Fast Lane - Exploring Human Behavior - Volume 19
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Summary
This document serves as a biannual progress report (Summer 2024–Winter 2025) for the Federal Highway Administration’s Human Factors Team at the Turner-Fairbank Highway Research Center. It outlines ongoing and completed research initiatives focused on transportation safety, specifically addressing human behavior in the context of automated vehicles (AVs), vulnerable road users, and traffic control devices. The report highlights the team’s use of simulators, virtual reality (VR), closed-course testing, and field studies to evaluate infrastructure and operational strategies that mitigate safety risks in mixed-fleet environments. The research employs diverse methodologies, including high-fidelity VR bicycle simulators, highway driving simulators, and closed-course field tests. Key completed studies utilized simulator and field data to assess driver responses to partially automated truck platooning, emergency vehicles in mixed fleets, and work zone infrastructure during transitions from automated to manual driving. These projects resulted in published technical reports (e.g., FHWA-HRT-24-071, FHWA-HRT-24-063, FHWA-HRT-24-117) providing guidance on signing, configuration, and infrastructure design. Ongoing projects involve data collection on merging behavior, lane-change responses to infrastructure warnings, and pedestrian signing at uncontrolled crossings. Additionally, the team is evaluating aesthetically treated crosswalks and bollard lighting for nighttime pedestrian conspicuity through field and closed-course studies. Findings from completed work provide actionable recommendations for transportation agencies. Research on truck platooning established guidance for signing and operations in mixed-fleet environments. Studies on work zones demonstrated how infrastructure can safely assist drivers in transitioning control from automated systems. The team also developed models comparing human driver behavior with low-speed automated shuttles at intersections and evaluated the impact of rainy weather on ADS-equipped vehicles. Preliminary work on LiDAR and infrared sensor fusion suggests potential improvements in detecting and counting vulnerable road users compared to single-sensor systems. The significance of this work lies in its contribution to the safe integration of automated vehicles and cooperative driving automation into existing transportation systems. By identifying human factors issues related to infrastructure, signage, and vehicle automation, the research supports the development of standards and guidelines that enhance safety for all road users, particularly vulnerable populations like pedestrians and bicyclists. The report also notes efforts to explore racial and socioeconomic disparities in pedestrian morbidity and mortality, indicating a broader commitment to equitable safety outcomes. The team’s active participation in conferences and dissemination of findings through technical reports and guidebooks ensures that these insights inform policy and practice across the transportation sector.
Key finding
The Federal Highway Administration's Human Factors Team conducted a wide range of completed and ongoing studies using simulators, virtual reality, and field methods to evaluate safety issues related to automated vehicles, vulnerable road users, and traffic control devices.
Methodology
other
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 (81 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 | 80 | 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.
- ehmi external hmi
- vru facing ehmi
- work zones
- perceptual countermeasures
- emergency work zone conspicuity
- rail grade crossings
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).
- Methodological Resource: dataset resource, tool software
- Synthesis & Review: research agenda