Using Complementary Models-Based Approaches for Representing and Analysing ATM Systems' Variability

International audienceLarge-Scale Socio-Technical Systems, such as Air Traffic Management (ATM), are organizations where different interconnected systems work together to achieve a common goal. Analysis of variability is particularly challenging in these systems of systems due to the non-linear and complex interactions among social and technical functions. This paper proposes a systematic approach able to represent and to reason about the variability of such socio-technical systems. The proposed approach is based on the synergistic use of 3 models able to represent the variability from different points of view. This federation of models focusses the analysis on the relevant aspects of the systems of systems at different levels of granularity. The models taken into account for the representation of system variability are FRAM [12] focusing on organizational functions, HAMSTERS [17], which is centred on human goals and activities and ICO [20] which is dedicated to the representation of systems' behaviour (including the user interface). The paper presents a detailed development process describing how the models are built and analysed. This process is exemplified on a case study involving the AMAN (Arrival MANager) system

Modelling of Automation Degradation : a Case Study

National audienceThis paper presents a modeling approach that has been developed within the SPAD project for analyzing consequences of automation degradation in large socio-technical systems. This modeling approach involves two different notations: FRAM [6] and HAMSTERS [2], [8]. In previous work [7] we have proposed a synergistic approach integrating these two views for describing the evolution of system performances under automation degradation. The focus of the paper is on how the outcome of the models can be integrated to analyse system behavior. After describing the principles of such integration we exemplify it by using a standalone ATM simulator, and analyzing the possible degradations of a system for managing unmanned aircraft (RPAS)

FRAM for systemic accident analysis: a matrix representation of functional resonance

Due to the inherent complexity of nowadays Air Traffic Management (ATM) system, standard methods looking at an event as a linear sequence of failures might become inappropriate. For this purpose, adopting a systemic perspective, the Functional Resonance Analysis Method (FRAM) originally developed by Hollnagel, helps identifying non-linear combinations of events and interrelationships. This paper aims to enhance the strength of FRAM-based accident analyses, discussing the Resilience Analysis Matrix (RAM), a user-friendly tool that supports the analyst during the analysis, in order to reduce the complexity of representation of FRAM. The RAM offers a two dimensional representation which highlights systematically connections among couplings, and thus even highly connected group of couplings. As an illustrative case study, this paper develops a systemic accident analysis for the runway incursion happened in February 1991 at LAX airport, involving SkyWest Flight 5569 and USAir Flight 1493. FRAM confirms itself a powerful method to characterize the variability of the operational scenario, identifying the dynamic couplings with a critical role during the event and helping discussing the systemic effects of variability at different level of analysis

A multi-modelS based approach for the modelling and the analysis of usable and resilient partly autonomous interactive systems

La croissance prévisionnelle du trafic aérien est telle que les moyens de gestion actuels doivent évoluer et être améliorés et l'automatisation de certains aspects de cette gestion semble être un moyen pour gérer cet accroissement du trafic tout en gardant comme invariant un niveau de sécurité constant. Toutefois, cette augmentation du trafic pourrait entraîner un accroissement de la variabilité de la performance de l'ensemble des moyens de gestion du trafic aérien, en particulier dans le cas de dégradation de cette automatisation. Les systèmes de gestion du trafic aérien sont considérés comme complexes car ils impliquent de nombreuses interactions entre humains et systèmes, et peuvent être profondément influencés par les aspects environnementaux (météorologie, organisation, stress ...) et tombent, de fait, dans la catégorie des Systèmes Sociotechniques (STS) (Emery & Trist, 1960). A cause de leur complexité, les interactions entre les différents éléments (humains, systèmes et organisations) de ces STS peuvent être linéaires et partiellement non linéaires, ce qui rend l'évolution de leur performance difficilement prévisible. Au sein de ces STS, les systèmes interactifs doivent être utilisables, i.e. permettre à leurs utilisateurs d'accomplir leurs tâches de manière efficace et efficiente. Un STS doit aussi être résilient aux perturbations telles que les défaillances logicielles et matérielles, les potentielles dégradations de l'automatisation ou les problèmes d'interaction entre les systèmes et leurs opérateurs. Ces problèmes peuvent affecter plusieurs aspects des systèmes sociotechniques comme les ressources, le temps d'exécution d'une tâche, la capacité à d'adaptation à l'environnement... Afin de pouvoir analyser l'impact de ces perturbations et d'évaluer la variabilité de la performance d'un STS, des techniques et méthodes dédiées sont requises. Elles doivent fournir un support à la modélisation et à l'analyse systématique de l'utilisabilité et de la résilience de systèmes interactifs aux comportements partiellement autonomes. Elles doivent aussi permettre de décrire et de structurer un grand nombre d'informations, ainsi que de traiter la variabilité de chaque élément du STS et la variabilité liée à leurs interrelations. Les techniques et méthodes existantes ne permettent actuellement ni de modéliser un STS dans son ensemble, ni d'en analyser les propriétés d'utilisabilité et de résilience (ou alors se focalisent sur un sous-ensemble du STS perdant, de fait, la vision systémique). Enfin, elles ne fournissent pas les moyens d'analyser la migration de tâches suite à l'introduction d'une nouvelle technologie ou d'analyser la variabilité de la performance en cas de dégradation de fonctions récemment automatisées. Ces arguments sont développés dans la thèse et appuyés par une analyse détaillée des techniques de modélisation existantes et des méthodes qui leurs sont associées. La contribution présentée est basée sur l'identification d'un ensemble d'exigences requises pour pouvoir modéliser et analyser chacun des éléments d'un STS. Certaines de ces exigences ont été remplies grâce à l'utilisation de techniques de modélisation existantes, les autres grâce à l'extension et au raffinement d'autres techniques. Cette thèse propose une approche qui intègre 3 techniques en particulier : FRAM (centrée sur les fonctions organisationnelles), HAMSTERS (centrée les objectifs et activités humaines) et ICO (dédiée à la modélisation du comportement des systèmes interactifs). Cette approche est illustrée par un exemple mettant en œuvre les extensions proposées et l'intégration des modèles. Une étude de cas plus complexe sur la gestion du trafic aérien (changement de route d'un avion en cas de mauvaises conditions météorologiques) est ensuite présentée pour montrer le passage à l'échelle de l'approche. Elle met en avant les bénéfices de l'intégration des modèles pour la prise en compte de la variabilité de la performance des différents éléments d'un STSThe current European Air Traffic Management (ATM) System needs to be improved for coping with the growth in air traffic forecasted for next years. It has been broadly recognised that the future ATM capacity and safety objectives can only be achieved by an intense enhancement of integrated automation support. However, increase of automation might come along with an increase of performance variability of the whole ATM System especially in case of automation degradation. ATM systems are considered complex as they encompass interactions involving humans and machines deeply influenced by environmental aspects (i.e. weather, organizational structure) making them belong to the class of Socio-Technical Systems (STS) (Emery & Trist, 1960). Due to this complexity, the interactions between the STS elements (human, system and organisational) can be partly linear and partly non-linear making its performance evolution complex and hardly predictable. Within such STS, interactive systems have to be usable i.e. enabling users to perform their tasks efficiently and effectively while ensuring a certain level of operator satisfaction. Besides, the STS has to be resilient to adverse events including potential automation degradation issues but also interaction problems between their interactive systems and the operators. These issues may affect several STS aspects such as resources, time in tasks performance, ability to adjust to environment, etc. In order to be able to analyse the impact of these perturbations and to assess the potential performance variability of a STS, dedicated techniques and methods are required. These techniques and methods have to provide support for modelling and analysing in a systematic way usability and resilience of interactive systems featuring partly autonomous behaviours. They also have to provide support for describing and structuring a large amount of information and to be able to address the variability of each of STS elements as well as the variability related to their interrelations. Current techniques, methods and processes do not enable to model a STS as a whole and to analyse both usability and resilience properties. Also, they do not embed all the elements that are required to describe and analyse each part of the STS (such as knowledge of different types which is needed by a user for accomplishing tasks or for interacting with dedicated technologies). Lastly, they do not provide means for analysing task migrations when a new technology is introduced or for analysing performance variability in case of degradation of the newly introduced automation. Such statements are argued in this thesis by a detailed analysis of existing modelling techniques and associated methods highlighting their advantages and limitations. This thesis proposes a multi-models based approach for the modelling and the analysis of partly-autonomous interactive systems for assessing their resilience and usability. The contribution is based on the identification of a set of requirements needed being able to model and analyse each of the STS elements. Some of these requirements were met by existing modelling techniques, others were reachable by extending and refining existing ones. This thesis proposes an approach which integrates 3 modelling techniques: FRAM (focused on organisational functions), HAMSTERS (centred on human goals and activities) and ICO (dedicated to the modelling of interactive systems). The principles of the multi-models approach is illustrated on an example for carefully showing the extensions proposed to the selected modelling techniques and how they integrate together. A more complex case study from the ATM World is then presented to demonstrate the scalability of the approach. This case study, dealing with aircraft route change due to bad weather conditions, highlights the ability of the integration of models to cope with performance variability of the various parts of the ST

Gamma distribution function to understand anaerobic digestion kinetics: Kinetic constants are not constant

The Gamma model is a novel approach to characterise the complex degradation dynamics taking place during anaerobic digestion. This three parameters model results from combining the first-order kinetic model and the Gamma distribution function. In contrast to conventional models, where the kinetic constant is considered invariant, the Gamma model allows analysing the variability of the kinetic constant using a probability density function. The kinetic constant of mono-digestion and co-digestion batch tests of different wastes were modelled using the Gamma model and two common first-order models: one-step one-fraction model and one-step two-fraction model. The Gamma distribution function approximates three distinct probability density functions, i.e. exponential, log-normal, and delta Dirac. Specifically, (i) cattle paunch and pig manure approximated a log-normal distribution; (ii) cattle manure and microalgae approximated an exponential distribution, and (iii) primary sludge and cellulose approximated a delta Dirac distribution. The Gamma model was able to characterise two distinct waste activated sludge, one approximated to a log-normal distribution and the other to an exponential distribution. The same cellulose was tested with two different inocula; in both tests, the Gamma distribution function approximated a delta Dirac function but with a different kinetic value. The potential and consistency of Gamma model were also evident when analysing pig manure and microalgae co-digestion batch tests since (i) the mean k of the co-digestion tests were within the values of the mono-digestion tests, and (ii) the profile of the density function transitioned from log-normal to exponential distribution as the percentage of microalgae in the mixture increased

Engage D5.6 Thematic challenge briefing notes (1st and 2nd releases)

Engage identified four thematic challenges to address research topics not contemporaneously (sufficiently) addressed by SESAR. This deliverable serves primarily as a record of the two sets of released thematic challenge briefing notes

Towards a Boolean network-based Computational Model for Cell Differentiation and its applications to Robotics

Living organisms are the ultimate product of a series of complex processes that take place within—and among—biological cells. Most of these processes, such as cell differentiation, are currently poorly understood. Cell differentiation is the process by which cells progressively specialise. Being a fundamental process within cells, its dysregulations have dramatic implications in biological organisms ranging from developmental issues to cancer formation. The thesis objective is to contribute to the progress in the understanding of cell differentiation and explore the applications of its properties for designing artificial systems. The proposed approach, which relies on Boolean networks based modelling and on the theory of dynamical systems, aims at investigating the general mechanisms underlying cell differentiation. The results obtained contribute to taking a further step towards the formulation of a general theoretical framework—so far missing—for cellular differentiation. We conducted an in-depth analysis of the impact of self-loops in random Boolean networks ensembles. We proposed a new model of differentiation driven by a simplified bio-inspired methylation mechanism in Boolean models of genetic regulatory networks. On the artificial side, by introducing the conceptual metaphor of the “attractor landscape” and related proofs of concept that support its potential, we paved the way for a new research direction in robotics called behavioural differentiation robotics: a branch of robotics dealing with the designing of robots capable of expressing different behaviours in a way similar to that of biological cells that undergo differentiation. The implications of the results achieved may have beneficial effects on medical research. Indeed, the proposed approach can foster new questions, experiments and in turn, models that hopefully in the next future will take us to cure differentiation-related diseases such as cancer. Our work may also contribute to address questions concerning the evolution of complex behaviours and to help design robust and adaptive robots

A framework for modeling the consequences of the propagation of automation degradation: application to air traffic control systems

International audienceThis paper presents a modelling approach for representing consequences of automation degradation in the context of a socio-technical network. This modelling approach involves two different notations. In previous work we have proposed a synergistic approach integrating these two views for describing the evolution of system performances under automation degradation. In the current paper we propose a more global approach encompassing the previous contribution and being specifically addressing the representation of consequences flowing from the occurrence of automation degradation. In this approach, four modelling levels of consequences are studied: direct consequences of automation propagation, consequences on the capacity to respond, consequences on resilience capacity and consequences on network performance. This stepwise refinement aims at acquiring and modelling additional information needed for being able to assess the consequences of automation degradation. The approach is exemplified on a case study in the domain of Air Traffic Management and more precisely Terminal Manoeuvre Area including an Arrival Manager (AMAN). Due to space constraints only the first level is fully presented