Operational Evaluation of Advisory Bike Lane Treatment on Road User Behavior in Ottawa, Canada
Bibliographic record
Abstract
The City of Ottawa has been investigating design solutions to facilitate the addition of cycling facilities, while maintaining parking, to roadways with limited right-of-ways. A pilot project to install advisory bike lanes was initiated. The purpose of this study is to determine how new pavement markings (advisory bike lanes) influence cyclist and motorist interactions and positioning, especially with respect to the distance between motorists and cyclists when passing. The study presents a before–after evaluation of two contrasting pavement indications. Video data were collected in two phases (pre- and post- treatment); each phase consisted of two different days. A number of safety performance parameters were used to assess whether safer conditions existed after the new treatment was installed: (i) the lateral distance between the motor vehicle and cyclist, (ii) the lateral distance between the cyclist and curbside edge/cyclist and buffer edge line, and (iii) the speed of the cyclist and motor vehicle. The findings indicate that the advisory bike lanes created more favorable conditions for cyclist safety and for motor vehicle compliance. These findings are (i) motorists passed cyclists with a greater lateral separation distance, (ii) cyclists positioned themselves further from parking edge line and rode in the middle of the bike lane, (iii) motor vehicle traveling speed decreased (the 85th percentile speed decreased by 5.2% after the installation of the advisory bike lane), and (iv) average cyclist speed increased (the average cyclist speed increased by 7.7% after the installation of the advisory bike lane).
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".