De nos jours, l’intérêt porté à la préservation de l’environnement à travers la réduction des émissions de gaz à effet de serre prend de plus en plus d’ampleur. Depuis 2006,la politique multimodale a évolué vers une politique co-modale qui n’oppose plus la voiture au transport public mais encourage une combinaison de tous les modes de transport sans favorisation dans le but d’une optimisation du service. Placés dans ce cadre, le but de cette thèse est de mettre en œuvre un système de gestion de véhicules partagés qui recouvre tous les services de transports existants tel que le transport public, le covoiturage, les véhicules en libre service et qui capable de satisfaire les demandes des utilisateurs en leur fournissant des itinéraires co-modaux optimisés en terme de temps, coût et émission des gaz à effet de serre tout en respectant leurs préférences et priorités. En recevant plusieurs requêtes simultanées en un court laps de temps, le système doit être capable à la fois de décomposer les solutions en tronçons que nous appelons Routes, en respectant toutes les similarités entre les différentes demandes et de regrouper les informations de manière cohérente pour déterminer les combinaisons de Routes possibles. Vu l’aspect dynamique et distribué du problème, une stratégie de résolution efficace mettant à profit une mixture de concepts ; à savoir les systèmes multi-agents et l’optimisation a été mise en place. Les résultats expérimentaux présentés dans cette thèse justifient l’importance de la co-modalité et la nécessité de mettre à profit la complémentarité entre les véhicules partagés et les autres moyens de transport à travers un système intelligent et global / Nowadays, the protection of the environment through the reduction of greenhouse gases is becoming more and more important. In order to resolve environmental problems, a multimodal policy is firstly adopted in order to encourage the use of public transport. Since 2006, a new notion: the co-modality is introduced and it consists on developing infrastructures and taking measures and actions that will ensure optimum combination of individual and public transport modes. In this context, the purpose of this thesis is to implement co-modal transport system that covers all the existing transport services such as the public transport, the carpooling or the free use vehicles (bikes, cars). In order to satisfy the user’s requests, the system offers optimized co-modal itineraries in terms of three criteria: total time, total cost and greenhouse gases emission taking into account their preferences and constraints. In a short time interval, many transport users can formulate simultaneously a set of requests. So the system should find feasible decompositions in terms of independent sub-itineraries called Routes recognizing similarities and recognize the different possibilities of Routes Combinations to compose each itinerary demand. Considering the dynamic and distributed aspect of the problem, an effective strategy combining different concepts like multi-agent system and optimization methods is applied. The experimental results presented in this thesis justify the importance of co-modality and the necessity of taking advantage of the complementarity between the shared vehicles and other means of transportation through an intelligent and global system

This paper discusses the implications of autonomous-connected-electric-shared vehicles (ACES) for public finance, which have so far been widely ignored in the literature. In OECD countries, 5-12% of federal and up to 30% of local tax revenues are currently collected from fuel and vehicle taxation. The diffusion of ACES will significantly reduce these important sources of government revenues and affect transport-related government expenditures, unless additional policies are introduced to align the new technological context with the tax revenue requirements. We argue that the realization of socioeconomic benefits of ACES depends on the implementation of tailored public finance policies, which can take advantage of the increase in data availability from the further digitalization of transportation systems. In particular, the introduction of road tolls in line with "user Pays" and "polluter Pays" principles will become more feasible for policy. Moreover, innovation in taxation schemes to fit the changing technological circumstances may alter the relative importance of levels of governance in transport policy making, likely shifting power towards local, in particular urban, governmental levels. We finally argue that, given the risk of path-dependencies and lock-in to sub-optimal public finance regimes if policies are implemented late, further research and near-term policy actions taken during the diffusion process of ACES are required.