimates of available SVC by considering the relevant environmental, mechanical, and cognitive factors, enabling us to objectively identify driver inattention against a valid reference point during a lateral vehicle control task. A driving simulator study (N = 32) was conducted to implement and evaluate the effectiveness of our methodology and to examine drivers’ visual sampling behavior in a lane-keeping task. We successfully predicted all lane excursions in advance. While the likelihood of inattention towards lane position during occluded driving is small, it exists and increases with speed. The time required to avoid lane excursions varies with speed, side of lane boundary, and individual driver differences. Quantifying situational SVC can aid in detecting driver inattention by providing a more accurate assessment in advance of safety–critical outcomes, thereby reducing false positives. Our approach offers potential for developing improved safety standards and designing proactive adaptive systems to monitor driver inattention based on contextual and driver-specific factors.
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横向车辆控制中视觉能力不足和驾驶员注意力不集中
司机通常拥有多余的视觉容量(SVC),这使得他们偶尔会因为与驾驶任务相关或无关的原因将目光从道路上转移开,而不会明显影响安全。这就需要从规范的角度对SVC进行量化,以便以上下文敏感的方式了解其局限性,这有助于及时发现潜在的驾驶员注意力不集中,并防止可能发生的事故。我们开发了一个数学公式,通过考虑相关的环境、机械和认知因素,生成可用SVC的情景估计,使我们能够客观地识别驾驶员在横向车辆控制任务中的注意力不集中。一项驾驶模拟器研究(N = 32)进行了实施和评估我们的方法的有效性,并检查驾驶员在车道保持任务中的视觉采样行为。我们成功地提前预测了所有的车道漂移。虽然在闭塞驾驶中对车道位置不注意的可能性很小,但这种情况确实存在,并且随着速度的增加而增加。避免车道偏移所需的时间随速度、车道边界的侧面和驾驶员个体的差异而变化。量化情景SVC可以在安全关键结果出现之前提供更准确的评估,从而帮助检测驾驶员的注意力不集中,从而减少误报。我们的方法为制定更好的安全标准和设计主动自适应系统提供了潜力,该系统可以根据环境和驾驶员特定因素监测驾驶员的注意力不集中。
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来源期刊
CiteScore
7.60
自引率
14.60%
发文量
239
审稿时长
71 days
期刊介绍: Transportation Research Part F: Traffic Psychology and Behaviour focuses on the behavioural and psychological aspects of traffic and transport. The aim of the journal is to enhance theory development, improve the quality of empirical studies and to stimulate the application of research findings in practice. TRF provides a focus and a means of communication for the considerable amount of research activities that are now being carried out in this field. The journal provides a forum for transportation researchers, psychologists, ergonomists, engineers and policy-makers with an interest in traffic and transport psychology.
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