Investigating the Impact of Distracted Driving among Different Socio-Demographic Groups

Jeihani, Mansoureh; Ahangari, Samira; Pour, Arsalan Hassan; Khadem, Nashid; Banerjee, Snehanshu · 2019 · ROSA P / Urban Mobility & Equity Center

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Summary

This study investigates the impact of various in-vehicle and out-of-vehicle distractions on driving performance, specifically examining how different distraction types interact with varying road classes. While previous research established that distracted driving compromises safety, this work addresses a gap in understanding how specific distraction modalities—such as hands-free calls, texting, and non-phone activities—affect drivers across different environments like freeways, urban arterials, and local roads. The research was motivated by the rising prevalence of cell phone usage and in-vehicle technologies, which contribute significantly to crash fatalities. The researchers employed a high-fidelity driving simulator and an eye-tracking system to analyze the behavior of 92 young participants (ages 18–40) from the Baltimore metropolitan area. Participants drove a simulated 36 km² network featuring four road classes: rural collector, freeway, urban arterial, and local road in a school zone. Each participant completed seven scenarios: one baseline drive without distraction and six distraction scenarios involving hands-free calls, hand-held calls, voice-command texting, manual texting, changing clothing, and eating or drinking. Additionally, out-of-vehicle distraction was assessed using billboards with varying cognitive loads. Data collected included speed, lane changes, lateral deviation, brake/throttle usage, and gaze fixation duration. Participants also completed pre- and post-simulation surveys regarding their demographics and driving habits. The results demonstrated that all forms of distraction negatively impacted driving safety, characterized by greater speed fluctuations, increased lane changes, and significant deviation from the road center. Notably, drivers reduced their speed by up to 33% while using hands-free or voice-command cell phone features, a finding that challenges current state policies often permitting such usage. The most severe speed reductions occurred on local roads, where participants slowed by 50% while changing clothing, 33% while using voice-command texting, and 29% while manually texting. Regarding out-of-vehicle distractions, billboard visibility and driver gender significantly influenced gaze behavior. Female participants exhibited shorter gaze fixation durations on billboards compared to males, whereas males looked at their phones for shorter durations than females. Furthermore, billboards with lower cognitive loads resulted in shorter gaze fixations than those with higher cognitive loads. The study concludes that hands-free and voice-command technologies do not eliminate the safety risks associated with distracted driving, as they still cause substantial speed reductions and performance impairments. The findings suggest that current regulations allowing hands-free phone use may be insufficient to ensure safety. Additionally, the research highlights that distraction effects are context-dependent, varying by road type and the cognitive demand of the distracting task. These insights provide empirical evidence for policymakers and vehicle designers to reconsider the safety implications of in-vehicle technologies and roadside advertisements, emphasizing the need for stricter regulations or improved interface designs to mitigate distraction-related crashes.

Key finding

Drivers reduced their speed by up to 33% while using hands-free or voice-command phones, and exhibited greater speed fluctuations, more lane changes, and increased road deviation across all distraction types.

Methodology

simulator

Sample size: 92

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• visual
• external distraction
• mobile phones
• visual manual
• temporal
• distraction detection algorithms

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: observational prevalence, behavioral performance data
• Theoretical Contribution: conceptual framework