Four-year trends of personal mobility devices in metropolitan vancouver: The evolution of mode shares, speeds, and comfort in off-street paths
Bibliographic record
Abstract
Personal Mobility Devices (PMD) such as (e-)bicycles, (e-)scooters, and (e-)skateboards are increasingly popular for urban travel, which poses challenges in the constrained spaces of cycling facilities and multi-use paths. This study investigates changes in the mode shares and speeds of PMD over 4 years (2019–2023) in metropolitan Vancouver, Canada and their implications for traveller comfort. Classified count and speed data of PMD were collected at 12 sampling locations in the summer of 2023. Those data were combined with similar count and speed data and survey data collected at the same locations in 2019 and 2020. Results show that the mode share of conventional bicycles decreased from 91% to 74%, while electric bicycles increased from 4.5% to 16.4% and stand-up electric scooters increased from 0.4% to 4.2%. Overall mean speed in cycling facilities and multi-use paths increased by 11% (2 km/hr). Controlling for contextual factors, electric and conventional bicycle speeds converged, while electric skateboard and self-balancing unicycle speeds increased by 4 km/hr and 10 km/hr, respectively. These changes reduce comfort, but the average path user remains moderately comfortable with most PMD encountered on off-street paths. Study implications include lower volume thresholds for separated versus multi-use paths, monitoring of PMD speeds, and restrictions on high-speed PMD.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".