Notice bibliographique
Résumé
Visibility is one of the basic requirements for safe driving. Any type of vision obstruction can interfere with the driver’s ability to operate a vehicle and thus poses a significant risk to road traffic safety. In addition to widely investigated adverse weather conditions such as rain, fog, and snow, which can reduce visibility, bright sunny days may also bring challenges to safe driving due to the phenomenon of sun glare. Although much evidence has been found to support that sun glare can highly impair one’s visual performance, there are significant gaps in the knowledge and methodology dedicated to examining and quantifying the sole effects of sun glare on road safety. The overall objective of this thesis is to gain a better understanding of the risks on the road network posed by sun glare and evaluate its safety effects in the city of Edmonton. To achieve this objective, a two-stage analysis was conducted. The first stage developed a methodology to model sun glare occurrence for the road network in the city, aiming to identify when and where a driver would be exposed to the risk of sun glare by considering different factors associated with the sun’s position and road geographical conditions. Consequently, potential sun glare time windows were demarcated for each month over a typical year and corresponding glare prone locations were identified and plotted in a series of visualization maps, which can provide a reference to the public for identifying locations where sun glare is most prominent in the city of Edmonton. After identifying the glare prone locations, the safety risks at those locations during sun glare periods were assessed in the second stage. By contrasting the number of collisions during glare and non-glare conditions, this second stage aimed to quantify the sole effects of sun glare on road collisions. A case-control design method was used to control for potential confounding factors related to weather condition, collision time/location, and travel direction. To test the significance of the differences in collision numbers, several statistical techniques were employed and included: chi-square test of independence, configural frequency analysis, and the Wilcoxon signed rank test. Ultimately, three major findings were concluded from the results of the collision analysis. First, sun glare was found to significantly contribute to collision occurrence, especially at road intersections. Quantitative assessments showed that collisions were expected to increase by about 30% under the condition of sun glare. Second, sun glare effects during mornings and evenings were observed to be especially worse in the months of spring and fall. Also, most of the daytimes in January, November, and December, traffic safety in the southbound direction was significantly affected by sun glare. Lastly, certain collision maneuver types were over-presented during sun glare. It was found that the collisions due to signal violations and failing to yield to pedestrians and cyclist were over-presented at intersections. At mid-block locations, the proportions of collisions due to improper turning and lane changes were observed to be significantly higher. Overall, the approaches proposed and developed in this thesis provide a new and innovative method to quantify the effects of sun glare on road safety. By linking sun glare exposure modeling with a thorough glare related collision assessment, this research helps to provide additional insights about the extent by which sun glare affects road safety. The findings from this thesis can be used to assist in alleviating the risks associated with sun glare in the planning and designing of future roads.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 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 | 0,000 |
| 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 ».