All over the world, many research studies focus on developing and enhancing real-time communications between various transport stakeholders in urban environments. Such motivation can be justified by the growing importance of pollution caused by the transport sector in urban areas. In this work, we propose an approach of assistance for displacement in urban environment taking advantages of multimodal urban transportation means, where several modes of public transports are available. In addition, we also consider the possibility of using both private modes of transport and cities parking. The proposed distributed approach described in this paper is based on an abstraction of a city multimodal graph according to the available modes of public transport and road traffic and transition graph approach to move from a mode to the other mode. Numerical results are developed to justify the effectiveness of our approach.

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Throughout the world and particularly in urban areas, population growth can be listed as a direct cause of the uprising use of personal vehicles in cities around the world. Such attitude may lead to dramatic consequences, not only economically, but socially and environmentally. To meet these challenges, and to promote the use of multiple means of public transports by citizens, public authorities and transport operators seek − within the framework of the implementation of connected cities projects and intelligent − to optimize the extraction as well as the exploitation of the multimodal information by developing Interactive Systems of Assistance to the Multimodal Movement (IAMM). However, finding the optimal multimodal path for a given person is far from being a simple matter. Indeed, each potential user may have different or unique preferences regarding the: cost and/or duration of his/her journey, number of mode changes, comfort or safety levels desired. In the present study, we propose a multi-agent system which, based on the parameters entered by each user, proposes the optimal paths in the Pareto sense, including different public transport modes, private cars and parking availability.

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Abstract-In this paper, are presented the general architecture and implementation of a multi-task distributed vision system designed and embedded onboard a Hex-Rotorcraft UAV. The system uses multiple cheap heterogeneous cameras in order to perform various tasks such as: ground target pedestrian detection, tracking, creating panoramic images, video stabilization and streaming multiple data/video feeds over a wireless secure channel. In what follows, are discussed this multiagent architecture designed to provide our UAV with an embedded intelligent vision system using autonomous agents entrusted with managing the previously listed functionalities. In addition to the cheap set of USB and module cameras, the presented vision system is composed of a Local Data Processing Module connected to each camera and a Central Module used to control the overall system, process the regrouped data and streams it to the ground station. The overall vision system has been tested in real flights and is still under improvements.