CVO driver fatigue and complex in-vehicle systems

Lee, Jacsik; Dingus, Thomas A.; Mollenhauer, Michael; Brown, Thomas; Neale, Vicki L · 1997 · ROSA P / United States. Federal Highway Administration

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Summary

This study, conducted by the Federal Highway Administration and Virginia Polytechnic Institute, investigates the impact of driver fatigue and mental workload on the performance of Commercial Vehicle Operators (CVOs) interacting with Advanced Traveler Information Systems (ATIS). The research was motivated by the high prevalence of fatigue-related accidents in the trucking industry and the need to develop human factors design guidelines for in-vehicle systems that do not exacerbate driver impairment. The study specifically examined how sleep deprivation, time-on-task fatigue, driving task load, and ATIS complexity affect objective driving metrics and subjective workload assessments. The experimental design utilized a fixed-base driving simulator at the University of Iowa with CVO drivers from the Iowa City area. Fatigue was manipulated through two methods: sleep deprivation (comparing sleep-deprived vs. non-sleep-deprived conditions) and time-on-task (a 90-minute continuous drive). Mental workload was manipulated by varying driving load (low load with wide lanes/high-speed curves vs. high load with narrow lanes/tight curves) and ATIS complexity (low, medium, and high information item counts). ATIS information was presented via both visual (Head-up Display) and auditory modalities. Dependent variables included driving performance measures (speed variability, lane deviation, acceleration), ATIS task performance (response latency, error frequency), physiological fatigue indicators (eye closure metrics), and subjective ratings of fatigue and workload. Results indicated that sleep-deprived drivers exhibited degraded driving performance compared to rested drivers, evidenced by increased lane deviation and speed variability. However, performance on ATIS-related tasks was not significantly affected by sleep deprivation; in fact, interacting with the ATIS appeared to enhance alertness, allowing fatigued drivers to maintain task performance comparable to rested drivers. Fatigue levels increased progressively throughout the 90-minute simulation, correlating with physiological signs such as increased eye closure duration. While ATIS complexity had little direct impact on objective driving performance, it significantly increased subjective mental workload ratings. High driving load environments resulted in poorer driving performance and higher subjective stress. Regarding display modality, auditory presentations yielded shorter response times than visual ones, though auditory response times degraded more sharply as message complexity increased. The study concludes that ATIS interaction can mitigate fatigue-related performance decrements by sustaining driver alertness, suggesting that drivers should not be discouraged from using these systems when fatigued. Commercial drivers can effectively handle moderate ATIS complexity without significant performance degradation. However, designers should prioritize filtering and sequencing messages to minimize task demands during high-driving-load scenarios. The findings support the development of ATIS guidelines that leverage system interaction to maintain vigilance while carefully managing information complexity to avoid excessive mental workload.

Key finding

Sleep-deprived drivers exhibited degraded general driving performance but maintained equivalent ATIS task performance compared to non-sleep-deprived drivers, suggesting that ATIS interaction may help sustain alertness during fatigue.

Methodology

simulator

Provenance

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

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• time on task
• truck driver fatigue
• mental demand
• drowsiness
• sleep deprivation
• drowsiness 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: physiological data, behavioral performance data
• Theoretical Contribution: theory or model