Abstract
Air Traffic Management (ATM) is a complex socio-technical system, whose behaviour depends on a combination of various subsystems of different nature: societal, technical, and human. Due to such aspects, it is difficult to understand which could be the part to be changed in order to improve performances, or which is the impact of a change on the overall performances. Such tasks are though issues, and cannot be easily performed. In this work, a new approach for the ATM change management process is proposed. It aims to introduce an innovative multidisciplinary process by combining the following different paradigms: the agent-based paradigm for the modelling of a change solution and the assessment of the achieved performances; the evolutionary computing paradigm for the tuning of the change: the sensitivity analysis to understand which part of the ATM system should be changed in order to match the targeted performance levels.
Highlights
Despite the excellent services supported by present Air Traffic Management (ATM) system, present architecture does not provide an efficient mechanism to adapt the capacity to the demand by exploiting the flexibility of the air transport system
The proposed work defines a new approach in order to perform the change assessment in ATM system by supporting all foreseen steps, from the strategic thinking to the change impact assessment
The innovation potential of this proposal lies both in the innovativeness of Agent-based Evolutionary Search (AES) application in the ATM field and in the strongly interdisciplinary vision inspiring our work
Summary
Despite the excellent services supported by present Air Traffic Management (ATM) system, present architecture does not provide an efficient mechanism to adapt the capacity to the demand by exploiting the flexibility of the air transport system. The key objectives are to restructure European airspace as a function of air traffic flows; to create additional capacity; to increase the overall efficiency of the ATM system. The design and the validation of the changes are tough issues due to the fact that the evaluation of the impact of a possible change on the overall ATM system cannot be performed. This work proposes an innovative process to perform the change management by combining the agent-based paradigms with evolutionary computing and sensitivity analysis. It discusses preliminary considerations on the approach itself, the Agent-Based modelling paradigms to adopt, the sensitivity analysis, and the possible Evolutionary algorithms to use; the referring case study to validate the approach; the performances to apply
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