Evaluation of Proof-of-Payment and Multiple-Unit Operations in Different Streetcar Route Configurations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study investigates the performance effects of Proof-of-Payment (POP) and Multiple-Unit (MU) streetcar operations when applied individually and jointly to 2 streetcar routes with different configurations and characteristics. Using a microscopic traffic simulation model, the 504 King and the 512 St. Clair streetcar routes in Toronto are investigated. The 2 routes have different operational characteristics. Currently, both routes suffer from major reliability problems including streetcar bunching and gapping. The purpose of POP is to reduce the magnitude and variability of passenger service time. In MU, individual streetcars are coupled while doubling the service headway. To estimate the impact of these measures, a state-of-the-art modeling tool was applied to replicate the existing and proposed scenarios. In general, the Proof-Of-Payment system shows better performance than the Pay-On-Entry system, and Multiple-Unit operation shows better performance than Single-Unit operation. In all cases, POP results in lower headway variability, shorter route travel times and reduced magnitude and variability of passenger service times. On both routes, MU offers the benefits of lower headway variability, fewer extreme headways, shorter route and section travel times, fewer passengers left behind and lower crowding at the peak load stop. In addition, the results point to the benefits of implementing a bundle of strategies since the scenarios with both Proof-Of-Payment and Multiple-Unit operation consistently perform best.
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.
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 | 0.026 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it