Building Online ITS Research and Training Facility: ITS Centre and Testbed Database and Platform
Bibliographic record
Abstract
The Intelligent Transportation System (ITS) Center and Testbed (ICAT) is a is a facility that enables the research and development of advanced computer analysis and control algorithms that are required in order to further improve the operational efficiency of our traffic network. The ICAT platform has live traffic data and video from the Ministry of Transportation of Ontario and the City of Toronto. The ICAT database stores 20-second loop detector data, CMS messages, operator incident logs and 3-minute snap-shots of camera images. This data can be accessed by practitioners and researchers using a web interface anywhere in the world. This paper describes some of the technical design choices involved in the development of such a research facility, and the reasons behind them. In particular, the communications system design, software and hardware architecture, as well as the design philosophy, are described in detail. Some features of the final system will be presented. The authors hope that this will add to the experience and knowledge base of designing this kind of ITS research facility.
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.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".