Evaluating the Impact of Travel Demand Management Strategies on GHGs for Downtown Commuters in Rail Catchment Areas
Bibliographic record
Abstract
This paper estimates mode choice changes and potential greenhouse gas (GHG) emission reductions from transit service modifications and parking pricing for downtown commuters living in commuter rail catchment areas in Montreal, Canada. This is done first by developing and estimating a joint neighborhood type – mode choice model. Neighborhood typologies are derived using a cluster analysis based on indicators such as population density, land use mix and transit supply at the residential location. This modeling system is then used to evaluate the potential impact of land-use, transit accessibility and demand management policies (parking pricing, PT fees and travel time) on the mode choice of downtown commuters. Then, GHG emissions at the individual level associated with their trips under different scenarios are estimated. Based on the estimated model and GHG emissions scenarios, it was found that potential GHG emissions from this segment of the population could decrease between 4% and 10% as commuters shift from using their cars to commuter rail. The former could be achieved by decreasing public transit travel time by 30%, and the latter by increasing parking fee by 20% and also decreasing public transit fee by 20%.
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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 | 0.020 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".