Users’ perceptions toward autonomous vehicles: case study in Alberta, Canada
Bibliographic record
Abstract
This study investigates perceptions and attitudes toward autonomous vehicles (AVs) using an online stated preference (SP) survey conducted in Alberta, Canada. It explores the effect of different sociodemographic, external, and psychological factors on users’ attitudes toward AVs. Additionally, factors contributing to people’s willingness to pay for AVs were evaluated. The results indicate that sociodemographic factors, external factors, and people’s perceptions significantly affect people’s willingness to pay for automation. Level 3 of automation is shown to have a positive effect on the drivers’ utility of driving for commuting and non-commuting trips, while other levels of automation were found negatively affecting the utility of driving. Men were generally more willing to pay for AVs, particularly for commuting trips, while weather conditions, especially icy roads, posed significant concerns about AV reliability. Middle-aged drivers exhibited the highest willingness to pay (WTP) for higher levels of automation, emphasizing the potential early adoption among this group.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".