Proposed Canadian automated highway system architecture: object-oriented approach
Bibliographic record
Abstract
Recent advances in the fields of data communication and automated controls make the implementation of automated highway systems (AHSs) more possible. Currently, substantial research effort is being made on the design of intelligent transportation system (ITS) architectures in Europe, Japan, the United States, and Canada. These architectures, however, have major limitations inherit in the design methodology used. Most ITS developers use a process-oriented approach for the design of the architecture that reduces its quality attributes (stability and flexibility) to future changes. This paper presents an approach to implement object-oriented design methodology in the Canadian intelligent transportation system (C-ITS) architecture for AHS. It was also shown that the C-ITS architecture needs a backup communication system to be integrated within the C-ITS architecture. Such a backup system would aid the reliability of future transportation systems to be developed based on this architecture. The proposed C-ITS architecture promotes flexibility, stability, and communication and, as such, should be of interest to ITS developers and researchers.Key words: intelligent transportation systems, architecture, automated highways, object-oriented approach, backup communication.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".