Estimation of Car Trips Generated by the Arrival of Autonomous Vehicles in the Montreal Metropolitan Area
Bibliographic record
Abstract
In this article, we estimate the car trips generated by the arrival of autonomous vehicles (AV) in the Greater Montreal Area. Our research methodology is based on a simulation model which estimates new travel demand associated with AV by measuring differences in travel needs by age categories. Given the uncertainty regarding the evolution of critical variables such as future car occupancy rate, we evaluate different scenarios to assess a range of potential effects of VA on motorized travel. Thus, the results predict a 13% average increase in motorized trips based on overall results, and a 16% to 20% increase in trips based on a stable average vehicle occupancy rate in the coming years. Otherwise, the predicted increase in travel is between 2%, based on a 14% increase in occupancy, and 26%, based on a 5% decrease in occupancy. For each of the scenarios assessed in the analysis, we estimate the effects on external costs caused by automobile travel. According to our results, AV could reduce private and social costs by $ 5, 059 billion in Quebec.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".