pr\u00e9sentent<\/p>\n\n\n\n
Autoris\u00e9 \u00e0 pr\u00e9senter ses travaux en vue de l\u2019obtention du Doctorat de l’Institut Polytechnique de Paris, pr\u00e9par\u00e9 \u00e0 T\u00e9l\u00e9com SudParis en :<\/p>\n\n\n\n
le JEUDI 4 D\u00e9CEMBRE 2025 \u00e0 14h00<\/p>\n\n\n\n
\u00e0<\/p>\n\n\n\n
Salle 4B01
19 place Marguerite Perey, 91120 Palaiseau<\/p>\n\n\n\n
Membres du jury :<\/strong><\/p>\n\n\n\n M. Mounim A. EL YACOUBI<\/strong>, Full professor, T\u00e9l\u00e9com SudParis, FRANCE – Directeur de th\u00e8se R\u00e9sum\u00e9 :<\/strong><\/p>\n\n\n\n L\u2019accessibilit\u00e9 d\u2019un lieu mesure la facilit\u00e9, pour les personnes qui y r\u00e9sident, d\u2019atteindre les opportunit\u00e9s environnantes, telles que les \u00e9coles, les commerces ou les emplois. Cette th\u00e8se s\u2019int\u00e9resse \u00e0 l\u2019accessibilit\u00e9 offerte par les Transports Publics (TP). Les TP conventionnels, bas\u00e9s sur des lignes et des horaires fixes, entra\u00eenent une r\u00e9partition in\u00e9gale de l\u2019accessibilit\u00e9 : elle est g\u00e9n\u00e9ralement bonne dans les centres-villes mais faible en p\u00e9riph\u00e9rie, qui devient ainsi d\u00e9pendante de la voiture. Cela rend les villes insoutenables sur les plans environnemental, \u00e9conomique et social. Les services de mobilit\u00e9 flexible (par ex., le Transport \u00e0 la Demande \u2013 TAD) semblent mieux adapt\u00e9s aux zones de faible densit\u00e9 et peuvent efficacement compl\u00e9ter les TP conventionnels. Toutefois, la plupart des m\u00e9thodes visant \u00e0 optimiser la conception et l\u2019exploitation de la mobilit\u00e9 flexible ciblent des objectifs traditionnels, tels que les co\u00fbts pour les usagers et les co\u00fbts op\u00e9rationnels, en n\u00e9gligeant l\u2019accessibilit\u00e9. L\u2019objectif g\u00e9n\u00e9ral de cette th\u00e8se est de d\u00e9velopper de nouvelles m\u00e9thodes pour concevoir les syst\u00e8mes de TP de prochaine g\u00e9n\u00e9ration, incluant TP conventionnels et flexibles, ayant pour finalit\u00e9 de r\u00e9duire les in\u00e9galit\u00e9s dans la distribution de l\u2019accessibilit\u00e9. Cette th\u00e8se comporte quatre contributions. Les premi\u00e8re et deuxi\u00e8me contributions consistent \u00e0 proposer des m\u00e9thodes de planification des TP visant \u00e0 r\u00e9duire les indices d\u2019in\u00e9galit\u00e9 d\u2019accessibilit\u00e9. Des solutions originales bas\u00e9es sur des heuristiques et sur l\u2019apprentissage par renforcement sur graphes sont propos\u00e9es. La troisi\u00e8me contribution d\u00e9veloppe, \u00e0 notre connaissance, la premi\u00e8re m\u00e9thode de planification pour l\u2019allocation d\u2019une flotte de TAD, avec pour objectif la r\u00e9duction des indices d\u2019in\u00e9galit\u00e9 d\u2019accessibilit\u00e9. Dans cette contribution, nous combinons une repr\u00e9sentation graphique du TP conventionnel et un mod\u00e8le d\u2019Approximation Continue du TAD. Nous proposons une m\u00e9thode d\u2019optimisation bi-niveaux, o\u00f9 le niveau sup\u00e9rieur est r\u00e9solu via une approche hybride combinant une heuristique bas\u00e9e sur le classement et l\u2019Optimisation Bay\u00e9sienne pour allouer la flotte de TAD, tandis que le niveau inf\u00e9rieur effectue l\u2019affectation des d\u00e9placements. La quatri\u00e8me contribution consiste \u00e0 concevoir un nouveau syst\u00e8me de TP flexible, situ\u00e9 entre le TP conventionnel et la mobilit\u00e9 flexible, combinant l\u2019efficacit\u00e9 d\u00e9coulant de la structure forte du premier et l\u2019adaptabilit\u00e9 du second. La gestion op\u00e9rationnelle d\u2019un tel syst\u00e8me est assur\u00e9e par une optimisation en horizon glissant fond\u00e9e sur la recherche arborescente de Monte-Carlo (Monte Carlo Tree Search). Cette th\u00e8se offre une perspective sur l\u2019op\u00e9rationnalisation de l\u2019accessibilit\u00e9 et de l\u2019\u00e9galit\u00e9 dans la conception des syst\u00e8mes de TP : alors que ces deux aspects ont \u00e9t\u00e9 analys\u00e9s dans la litt\u00e9rature de mani\u00e8re ex-post, les m\u00e9thodes propos\u00e9es ici permettent de les internaliser ex-ante, directement au sein des objectifs d\u2019optimisation.<\/p>\n\n\n\n Abstract :<\/strong><\/p>\n\n\n\n The accessibility of a location measures the ease, for people leaving there, to reach surrounding opportunities, such as schools, shops, or jobs. This thesis focuses on accessibility provided by Public Transport (PT). Conventional PT, based on fixed lines and schedules, results in an unequal distribution of accessibility: it is generally good in city centers but poor in the suburbs, which are thus car-dependent. This makes cities environmentally, economically, and socially unsustainable. Flexible mobility services (e.g., Demand-Responsive Transport (DRT)) are potentially better suited for low-density areas and can effectively complement conventional PT. However, most methods to optimize the design and operation of flexible mobility target traditional objectives, e.g., user and operational costs, neglecting accessibility. The overarching aim of this thesis is to develop novel methods for designing future-generation PT systems, including conventional and flexible PT, whose objective is to reduce the inequality of accessibility distribution. This thesis comprises four contributions. The first and second contributions consists in providing PT planning methods to reduce accessibility inequality indices. Original solutions based on heuristics and graph-based reinforcement learning are provided. The third contribution devises, to the best of our knowledge, the first planning method for DRT fleet allocation, with the objective of reducing accessibility inequality indices. In this contribution, we combine a graph representation of conventional PT and a Continuous Approximation model of DRT. We provide a bilevel optimization method, where the upper level is solved via a hybrid approach, combining a rank-based heuristic and Bayesian Optimization, to allocate the DRT fleet and the lower level performs transport assignment. The fourth contribution consists in devising a novel flexible PT system, which sits between conventional PT and flexible mobility, combining the efficiency resulting from the strong structure of the former and the adaptivity of the latter. The operational management of such a system is done via a rolling horizon optimization based on Monte-Carlo Tree Search. This thesis offers a perspective on operationalizing accessibility and equality in the design of PT system: while these two aspects have been analyzed in the literature ex-post, the methods proposed here allow to internalize it ex-ante, directly within the optimization objectives.<\/p>\n","protected":false},"excerpt":{"rendered":" L’Ecole doctorale : Ecole Doctorale de l’Institut Polytechnique de Paris et le Laboratoire de recherche SAMOVAR – Services r\u00e9partis, Architectures, Mod\u00e9lisation, Validation, Administration des R\u00e9seaux pr\u00e9sentent l\u2019AVIS DE SOUTENANCE de Monsieur Duo WANG Autoris\u00e9 \u00e0 pr\u00e9senter ses travaux en vue de l\u2019obtention du Doctorat de l’Institut Polytechnique de Paris, pr\u00e9par\u00e9 \u00e0 T\u00e9l\u00e9com SudParis en : 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M. Jakob PUCHINGER<\/strong>, Full professor, EM Normandie, FRANCE – Rapporteur
M. Francisco (C\u00e2mara) PEREIRA<\/strong>, Full professor, Technical University of Denmark, DANEMARK – Rapporteur
M. Roberto WOLFLER CALVO<\/strong>, Full professor, Universit\u00e9 Paris-13, FRANCE – Examinateur
Mme Negin ALISOLTANI<\/strong>, Assistant professor, Universit\u00e9 Gustave Eiffel, FRANCE – Examinateur
M. Sebastian H\u00f6RL<\/strong>, Charg\u00e9 de recherche, IRT SystemX, FRANCE – Examinateur
M. R\u00e9my CHEVRIER<\/strong>, Docteur, SNCF, FRANCE – Examinateur
M. Andrea ARALDO<\/strong>, Associate Professor, Institut Polytechnique de Paris \u2013 T\u00e9l\u00e9com SudParis, FRANCE – Co-encadrant de th\u00e8se<\/p>\n\n\n\n\u00ab Conception des transports publics de nouvelle g\u00e9n\u00e9ration pour r\u00e9duire les in\u00e9galit\u00e9s d\u2019accessibilit\u00e9 \u00bb<\/h2>\n\n\n\n
pr\u00e9sent\u00e9 par Monsieur Duo WANG<\/h2>\n\n\n\n