Development of Human Factors Guidelines for Advanced Traveler Information Systems and Commercial Vehicle Operations: Investigation of ATIS Function Transition and the Effects of an In-Vehicle ATIS on Driver Performance
archive: archived pipeline: cataloged verified
Get this paper ↗ (full text — opens at the source; we link to it, we don't host it)
Summary
This study, conducted by the Federal Highway Administration, investigates the human factors associated with Advanced Traveler Information Systems (ATIS) to develop design guidelines for commercial and private vehicle operations. The research addresses two primary problems: the cognitive demands placed on drivers when transitioning between different ATIS functions during pre-drive planning, and the impact of in-vehicle ATIS usage on driving performance during transit. The work was motivated by a gap in existing guidelines for "drive mode" operations and the need to evaluate whether ATIS devices improve driver compliance with regulatory information compared to standard roadside signage. The research comprised two experiments. Experiment 1 utilized the Battelle ATIS Simulator to assess pre-drive cognitive demands. Researchers developed two prototype ATIS systems: an "integrated" system with uniform user interfaces across functions and a "non-integrated" system with distinct interfaces for each function. Using Cognitive Task Analysis (CTA), verbal protocols, and performance metrics, the study measured how drivers navigated trip planning scenarios. Experiment 2 employed a high-fidelity driving simulator featuring a virtual representation of Seattle. Eighteen subjects drove while interacting with a simulated ATIS via a dashboard-mounted 4-inch color monitor and a dedicated keypad. The study manipulated independent variables including ATIS status (on/off), control input type (ATIS vs. standard devices like radio/HVAC), and message potency (visual only, visual with auditory alert, auditory command, or roadside sign). Dependent variables included driving performance metrics (speed standard deviation, steering reversals) and reactions to roadway events (compliance with speed changes, time to lane crossing). The findings indicate that ATIS devices can be learned and used successfully by drivers. In Experiment 1, cognitive demands associated with function transitions were low, and performance levels were acceptable. Interestingly, drivers recognized non-integrated screens faster and more accurately than integrated ones, suggesting unique visual designs for each function may aid recognition. Experiment 2 revealed that ATIS messages significantly improved driver compliance with regulatory information compared to roadside signs alone. Specifically, visual ATIS messages were more effective than signs, and concurrent visual and auditory alerts were beneficial. While operating the ATIS introduced some cognitive load, it did not severely degrade driving performance. The moving map display and control inputs were manageable, though the study noted that minimizing the number of ATIS functions could further reduce cognitive demands. The significance of this research lies in its contribution to human factors design guidelines for Intelligent Transportation Systems. The results suggest that in-vehicle ATIS has the potential to enhance safety and regulatory compliance by providing more effective information than traditional signage. The study supports the implementation of ATIS with clear, distinct visual cues and suggests that while cognitive load is a concern, it can be mitigated through careful interface design and function selection. These findings provide empirical evidence for designing ATIS systems that balance informational utility with driver safety.
Key finding
Visual ATIS messages alone are significantly better than roadside signage alone for driver compliance with regulatory information.
Methodology
simulator
Sample size: 18
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).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 19 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
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.
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).
- Applied Guidance: design guidelines
- Methodological Resource: tool software
- Theoretical Contribution: computational model