Driver Distraction: Mechanisms, Evidence, Prevention, and Mitigation

Regan, Michael A.; Oviedo-Trespalacios, Oscar · 2023 · Crossref

DOI: 10.1007/978-3-030-76505-7_38

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Summary

This review chapter by Regan and Oviedo-Trespalacios addresses the multifaceted problem of driver distraction, aiming to clarify its definition, underlying mechanisms, impact on safety, and potential countermeasures. The authors are motivated by inconsistent definitions in existing literature, which hinder the operationalization of distraction in crash data and complicate cross-study comparisons. The paper seeks to provide a comprehensive framework for understanding distraction as a critical road safety issue, particularly in the context of the Vision Zero goal to eliminate traffic fatalities. The authors synthesize existing research to establish a taxonomy of driver inattention, distinguishing "driver diverted attention" (distraction) from other mechanisms like restricted or neglected attention. Distraction is defined as the diversion of attention from activities critical for safe driving toward a competing activity. The review categorizes distraction triggers into top-down (voluntary, driven by driver states or needs) and bottom-up (involuntary, driven by stimulus properties) mechanisms. It further differentiates between the source of distraction (e.g., objects, events, passengers) and the actions performed on them. The authors critique common classifications of distraction types (visual, cognitive, auditory, biomechanical), arguing that biomechanical distraction is actually interference rather than a distinct type, and that auditory distraction is often a byproduct of cognitive diversion. Key findings detail how distraction interferes with driving performance through specific "triggered responses," such as taking eyes, mind, ears, or hands off the road. Visual distraction primarily impairs information selection and vehicle control, leading to delayed event detection and degraded lane keeping. Cognitive distraction affects information processing, causing inattention blindness and memory loss, while also increasing traffic rule violations and conflicts with vulnerable road users. The impact of distraction is moderated by driver characteristics, driving task demands, secondary task demands, and the driver’s ability to self-regulate behavior. Evidence from crash studies indicates that distraction contributes to approximately 10–16% of crashes, with technology interaction being a significant subset. The significance of this work lies in its structured approach to managing distracted driving. The authors conclude that achieving Vision Zero is unlikely until vehicles can safely automate all driving functions in all conditions. However, they emphasize that substantial progress can be made through coordinated strategies involving prevention, evidence-based countermeasures, and mitigation. The review highlights the emerging challenge of distraction in automated vehicles, where automation itself can create distraction or impair takeover ability. By clarifying definitions and mechanisms, the paper provides a foundation for stakeholders to develop more effective policies and interventions to reduce the spread and effects of distracted driving.

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Topics

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• visual
• distraction detection algorithms
• cognitive
• manual
• external distraction
• situational awareness

Information type

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• Theoretical Contribution: conceptual framework, theory or model