Régulation de trafic urbain multimodal : une modélisation multi-agents. (Cooperative system for multimodal traffic regulation : a multiagent model)

Since several decades, urban congestion causes various problems and deteriorate the quality of life of citizens who live in cities. Several methods are used to reduce urban congestion, notably traffic regulation and promotion of public transportation. Since the 1990’s, the usage of tools from artificial intelligence, particularly distributed methods and multi-agent systems, allowed to design new methods for traffic regulation. Indeed, these methods ease to take into account the complexity of traffic-related problems with distribution. Moreover, the improvement of the communication abilities of the vehicles and the coming of autonomous vehicles allow to consider new approaches for regulation, in which the vehicles and infrastructures collaborate. The research work presented in this work is twofold. First we propose a method for traffic regulation at an intersection based on automatic negotiation. Our method is based on an argumentation system describing the state of the traffic and the preferences of each vehicle, relying on reasonning methods for vehicles and infrastructures. Our regulation method enables to coordinate the crossing of the intersection with more accuracy than traffic lights, taking into account the complexity of the environment and individual trajectory of each vehicle. Moreover, our method allows the application of specific regulation policies on a larger scale. In the second part of this thesis, we propose a coordination method for buses with the other vehicles. Indeed, in contemporary regulation systems the bus often benefit from priority on an intersection, but they suffer from traffic deterioration and it has to be taken into account because this damages their efficiency. Our method allows a bus to coordinate in an anticipatory way with the next intersections on its trajectory, in order to define a common regulation policy allowing the bus to reach its next stop without suffering from potential congestions. Setting up this policy is based on the regulation method for the intersection described previously.