Analyzing the behavior of cyclists at intersections to improve behavior variability within micro-simulation traffic models
Notice bibliographique
Résumé
The purpose of this thesis can be separated into two components: \nComponent 1: \n\tThe purpose of this component was to update the input parameters for cyclists for application in mixed-traffic micro simulation models. This component used GPS data from cyclists to develop distributions of desired speed under variable road and facility conditions. Desired speed distributions as a function of road grade and the effect that road surface and facility type have on desired speed were analyzed. The findings suggest that facility type (multi-use trail, bike lane, and no bike lane) had no significant effect on the desired speed of the cyclists in the study. A distribution of the desired speed of cyclists was developed and can be applied to improve variability within micro-simulation traffic models. \nComponent 2: \nThe purpose of this component was to observe and analyze the left turn behavior of cyclists at different types of signalized intersections in the City of Toronto with the intent of recommending what facilities are most effective at facilitating left turning movements under varying input conditions. From the observations, a database was created that includes turning behavior, approach conditions, and individual cyclist related variables for each cyclist. \nBy analyzing the behavior data base, conclusions were made regarding the effect that intersection type, facility type, and input conditions have on the rule compliance and facility compliance of the cyclists that were observed. From these conclusions, recommendations have been made that are intended to suggest some facility interventions that will result in improved rule compliance and facility compliance, ultimately creating a more comfortable cycling environment and one that matches that natural tendencies of cyclists in the city. \nThe measurement of rule compliance in this report is based on the simple observation of whether the cyclists, when making a left turn at the intersection, complied with the rules of the road or broke the rules of the road as defined by the Ontario Highway Traffic Act. The measurement of facility compliance is based on whether the cyclist made a left turn using the facility as the design intends them to use it. \nCyclist behaviors at five different intersection configurations were observed in the study. This sample of intersection configurations is significant as they represent most of the generic intersection types that are located throughout Toronto’s cycling network. The distribution of these behaviors for each intersection type can be considered in micro-simulation models when considering the stochastic nature of a cyclists and their decision process with regards to navigating a left turn through an intersection. \nFacilities with more left turning options proved to promote rule compliance more so than the intersections with fewer options.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».