Abstract

International audience; Process flexibility has been investigated in depth in the context of intra-organisational processes, but it is still an open issue when processes cross the boundaries of companies. In this paper, we address the modelling of flexible inter-organisational processes using a version-based approach. Indeed, versions are known to be a powerful technique to deal with variability, evolution and adaptation of processes, which are the three main needs of process flexibility. More precisely, this paper presents VP2M (Version of Process Meta-Model), a meta-model supporting the modelling of versions of inter-organisational processes, addressing both static and dynamic aspects of VP2M. It also illustrates process version modelling within the Subsea Pipeline process example.

Abstract

International audience; Air traffic generators are widely used in the air traffic control and aeronautics industry for training purposes and to validate new concepts or new systems. But it is difficult for a machine to generate realistic trajectories and behavior for an aircraft which lead to the participation of many humans in the simulation to compensate. Traditional generators require performance data for aircrafts and heavy preparation to generate realistic trajectories. Our approach takes advantage of widespread flight location data to learn from their behavior and improve traffic generation. Combining cooperative multi-agent learning methods [1] and big data we show that it is possible to design and generate a realistic and intelligent traffic more easily and without human intervention.

Abstract

International audience; In the near future, air traffic control (ATC) will have to cope with a radical change in the structure of air transport [1]. Apart from the increase in traffic that will push the system to its limits, the insertion of new aerial vehicles such as drones into the airspace, with different flight performances, will increase its heterogeneity. Current research aims at increasing the level of automation and partial delegation of the control to on-board systems. In this work, we investigate the collision avoidance management problem using a decentralized distributed approach. We propose an autonomous and generic multi-agent system to address this complex problem. We validate our system using state-of-the-art benchmarks. The results underline the adequacy of our local and cooperative approaches to efficiently solve the studied problem.