Effectiveness and Workload Reduction Model of Hands-off Function in Driver Assistance System
archive: archived pipeline: cataloged verified
Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)
Summary
This study investigates the effectiveness of "hands-off" functionality in Level 2 driver assistance systems, specifically examining its impact on reducing physical and mental workload compared to traditional "hands-on" operation. As Level 2 automation (combining Adaptive Cruise Control and Lane Keeping Assist System) becomes widespread, manufacturers are introducing hands-off capabilities to further alleviate driver burden. The research aims to clarify the constituent factors of driving workload in Level 2 systems and identify how hands-off operation specifically contributes to workload reduction. The experiment involved 28 participants (26 male, 2 female, aged 20–50) who were experienced with Level 2 systems. Data was collected during real-world driving on the Tohoku Expressway, covering a round-trip distance of 206 km. Participants drove under both hands-on and hands-off conditions on separate days, with order counterbalanced. Measurements included subjective evaluations of fatigue and mental load (using RAS and NASA-TLX), physiological indicators (surface electromyography for upper and lower limbs, and heart rate variability via LF/HF ratio), and secondary task performance. After excluding data with control deficiencies, 18 participants were analyzed using paired t-tests, factor analysis, and multiple regression analysis. Results demonstrated that hands-off operation significantly reduced overall and local fatigue, as well as subjective mental load indicators such as effort and dissatisfaction, compared to hands-on driving. Physiologically, hands-off driving led to lower upper-limb muscle activity and a reduced LF/HF ratio, indicating decreased sympathetic nervous system activation. Factor analysis identified five components of driving workload: information processing/operational annoyance, physical constraint, drowsiness, and low driving motivation. Multiple regression analysis revealed that "physical constraint" was the strongest predictor of overall fatigue. A subsequent model for physical constraint showed it was positively correlated with upper-limb muscle burden and negatively correlated with lower-limb muscle burden and system trust. The authors suggest that hands-off operation reduces physical constraint by freeing the upper limbs and allowing more natural lower-limb movements, while higher trust in the system reduces the need for preparatory postures. Additionally, individual variations in arousal effort related to drowsiness were found to contribute to fatigue. The study concludes that hands-off functionality in Level 2 systems effectively reduces both physical and mental workload. The reduction in physical constraint, driven by decreased upper-limb muscle tension and increased system trust, is a key mechanism for lowering overall fatigue. These findings provide a structural understanding of workload in automated driving, suggesting that enhancing system trust and optimizing physical posture support are critical for improving the effectiveness of hands-off driver assistance features.
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.
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | canonical_url | — | — | 1 | 2026-08-09 |
| extract | success | cached | — | — | 3 | 2026-08-10 |
| clean | success | clean | — | — | 1 | 2026-08-09 |
| chunk | success | chunk | — | — | 1 | 2026-08-09 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-08-09 |
| enrich | success | openalex | — | — | 2 | 2026-08-23 |
| promote | success | — | — | — | 1 | 2026-08-09 |
| summarize | success | llm | qwen3.6-27b-nvidia | summ-v5 | 2 | 2026-08-10 |
| tag | success | vector_similarity | — | — | 10 | 2026-08-11 |
| verify | success | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; 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).
- Empirical Findings: physiological data, self report data
- Theoretical Contribution: theory or model