Effects of Hybrid Interface on Ecodriving and Driver Distraction
Bibliographic record
Abstract
Hybrid interfaces are emerging in-vehicle technologies that have received minimal research attention in the literature concerning potential impacts on driver performance. Hybrid interfaces have the potential to improve driver fuel efficiency but also to distract drivers. Participants drove a number of urban and suburban routes in the University of Calgary Driving Simulator while interacting with a hybrid interface and attempting to drive fuel efficiently. A within-subjects design was used and each participant drove with and without the hybrid interface. With the hybrid interface, significant reductions in acceleration from a stop were observed when compared with driving without the hybrid interface. Participants spent significantly less time looking to the road ahead while driving with the interface than without it. The duration of participant eye glances to the interface did not exceed 1.6 s; however, drivers tended to combine glances to the interface and speedometer. This combination resulted in several glance durations above 1.6 s without looking back to the road ahead. Balancing ecodriving benefits with driver distraction costs is discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".