Effect of Driving Experience on Change Detection Based on Target Relevance and Size

Abstract

Summary:Earlier studies that investigated the effects of driving experience and target safety relevance on change detection have produced conflicting results. Using a flicker change detection task to investigate the effect of driving experience on the ability to detect changes in objects that vary in safety relevance and size, the present study attempted to clarify some controversies by addressing three important methodological issues. The data showed that experienced drivers exhibited more efficient selection strategies than novice drivers and thus may have more spare resources to analyze less relevant objects in the driving environment. Selection strategies for relevant information appear to be sensitive to object size whereas selection of irrelevant information is downgraded comparatively and unaffected by size. Findings are discussed as they relate to theoretical and practical implications.

Do cyclists make better drivers? Associations between cycling experience and change detection in road scenes

“…RT to correctly identify changes followed a similar pattern, with faster responses to non-sign change targets. Many previous studies examining the effect of change target compared relevant versus irrelevant targets (e.g., Galpin et al, 2009;Mueller and Trick, 2013;Zhao et al, 2014), whereas in the current study we found marked differences in change blindness towards different types of driving-related targets. All observers were more likely to experience change blindness when the target that was moved or removed was a road sign, and were slower to notice the changes that they did identify.…”

“…Observers with domain expertise are more efficient than domain-novices at detecting changes, but only when the changes are relevant to their expertise (Feil and Mestre, 2010;Reingold et al, 2001;Werner and Thies, 2000). In contrast, bottom-up salience and physical size do not influence change detection in real-world contexts, including driving-related tasks (Caird et al, 2005;Mueller and Trick, 2013;Richard et al, 2002;Stirk and Underwood, 2007).…”

“…Change detection paradigms have demonstrated utility for revealing which aspects of the scene attract drivers' attention. Drivers are more efficient at detecting changes with greater safety relevance, such as vehicles changing position, compared with changes that have less safety relevance or changes that are irrelevant to driving (Beanland et al, 2017;Galpin et al, 2009;Lee et al, 2007;Mueller and Trick, 2013;Shinoda et al, 2001;Zhao et al, 2014). Drivers are comparatively poor at detecting changes to road signs (Beanland et al, 2017;Metz and Krüger, 2014) and increasing familiarity with the driving route further exacerbates change blindness to road signs Starkey, 2011, 2013;Harms and Brookhuis, 2016;Martens, 2011;Martens and Fox, 2007).…”

Analysis of Distracted Driver Behaviour Using Self-Organizing Maps

“…Various driver characteristics were analysed in different environments, to understand behavioural patterns of drivers in general. One of the features analyzed was the factor of experience in driving [7] . The study aims to further understand while driving, how different object size and shape (along the course) serve as qualifiers as to what is relevant to the driver and what isn't.…”