Mobile eye tracking during real-world night driving: A selective review of findings and recommendations for future research

Grüner, Markus; Ansorge, Ulrich · 2017 · Crossref

DOI: 10.16910/jemr.10.2.1

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Summary

This review paper addresses the critical safety issue of real-world night driving, where fatal traffic accidents disproportionately occur compared to daytime driving. The authors, Grüner and Ansorge, aim to understand the visual and cognitive conditions that facilitate or hinder safe nocturnal driving by exhaustively reviewing published eye-tracking research. The study is motivated by the need to interpret gaze behavior through established theoretical frameworks: Gibson and Crooks’ (1938) model of driving as visually guided path selection through a "field of safe travel," and Endsley’s (1995) situation awareness model, which emphasizes the role of cognitive factors like memory and load. The review focuses specifically on real-world data rather than simulator studies to ensure ecological validity, acknowledging that low illumination at night impairs visual acuity, color discrimination, and contrast sensitivity, thereby challenging drivers' ability to maintain accurate situation awareness. The methodology involves a systematic categorization of existing eye-tracking studies based on two orthogonal dimensions: the origin of influencing factors (environmental vs. organismic) and their temporal inertia (stable vs. dynamic). Environmental factors include elements like headlamp conditions, road geometry, and traffic signs, while organismic factors encompass driver age, experience, and cognitive load. The authors evaluate these studies against the theoretical models to determine whether observed eye movements reflect controlled, task-relevant strategies or automatic, potentially distracting responses to salient stimuli. The review also distinguishes between different types of visual attention—reflexes, habits, exploration, and deliberation—to better interpret the cognitive processes underlying gaze patterns during night driving. The findings indicate that drivers generally exhibit expedient looking behavior, directing their gaze toward the boundaries of the field of safe travel and other road users. This suggests that controlled, intended eye movements largely supervise driving performance. However, the review highlights ambiguity in interpreting certain gaze patterns; for instance, it remains uncertain whether wider fixation dispersion during daytime driving reflects beneficial strategic scanning or distraction by irrelevant stimuli. The authors note that while drivers adapt to low-light conditions using rod-mediated vision, this comes at the cost of reduced spatial resolution and color perception, which can impair hazard detection. Furthermore, the review identifies a significant gap in the literature: most studies fail to correlate eye movement data with other driving performance metrics, limiting the ability to evaluate the actual impact of gaze behavior on driving safety. The significance of this work lies in its proposal for a more fine-grained model of the driving task that details the contribution of eye movements to specific subtasks. By integrating environmental and organismic factors, the authors argue for a more nuanced understanding of how visual information selection supports situation awareness during night driving. The review concludes that future research must bridge the gap between gaze data and performance outcomes to better assess real-world night driving safety. This approach could inform the development of improved driver training, vehicle lighting systems, and road infrastructure designed to mitigate the unique visual challenges of nocturnal driving.

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Topics

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• eye movements scanning
• dark adaptation mesopic
• peripheral attention
• gaze based attention detection
• visual
• attention allocation

Information type

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• Empirical Findings: behavioral performance data
• Methodological Resource: tool software
• Theoretical Contribution: theory or model