Analyzing Network Connectivity by Cyclist Comfort: An Empirical Reappraisal of the Four Types of Cyclists Typology and Level of Traffic Stress Framework
Bibliographic record
Abstract
North America is seeing a resurgence of interest in cycling both for recreation and as a transportation mode. Cycling is touted as a means to reduce traffic congestion and its GHG emissions and pollution, increase livability, and provide a remedy to inactivity and its related health problems. Building a network of safe and connected infrastructure has been recognized as an important step for cities seeking to increase the share of cycling as a transportation mode. Developing methods to assess bicycle network connectivity and accessibility has been the focus of a large body of research. In particular, the Level of Traffic Stress (LTS) framework was developed to classify network links according to the stress they might represent for cyclists. The level of stress is roughly mapped to accommodate cyclists with varying cycling confidence, known in the literature as the Four Types of Cyclists: No Way No How, Interested but Concerned, Enthused and Confident, and Strong and Fearless. In this work, we first adapt the LTS framework to a Canadian context and apply it to Edmonton’s network to understand the connectivity improvements stemming from the implementation of a network of physically protected bike lanes in the city’s core in 2017. Our metrics show an important increase in network integration and an almost four-fold increase in connected origin-destination pairs. We then ask whether the LTS framework adequately captures the comfort of the Four Types of Cyclists, and whether the Four Types of Cyclists adequately represents the distribution of cyclist types in Edmonton. To answer these questions, we developed a survey where we presented respondents with cycling environment descriptions and video clips, and asked them to rate their perceived comfort. We also asked about their intent to cycle more often than they do now, their cycling habits, and demographic information. We analyzed survey results to test the existing cyclist typology and determine whether a new one is warranted, using variables as similar as possible to the Four Types of Cyclists. Our results show a three-level typology better describes survey respondents and uncovers some limitations of the Four Types of Cyclists as applied to an Edmonton population. Our three types of cyclists are Uncomfortable or Uninterested, Cautious Majority, and Very Comfortable Cyclists. We then apply binary logistic regression to understand environmental and infrastructure characteristics that make each cyclist type most comfortable. We pair this data with the comfort ratings and route descriptions from a subset of survey respondents to develop an updated LTS framework called Level of Cycling Comfort (LCC). The levels of the LCC framework map onto the three types of cyclists to reflect their perceived comfort on different types of infrastructure. Overall, dedicated cyclist/pedestrian paths and certain protected lanes are suitable for the Uncomfortable or Uninterested; protected lanes and very calm residential streets are adequate for the Cautious Majority; most other cycling conditions with up to two lanes of traffic per direction and 60 kph motorized traffic speeds are suitable for Very Comfortable Cyclists. Finally, we use the LCC framework to reassess network connectivity and compare results with those obtained using the LTS framework. The LCC framework generally shows a less optimistic, but more realistic assessment of network connectivity compared to the LTS framework.
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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 | 0.001 |
| 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".