The Development and Deployment of a GIS tool for Transit Network Design
Notice bibliographique
Résumé
Public transportation contributes to sustainable transportation in urban areas. Unfortunately, in some cases public transit systems have been underperforming. Over the years, factors such as urban sprawl and the increase in private vehicle ownership have led to challenges for public transportation providers. The lack of investment in transit infrastructure has resulted in transit agencies being under resourced which further limit the agencies’ ability to respond. Realizing the need to change and move towards a more sustainable and balanced transportation system, governments have begun to invest more and more in transportation infrastructure projects. \nIn order to encourage public transportation, focus has shifted to improving the quality of transit service being provided. There are many ways in which transit improvements can be made. The problem that describes the design of a public transportation network is referred to as the transit network design problem (TNDP). Much of the existing literature that addresses the TNDP describes methods that are rigorous and complex and have limited application in practice. Given the emergence of geographic information systems (GIS), there exists new opportunities to address the TNDP. \nThis thesis presents a customized GIS tool that assists transit network design. The approach utilizes GIS to identify desire lines or major travel demand corridors from which trunk transit routes are proposed and evaluated. The GIS tool is built using VBA scripting in ArcMap 9.3 part of ESRI’s general ArcGIS suite but the underlying GIS functionality needed by the tool is not limited to ESRI software. The tool offers a proven methodology for use within transit network design and evaluation at a level of resource requirement that is consistent with most transit agencies. The tool has been customized to minimize the need for GIS training and to maximize its adaptability for application in multiple cities. The analyst applying the tools must have substantial knowledge of local conditions. \nThe tool is applied to the Regional Municipality of Waterloo, Ontario, Canada, at the TAZ (traffic analysis zone) level using population and employment data. A street network with corresponding posted speeds on each link and the location of signalized intersections were also used in the analysis. The results of the analysis depicted major flows throughout Kitchener, Waterloo and Cambridge. Unique flows from students, major employers and an analysis of average income levels also provide input into the major demand corridors. From these results seven high order transit routes were designed to accommodate the major demand corridors. \nFrom the results it was found that GIS can be used to depict major demand corridors and inform transit network design. GIS is an excellent tool that can display complex information and visually identify spatial patterns. Further research includes the development of a model that evaluates network alternatives or the development of quantitative methods by which limits on aggregation can be automated.
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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 | 0,003 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,025 | 0,007 |
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 ».