Behavioral Research and Practical Models of Drivers' Attention

Kotseruba, Iuliia; Tsotsos, John K. · 2021 · OpenAlex-citations

DOI: 10.48550/arxiv.2104.05677

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Summary

This paper reviews the literature on drivers’ visual attention, addressing the persistent problem of driver inattention as a primary cause of traffic accidents. The authors aim to bridge cross-disciplinary theoretical research with practical applications, such as driver monitoring systems (DMS), advanced driver assistance systems (ADAS), and highly automated driving (HAD). The study synthesizes findings from over 175 behavioral studies, nearly 100 practical papers, and 70 surveys published in the last decade, focusing specifically on research that explicitly measures attention using eye-tracking data. The review analyzes the biological and methodological foundations of attention research. It distinguishes between overt attention (gaze shifts) and covert attention (mental focus without gaze change), noting that gaze alone is an imperfect proxy for awareness due to phenomena like change blindness and inattention blindness. The authors examine the roles of foveal and peripheral vision, highlighting that while peripheral vision has lower acuity, it is critical for hazard detection and lane maintenance. The paper also evaluates data collection methodologies, comparing naturalistic on-road studies, directed on-road experiments, closed-track tests, and driving simulators. It details the trade-offs between ecological validity and experimental control, noting that while simulators offer reproducibility, they may lack the physical and visual realism of real-world driving. Key findings indicate that driver gaze is governed by a complex interplay of bottom-up mechanisms (stimulus saliency) and top-down mechanisms (task demands and experience). Top-down control appears dominant, as drivers adjust visual strategies based on task priorities, such as monitoring speedometers more frequently when speed maintenance is prioritized. The review identifies significant variations in attention allocation based on internal factors (age, skill, fatigue) and external factors (distractions, automation, environmental conditions). For instance, older drivers often exhibit a reduced Useful Field of View (UFOV), correlating with higher crash risks, while distractions lead to "looked but failed to see" errors. The authors also note that bottom-up saliency is insufficient for safe driving, as critical objects like motorcycles may have low visual saliency, requiring experience-driven top-down scanning to detect. The significance of this work lies in its comprehensive mapping of attention mechanisms to practical solutions. By linking behavioral insights to engineering applications, the paper informs the design of safer road infrastructure, improved driver education, and more effective automated systems. It concludes by identifying limitations in current gaze-based models and outlining future research directions, emphasizing the need to better understand the integration of bottom-up and top-down attentional controls and the role of peripheral vision in dynamic driving environments.

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Topics

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• visual
• attention allocation
• inattentional change blindness
• distraction detection algorithms
• gaze based attention detection
• situational awareness

Information type

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• Methodological Resource: tool software
• Theoretical Contribution: theory or model, conceptual framework