Notice bibliographique
Résumé
A larger amount of funding and attention are going toward highway infrastructure of Ontario for rehabilitation, maintenance and construction projects. These rehabilitation and maintenance activities on highways involve lane closures, which reduce the traffic throughput and cause delays for the road users. The impact of these activities is very important and has led to research into improvements of work zones in Ontario. To prevent the significant cost that these construction delays have on the general public, contractors are required to keep highway lanes open during the peak traffic hours and work at night. However, working at night may reduce the quality of the work by increasing cold joints and construction joints in the pavement, and may increase the amount of time needed to complete the work. Therefore, finding a balance between the times that the lanes can be closed and the times they should be kept open requires an accurate prediction of the construction work zone throughputs, which can increase the efficiency of the contractor work, save money and reduce the user delay costs. \n \nConsequently, this study which has been funded by the Ministry of Transportation of Ontario (MTO) Highway Infrastructure Innovation Funding Program (HIIFP) involves measurement of highway construction work zones throughput of Southern Ontario, to determine the factors affecting the throughput. It has been carried out in partnership with researchers at the University of Toronto. For this study, a manual counting method for collecting throughput data has been employed. This involved data collection of variables such as heavy vehicles which had not been included in previous studies. This provides the visual confirmation of queuing and assists in evaluating the intensity of work activity at the work zones. New generic models for throughput have been developed in this research to better describe current state-of-the practice on Southern Ontario highways. Furthermore, a better functioning highway specific model was developed to calculate the throughput of the MTO Southern Ontario Highway network. In addition to development of these new models, this project involved further development and refinement to a spreadsheet based model SZUDA (Simplified work Zone User Delay Analysis) that uses normal hourly traffic flows to calculate the resulting queue for that entire hour and approximate user delay cost associated with road user delay. \n \nOverall, the thesis describes a methodology for collection of data in work zones. This involved collection of data during 2009 and 2010 Ontario construction season. Furthermore, the data were then used to develop more reliable generic and highway specific models for the MTO. These models can be used to determine when and how work zones should be established. Finally the refined SZUDA model and case studies demonstrate the impact of various work zone configurations on the traveling public.
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 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».