Evaluation of the Passing Behavior of Motorized Vehicles When Overtaking Bicycles on Urban Arterial Roadways
Bibliographic record
Abstract
This paper evaluates the influence of on-street bike lanes on the lateral separation between motor vehicles and cyclists when the vehicle overtakes the cyclist and investigates the relationship between the passing behavior and traffic conditions. A bicycle was instrumented with a sensor array that consisted of an ultrasonic sensor, a GPS receiver, and a video camera. A total of 5,227 passing events were recorded across different categories of urban arterials. The results showed that the facilities with on-street bike lanes provided greater separation between bicycles and motor vehicles. Passing maneuvers with lateral separation of less than 1,000 mm (3.30 ft) were observed less frequently on the facilities with on-street bike lanes. Further, it was found that, in the absence of a bike lane, a higher proportion of passing vehicles moved laterally to the left and encroached on the adjacent lane. The analysis showed that for arterial roadways without on-street bike lanes, drivers tended to provide increased lateral clearance by either changing lanes or encroaching on the adjacent lane. However, drivers' ability to perform either of these maneuvers may be restricted by surrounding vehicles.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".