Enhancing Pedestrian Safety - Lessons Learned from Calgary's RRFB Pilot
Bibliographic record
Abstract
Pedestrians are the most vulnerable road users in transportation system. In 2013, Calgary witnessed 348 casualty (fatal and injury) collisions involving pedestrians. Accommodation of pedestrians at crosswalks in a safe and interactive manner has always been a great challenge. Amid the growing use of Rectangular Rapid Flashing Beacons (RRFBs) in the United States after FHWA approval (FHWA, 2008), there has been a significant amount of research conducted on the effectiveness of this device and technical specifications. However, there is very limited information in the Canadian context simply because of the lack of use of this device in Canada. The City of Calgary provided a research platform by piloting these devices at eight locations in 2012 to evaluate motorists’ yielding behavior to pedestrians and the reliability of RRFB’s solar powered battery system in Canadian weather. Following the encouraging study results presented to the City Council, Calgary decided to expand the RRFB installation to 25 locations by 2015. In tune with the ‘Vulnerable Road User Safety Strategy’; one of the 11 strategies identified in Calgary Safer Mobility Plan 2013-2017, this device is expected to help in reducing pedestrian related collisions at crosswalks. Before-after studies conducted within the City for RRFB devices indicated that the level of motorists’ yield compliance to pedestrians increased significantly at pedestrian crossings from lower to mid 80% to over 95% in most cases. It was concluded that given the significantly lower installation cost (approximately 1/3rd) compared to overhead flashers and yet similar results on yield compliance by motorists, this device could provide a cost-effective solution to improve pedestrian safety at crosswalks (both intersections and mid-block locations). The rapid flashing pattern of RRFBs appears to be very effective in catching driver’s attention thereby increasing motorists’ yield compliance to pedestrians at crosswalks. Increased yield compliance at significantly low cost provides an opportunity to overcome budget constraints. Versatile nature of this device with options to power by solar batteries or by connecting to permanent power grid provides a perfect opportunity to use this device in various climatic conditions, especially in Canadian context. This paper presents the results of the before-after studies, lessons learned on the performance, powering the device and next steps for the use of this device. With the recent TAC approval of RRFB as a traffic control device, this device is expected to be used widely across Canada once the warrant process has been established.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".