Bibliographic record
Abstract
Roundabouts are used for traffic calming, have cheaper lifetime costs, and are environmentally friendly. For Persons with Vision Loss (PWVL), roundabouts are challenging when crossing streets due to lack of signalization and difficulties in differentiating sound cues. The objectives of this research were to investigate roundabout accessibility issues confronting PWVL and to evaluate a safe crossing solution. To achieve these objectives, a national workshop with the Canadian National Institute for the Blind (CNIB) clients, and a survey with volunteers were conducted to determine accessibility issues. For evaluation of the crossing solution, steps included using a 3D model of a roundabout, developing sound strips, testing them on a parking lot, installing and utilizing them at the roundabout, and conducting a post-experiment survey. CNIB staff facilitated local meetings, the national workshop and assistance with volunteers during field tests. Field studies were conducted with six volunteers during one day before sound strips were installed and one day after. Data collected at the roundabout included vehicle speed, vehicle yield for pedestrians, delay felt by pedestrians, and pedestrians' opinions. Results showed that sound strips provided PWVL with warnings of upcoming vehicles. Data analysis showed 57% of vehicles yielding to pedestrians before installation and 41% after. Also, the average delay experienced by pedestrians decreased from 41.39 seconds to 38.34 seconds. In reference to speed, a few vehicles traveling through the intersection exceeded the 40KPH posted speed prior and after installation of the strips, highlighting the need for continued safety measures. Furthermore, it was determined that using a 3D model was helpful in discussing accessibility issues with volunteers. These findings provide meaningful information about concerns and issues faced by PWVL at roundabouts, suggesting that treatment using sound strips is beneficial for this vulnerable group when navigating these locations. Overall, this research provides valuable insights into roundabout accessibility issues and offers a potential solution to improve safety and mobility for PWVL. A statistical analysis revealed changes in vehicle speeds across four approaches, with highly significant reductions (p < 0.001) observed before treatment on Approaches 1, 2, and 4. However, results after treatment were mixed, with marginal significance (p = 0.072 and p = 0.084) on Approaches 2 and 4. Due to the small sample size, findings should be interpreted with caution, and further research is needed to draw definitive conclusions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".