Notice bibliographique
Résumé
Fairness is an important concept in transportation system because transport services are generally recognized as public goods and affect travellers’ access to basic needs. Moreover, transportation system has significant impacts on all facets of communities and these impacts may be significantly different for travellers from different groups. Thus, there is a need for considering fairness in transportation system planning. The thesis proposes methodologies to evaluate fairness impacts and design fair transportation systems. A mathematical model is developed to evaluate the fairness impacts of congestion pricing accompanied with revenue neutral mechanism and transit network re-design. The revenue-neutral mechanism uses the revenue from congestion pricing to finance public transit. This model refines existing models for cost structure of transit and road networks to predict the effects of congestion pricing policies on travel times and travel costs. The mode shift from cars to public transit is also incorporated by a choice mode. The proposed mode is implemented on Sydney Central Business District to evaluate the fairness impacts of congestion pricing policies. The evaluation results reveal that congestion pricing policies benefit transit-dependent and low-income groups and reduce the performance gap between cars and public transit. Hence, congestion pricing policies are fair if the revenue is refunded and the transit network is improved. The evaluation also suggests to assign the pricing revenue to different groups for improving public acceptability. In the context of congestion pricing revenue assignment problem. An investigation into the properties of fairness schemes is conducted. Four revenue assignment mechanisms corresponding to opportunity fairness, individual value proportional fairness, marginal value proportional fairness, and market fairness are examined to demonstrate their properties and highlight their policy implications. Then, these assignment mechanisms are applied on Winnipeg’s downtown network. The results illustrate that market fairness is the most axiomatically restrictive and is complex to compute, while opportunity fairness is the least restrictive but requires the minimal computational resources. The results also reveal that individual value proportional fairness and marginal value proportional fairness are equivalent to market fairness when the coalition effects are zero. Apart from the theoretical comparison, the lower bounds for the assignment mechanisms are characterized and a paradoxical situation where a market fairness or marginal value proportional fair assignment involves taxing a certain group is demonstrated. Finally, a model to seek the fair and efficiency subsidy schemes in the oligopolistic transit system is proposed. The model incorporates a market competition model to represent the competition between transit operators. It also includes a discrete choice model to account travellers’ mode choice behaviour. The numerical analysis illustrates the capability of the proposed model and presents empirical evidence of the trade-off between efficiency and fairness in transit system. The core contribution of the thesis is to provide insights into the properties of fairness in transportation system and to develop modelling tools to promote transportation system fairness.
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 | 0,008 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,005 |
| Communication savante | 0,006 | 0,008 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 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 ».