Understanding the impacts of mobile phone distraction on driving performance: A systematic review
DOI: 10.1016/j.trc.2016.10.006
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Summary
This systematic review addresses the lack of understanding regarding the mechanisms by which mobile phone distraction affects driving performance. While mobile phone use while driving is a prevalent behavior associated with increased crash risk, existing literature often employs reductionist methodologies that isolate specific distractive conditions without considering their combined effects or the underlying human-machine interactions. The authors aim to fill this gap by proposing a novel human-machine system (HMS) framework to systematically analyze the components and interactions involved in mobile phone distracted driving (MPDD). The study employs a systematic classification scheme derived from the HMS framework to review and synthesize relevant literature. The authors analyzed 11 literature reviews or meta-analyses published between 2005 and 2014, as well as 62 original research articles published between 2010 and April 2015. The HMS framework defines MPDD as a system comprising the driver (human), the vehicle and mobile phone (plants), and the road traffic environment. It identifies five key in-vehicle interactions: human-car interface, human-car controls, human-mobile phone interface, human-mobile phone control, and human-environment interface. The review categorizes studies based on these components, the interference between in-vehicle tasks, and resulting system performance metrics such as speed, lateral control, and braking response. The analysis reveals that while numerous studies measure system outcomes like speed selection and lane deviations, research on how drivers interactively manage in-vehicle secondary tasks and adapt their behavior is scant. The review finds that mobile phone tasks, particularly those requiring concurrent use of phone controls and interfaces (e.g., texting), impose high workload and significantly impair driving performance. Specifically, mobile phone use leads to increased steering wheel corrections, delayed braking responses, and reduced visual scanning of the environment. Although conversing on a mobile phone was the most studied interaction, findings regarding its impact on crash involvement remain inconsistent. Furthermore, the review highlights that hands-free devices do not significantly reduce crash risk compared to handheld phones, as the cognitive impairment remains equivalent. The significance of this work lies in the proposed HMS framework, which provides a comprehensive structure for understanding MPDD by isolating system components and interactions. This approach helps identify research gaps, particularly regarding the inverse influence of driving tasks on secondary task performance and the role of vehicle characteristics. The authors conclude that future research should focus on technology-based countermeasures, such as real-time feedback systems based on eye/head movements and vehicle dynamics, to mitigate safety issues. By adopting this systematic approach, the field can better parameterize driver behavior and develop more effective interventions for mobile phone-related driving distractions.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | OpenAlex-citations | — | — | 1 | 2026-06-17 |
| archive | success | unpaywall | — | — | 2 | 2026-06-25 |
| extract | success | pdftotext | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-26 |
| chunk | success | chunk | — | — | 1 | 2026-06-26 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-26 |
| enrich | failed | — | — | — | 5 | 2026-07-05 |
| promote | success | — | — | — | 1 | 2026-06-17 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-25 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-26 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-25; verification: verified.
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- Empirical Findings: observational prevalence, behavioral performance data
- Theoretical Contribution: conceptual framework