Analyzing Network Connectivity by Cyclist Comfort: An Empirical Reappraisal of the Four Types of Cyclists Typology and Level of Traffic Stress Framework
Notice bibliographique
Résumé
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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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».