Bibliographic record
Abstract
Pedestrian safety is a topic of growing concern. To better understand pedestrian safety and the variables that affect it, this thesis had four main objectives. The first objective was to build a database to be used for the analysis of pedestrian safety. The database built consisted of 1,875 signalized intersections (75% of all signalized intersections on the island), randomly distributed throughout the island of Montreal. Manual vehicular and pedestrian counts were provided by local authorities for these intersections, but they also needed to be visited individually, so that geometric data could be recorded for each intersection. This is the largest data set that has ever been assembled for a pedestrian safety analysis. The second objective was to use automatic counters to extrapolate manual pedestrian counts taken during peak periods, to full 24 hour average daily counts through the use of expansion factors. By placing automatic counters at six different locations throughout the city of Montreal for one full year, various expansion factors were generated (monthly, daily and hourly). The third objective was to investigate the effect of traffic exposure measures, geometric designs and traffic controls on vehicle-pedestrian collision occurrence at signalized intersections. To investigate the impact of vehicle movements on pedestrian accidents, three separate definitions of risk exposure were used: completely aggregated flows, motor-vehicle flows aggregated by movement type (left, right and through movements) and disaggregated flows analyzing potential conflicts between motor vehicles and pedestrians. Various negative binomial (NB) models were fitted to the data with and without geometric design characteristics. Among other findings, vehicular traffic is found to be the main contributing factor in accordance with previous works. Significant geometric properties included pedestrian phasing, exclusive left turn lanes, commercial entrances and exits, total crossing distance, curb extension and number of lanes. Exclusive left turn lanes, pedestrian phasing and curb extensions were found to decrease pedestrian accidents, whereas longer crossing distances, number of lanes and more commercial entrances and exits were found to increase pedestrian-vehicular accidents after controlling for vehicular and pedestrian flows. The final objective was to estimate pedestrian activity at signalized intersections based on built environment attributes. Using both a log-linear and negative binomial regression, it was found that pedestrian activity could be estimated by several land-use, transit, demographic and weather variables; including: population, commercial space, open space, subway presence, bus stations, schools, percent major arterials, number of street segments, presence of a 4-way intersections, presence of precipitation and presence of windy conditions. These findings support other studies done in this field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| 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 | 0.000 |
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".