A Vehicle Simulation Study Examining the Effects of System Interface Design Elements on Performance in Different Vibration Environments Below 3 Hz
Bibliographic record
Abstract
OBJECTIVE: This study aimed to explore the relationship between system interface elements' design features and interaction performance in simulated vehicle vibration environments. BACKGROUND: Touch screens have been widely used in vehicle information systems, but few studies have focused on the decline of touchscreen interaction performance and task load increase when driving on unpaved roads. METHOD: The interaction performance (reaction time and task accuracy rate) with vibration frequencies below 3 Hz (1.5, 2.0, and 2.5 Hz) and different interface design elements was investigated employing a touch screen computer and E-prime software. RESULTS: The results indicate that vehicle vibration (below 3 Hz) can significantly reduce interaction performance with a vehicle information system interface. CONCLUSION: An appropriate increase in the physical size of the interface design features (visual stimulus materials and touch buttons) can help to mitigate this negative effect of vibration. APPLICATION: The results and findings of this study can be utilized for the design of information system interfaces as it relates to the vibration scenario of unpaved roads.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".