Agent-based modelling and simulation for quantification of resilience in air transport

Abstract

Socio-technical systems consist of deeply interconnected and interdependent social entities and technical systems that collaborate to achieve a global goal. The individual characteristics and behaviours of each involved actor and their interactions define the resulting overall emergent system behaviour. Due to increased complexities in socio-technical systems traditional safety risk assessment strategies are found to become less suitable to predict, to reveal and to understand emergent system behaviour. In recent years there has therefore been a shift in the way how safety in complex socio-technical systems is perceived. The relatively new safety management paradigm called resilience engineering focusses on the ability of socio-technical systems to cope with varying conditions by applying everyday performance. Recent studies related to resilience engineering insist on the need for more structured modelling approaches for analysis and quantification of resilience in socio-technical systems. This study contributes to this need by presenting a quantitative agent-based modelling and simulation approach. The suitability of such approach for more profound analysis and quantification of resilience in socio-technical systems has been studied in the context of conventional approach operations during a sudden and unexpected bad weather disturbance. The formal agent-based model that has been developed for this resilience study especially emphasized the role of executive controllers in achieving and maintaining resilience. The adaptive strategies that are considered for this purpose are multiple vectoring strategies, the initiation of holding operations and go-arounds. The resilient capacities of conventional approach operations have been quantified using the emergent outcomes of these adaptive strategies. Considering the obtained simulation results and gained insight there can be concluded that quantitative agent-based modelling and simulation is a suitable, structured and powerful approach for more profound analysis and quantification of resilience in socio-technical systems.