Effects of Reading Text While Driving: A Driving Simulator Study

Prevedouros, Panos D; Miah, M Mintu; Nathanail, Eftihia · 2020 · ROSA P / University of Alaska Fairbanks. Center for Safety Equity in Transportation (CSET)

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Summary

This study investigates the impact of reading text while driving on vehicle control and safety, addressing a critical gap in distracted driving research by utilizing a large sample of professional drivers. While distracted driving is a leading cause of motor vehicle crashes, prior simulator studies often relied on small participant pools. This research specifically targeted text reading, a common distraction for taxi and delivery drivers, to determine how this secondary task affects driving performance metrics such as headway, lane deviation, and visual attention. The experimental design involved 203 professional taxi drivers from a Honolulu-based company, providing a statistically robust dataset compared to previous literature. Participants used a mid-range VS500M driving simulator to navigate a two-lane rural highway with a 60 mph speed limit and medium traffic. After a familiarization period, drivers completed a baseline driving segment followed by a distraction segment where they were required to read three realistic text messages regarding passenger pickups and traffic conditions displayed on a 7-inch tablet mounted on the dashboard. Eye and head movements were monitored to quantify time spent driving blind. The study also analyzed demographic factors, including age, gender, race, and education, to identify predictors of distraction severity. The results demonstrated significant degradation in driving performance during the text-reading condition. Drivers significantly increased their following headway by 20.7% and lane deviations by 354%. Visual attention metrics showed substantial impairment, with total time driving blind increasing by 352%, maximum duration per glance rising by 87.6%, and driving blind incidents increasing by 170%. Conversely, lane change frequency decreased by 35.1%, indicating reduced maneuvering activity. Notably, braking aggressiveness did not change significantly, likely due to the professional drivers' established skills in smooth vehicle control. Eight drivers lost control and experienced simulated crashes. The study concludes that reading text while driving severely compromises safety and vehicle control. Advanced analysis revealed that demographic and behavioral factors significantly influence distraction levels. Older drivers, despite greater experience, exhibited higher distraction levels, particularly in visual attention. Race also played a role, with Filipino drivers maintaining shorter following intervals and Vietnamese drivers exhibiting longer blind driving durations. Gender differences indicated that women were more conservative in lane positioning but followed at longer intervals. The findings imply that all drivers, particularly those in transportation network companies and logistics, should be discouraged from reading text while driving. The research underscores the importance of incorporating individual behavioral profiles and demographic characteristics into safety assessments and policy interventions.

Key finding

Reading text while driving significantly increased headway by 20.7%, lane deviations by 354%, total time of driving blind by 352%, maximum duration of driving blind by 87.6%, driving blind incidents by 170%, and driving blind distance by 337%, while significantly decreasing lane change frequency by 35.1%.

Methodology

simulator

Sample size: 203

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).

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

Topics

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

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: behavioral performance data, observational prevalence
• Methodological Resource: tool software