Studying hazards for resilience modelling in ATM Mathematical Approach towards Resilience Engineering in ATM ( MAREA )

Foreword — This paper describes a project that is part of SESAR WP-E, which is addressing long-term and innovative research. Abstract — Resilience engineering purports to improve the safety in complex socio-technical systems, such as in air traffic management (ATM). The MAREA project aims to support a more systematic analysis of resilience in ATM by developing a mathematical modelling and analysis approach for resilience engineering in ATM. Key elements will be models for humanrelated aspects. This paper describes the basis for this development. It describes model constructs of existing safety analysis methods. It presents a broad set of ATM hazards, highlighting various sources of performance variability in the ATM socio-technical system. It discusses interviews with pilots and controllers about their ways to deal with hazards. It studies the potential of the existing model constructs to describe the performance variability indicated by the hazards. It is concluded that multi-agent dynamic risk modelling can represent a wide variety of performance variability in complex ATM scenarios and has the potential to systematically analyse risk and resilience.

[1]  Nancy G. Leveson,et al.  A new accident model for engineering safer systems , 2004 .

[2]  Andres G. Zellweger,et al.  Accident Risk Assessment for Advanced Air Traffic Management , 2001 .

[3]  Rogier Woltjer,et al.  Functional modeling for risk assessment of automation in a changing air traffic management environment , 2008 .

[4]  Christopher Nemeth,et al.  Preparation and restoration , 2009 .

[5]  Robert L. Wears,et al.  Resilience Engineering: Concepts and Precepts , 2006, Quality and Safety in Health Care.

[6]  Erik Hollnagel,et al.  Resilience Engineering approach to safety assessment: an application of FRAM for the MSAW system. , 2009 .

[7]  J. Forrester Industrial Dynamics , 1997 .

[8]  Rogier Woltjer,et al.  Functional Modeling of Constraint Management in Aviation Safety and Command and Control , 2009 .

[9]  Erik Hollnagel,et al.  Barriers And Accident Prevention , 2004 .

[10]  Henk A. P. Blom,et al.  Systemic accident risk assessment in air traffic by Monte Carlo simulation , 2009 .

[11]  C. Nemeth Resilience Engineering Perspectives, Volume 1: Remaining Sensitive to the Possibility of Failure , 2008 .

[12]  Nancy G. Leveson,et al.  Engineering a Safer World: Systems Thinking Applied to Safety , 2012 .

[13]  Henk A. P. Blom,et al.  Compositional Specification of a Multi-Agent System by Stochastically and Dynamically Coloured Petri Nets , 2006 .

[14]  Henk A. P. Blom,et al.  Multi-agent situation awareness error evolution in accident risk modelling , 2003 .

[15]  G. J. Bakker,et al.  NLR-TP-2011-291 CONTRASTING SAFETY ASSESSMENTS OF A RUNWAY INCURSION SCENARIO BY EVENT SEQUENCE ANALYSIS VERSUS MULTI-AGENT DYNAMIC RISK MODELLING , 2011 .

[16]  Erik Hollnagel,et al.  Human Reliability Analysis: Context and Control , 1994 .

[17]  Tamsyn Edwards Human performance in air traffic control , 2013 .

[18]  Mica R. Endsley,et al.  Toward a Theory of Situation Awareness in Dynamic Systems , 1995, Hum. Factors.

[19]  Henk A. P. Blom,et al.  Multi-Agent Situation Awareness Error Evolution in Air Traffic , 2004 .