Design and configuration of audible pedestrian signals in the city of Winnipeg
Bibliographic record
Abstract
The city of Winnipeg is making a continuous effort to improve city accessibility. One of the projects the city has implemented to achieve this goal was installing audible traffic signals (ATS) at some intersections to help visually impaired people (VIP) to cross the streets safely. These ATSs were installed at about 200 intersections so far. However the performance of these systems was not satisfactory due to inconsistent audibility resulting from various aspects such as; traffic noise, wind interference, existence of high rise buildings around intersections, etc. This research outlines the specific issues surrounding the current system and suggests the potential solutions to counteract them. Design of experiments was used to analyze the effectiveness of the ATS system in different levels of speaker height, seasons, number of lanes, and existence of high-rise buildings nearby. Data was collected from a questionnaire through a set of tests conducted at intersections with the help of 16 VIPs. Conclusions were drawn based on the Analysis of Variance (ANOVA) using the MINITAB R software. Finally, the results were reported along with the recommendations related to the system design and maintenance. One of the main recommendations was to lower the speaker height to 4 feet (1.22 meters) instead of the current 10 feet (3.05 meters) height. In view of the results that manifested from the experiments and to counter all other known issues such as echoing effects, annoyance in the neighbourhood, vandalism, etc., a new design of the ATS speaker also has been developed in this thesis and its prototypes submitted to the Public Works Department City for their consideration to implement in the city of Winnipeg.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".