Design of an Experiment to Pinpoint Cognitive Failure Processes in the Interaction of Motorists and Vulnerable Road Users.

IV(2023)

引用 0|浏览9
暂无评分
摘要
Background: Driving in urban traffic requires advanced cognitive skills: perceiving all relevant traffic participants, anticipating their likely trajectories, deciding which action to take, and controlling the vehicle. The underlying perceptual and cognitive processes are subject to occasional failures, which can depend in a complex way on learned heuristics and the cognitive load. Collisions between motor vehicles and vulnerable road users (VRU) in urban traffic remain frequent and have severe consequences. In this article, we study the behavior of drivers of motor vehicles turning right who are required to yield to cyclists riding straight through an intersection. A key potential error process is failure to perceive the cyclist. Methods: We conducted a trial with n = 35 subjects on our closed test track including observations of perceptual actions and gaze control, subject to variations in cognitive load and other factors. The artificial environment of a closed test track and the constraints due to ethical requirements pose challenges to the interpretation of any empirical trial. The current paper focuses on the trial design and on quantification of measurement validity. Results: Summary statistics involving trial features were assessed. Most participants reported that they performed the visual task of checking for cyclists in a manner similar to their behavior in real traffic (whether or not cyclist interactions were expected). The spatial distributions of driver glances to perceive cyclists were evaluated. Conclusion: The realism in this trial despite laboratory conditions may be attributable to ingrained skills and habits of participants. Laboratory trials can help to identify root causes of cognitive errors and ultimately guide efficient and effective deployment of bicycle safety countermeasures.
更多
查看译文
关键词
Traffic analysis, human factors, cognitive models, experimental design
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要