Quantifying Impacts of Transit Reliability on User Costs
Bibliographic record
Abstract
Transportation modeling frameworks assume that travelers are economically rational; that is, they choose the lowest-cost alternative to complete a desired trip. The reliability of travel time is of critical importance to travelers. The ability to quantify reliability allows planners to estimate more accurately how system performance influences local travel behavior and to evaluate more appropriately potential investments in the transportation system infrastructure. This paper presents a methodology that makes use of automatic vehicle location data from the regional municipality of Waterloo, Ontario, Canada, to estimate the reliability of transit service. On the basis of these data, the impacts of unreliable service on generalized transit user costs are quantified by use of a simulation model of bus arrivals and passengers’ desired arrival times. It is shown that the increasing reliability of arrivals at a station can decrease transit users’ generalized costs significantly and by as much as 15% in a reasonably reliable network. It is further posited that the inclusion of uncertainty in the calculation of generalized costs may provide better estimates of mode splits in travel forecasting models. A description of future applications of the model concludes the paper.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".