A causal model to analyze aircraft collision avoidance deadlock scenarios

[Abstract] Continuous increase in the traffic density over the certain en-route sectors provokes many situations in which a loss of separation minima (SM) between two aircraft occurs. Although, this loss is predicted well in advance, giving a proper look-ahead time (LAT) for a detection function, the resolution of such an event may lead to a new conflict situation due to dynamics of surrounding traffic aircraft. A multiagent system framework can deal with these cases. This work presents three different complexity indicators that can be used to shape the social behavior of the agents. Simulation results show that the proposed indicators can suggest drastically different nature of the same ecosystem, therefore further investigation of the correlation of the proposed indicators to the actual complexity is necessary.Ministerio de Economía y Competitividad; TIN2014-56919-C3-1-

Agent-based modeling and simulation for the design of the future european Air Traffic Management system: the experience of CASSIOPEIA

The SESAR (Single European Sky ATM Research) program is an ambitious re-search and development initiative to design the future European air traffic man-agement (ATM) system. The study of the behavior of ATM systems using agent-based modeling and simulation tools can help the development of new methods to improve their performance. This paper presents an overview of existing agent-based approaches in air transportation (paying special attention to the challenges that exist for the design of future ATM systems) and, subsequently, describes a new agent-based approach that we proposed in the CASSIOPEIA project, which was developed according to the goals of the SESAR program. In our approach, we use agent models for different ATM stakeholders, and, in contrast to previous work, our solution models new collaborative decision processes for flow traffic management, it uses an intermediate level of abstraction (useful for simulations at larger scales), and was designed to be a practical tool (open and reusable) for the development of different ATM studies. It was successfully applied in three stud-ies related to the design of future ATM systems in Europe

Complexity challenges in ATM

After more than 4 years of activity, the ComplexWorld Network, together with the projects and PhDs covered under the SESAR long-term research umbrella, have developed sound research material contributing to progress beyond the state of the art in fields such as resilience, uncertainty, multi-agent systems, metrics and data science. The achievements made by the ComplexWorld stakeholders have also led to the identification of new challenges that need to be addressed in the future. In order to pave the way for complexity science research in Air Traffic Management (ATM) in the coming years, ComplexWorld requested external assessments on how the challenges have been covered and where there are existing gaps. For that purpose, ComplexWorld, with the support of EUROCONTROL, established an expert panel to review selected documentation developed by the network and provide their assessment on their topic of expertise

Wind effect analysis on air traffic congestion in terminal area via cellular automata

The behavior of any traffic flow is sensitive to the speed pattern of the vehicles involved. The heavier the traffic, the more sensitive the behavior is to speed changes. Focusing on air traffic flow, weather condition has a major role in the deviations of aircraft operational speed from the desired speed and causes surplus delays. In this paper, the effects of wind on delays in a terminal area are analyzed using a Cellular Automaton (CA) model. Cellular automata are discrete models that are widely used for simulating complex emerging properties of dynamic systems. A one-dimensional cellular array is used to model the flow of the terminal traffic into a wind field. The proposed model, due to the quickness and acceptable level of accuracy, can be utilized online in the tactical phase of air traffic control processes and system-level decision-makings, where quick response and system behavior are needed. The modeled route is an RNAV STAR route to Atlanta International Airport. The model is verified by real traffic data in a non-delayed scenario. Based on simulation results, the proposed model exhibits an acceptable level of accuracy (3–15% accuracy drop), with worthy time and computational efficiency (about 2.9 seconds run time for a 2-hour operation)

Agent-based modeling and simulation of emergent behavior in air transportation

Purpose Commercial aviation is feasible thanks to the complex socio-technical air transportation system, which involves interactions between human operators, technical systems, and procedures. In view of the expected growth in commercial aviation, significant changes in this socio-technical system are in development both in the USA and Europe. Such a complex socio-technical system may generate various types of emergent behavior, which may range from simple emergence, through weak emergence, up to strong emergence. The purpose of this paper is to demonstrate that agent-based modeling and simulation allows identifying changed and novel rare emergent behavior in this complex socio-technical system. Methods An agent based model of a specific operation at an airport has been developed. The specific operation considered is the controlled crossing by a taxiing aircraft of a runway that is in use for controlled departures. The agent-based model includes all relevant human and technical agents, such as the aircraft, the pilots, the controllers and the decision support systems involved. This agent-based model is used to conduct rare event Monte Carlo (MC) simulations. Results The MC simulation results obtained confirm that agent based modeling and simulation of a socio-technical air transportation system allows to identify rare emergent behavior that was not identified through earlier, non-agent-based simulations, including human-in-the-loop simulations of the same operation. A typical example of such emergent behavior is the finding that alerting systems do not really reduce the safety risk. Conclusions Agent based MC simulations of commercial aviation operations has been demonstrated as a viable way to be evaluated regarding rare emergent behaviour. This rare emergent behaviour could not have been found through the more traditional simulation approaches.Control and OperationsAerospace Engineerin

Objective Validation of Airport Terminal Architecture using Agent-based Simulations

This thesis explores how airport terminal architecture is tested before it is built. The purpose of testing is to make sure an architectural layout aligns with the rest of the airport’s systems. The design of a terminal is a long and expensive process that must accommodate tens of thousands of passengers every hour, the movement of logistics, and control of security. Evaluating spaces for that many people can be difficult to measure, which can result in architects relying on their intuition and experience to judge the impact of a layout for daily operations without objective validation. It is not practical for designers to build a complete airport to see how it works and make renovations after finding aspects that have poor performance. As a result, testing airports requires using mathematical models and simulations to validate how well different systems work together. Designers try to validate architectural layouts in airport terminals by using crowd simulations to approximate passenger behaviour. Existing research in civil engineering and computer science has shown how mathematical models can predict patterns of human activity in the built environment on a large scale. However, these simulations have primarily focused on either modelling passengers as a process flow or people in emergency building evacuation. As a result, existing agent navigation does not consider how passengers use the surrounding architecture for decision-making during daily airport interactions. When passengers enter a terminal for the first time, they can be unaware of what they need to do or how to get there. Instead, passengers rely on using their perception of the environment (the architecture) to inform them what to do. However, there currently are no methods that incorporate architectural perception to validate a building layout in these conditions. This thesis develops an agent-based simulation to validate how well architectural layouts align with the daily operations of an airport terminal. It quantifies the value of a spatial arrangement as a function of people’s interactions in a given space. The model approximates human behaviour based on statistics from existing crowd simulations. It uses spatial analysis, like the isovist and graph theory, for agent navigation and measuring architectural conditions. The proposal incorporates agent perception to provide feedback between people’s decision-making and the influence of the surrounding space. The thesis calculates architectural value using normalized passenger priorities based on typical processing and non-processing airport domains. The success of a terminal layout is dependent on the agent’s ability to complete airport processing and fulfill their priorities. The final value of an architectural layout is determined using statistical methods to provide a probability distribution of likely values. The proposed agent simulation and mathematical models are built using Unity software, which is used to perform several simulation tests in this thesis. Basic functional components of the simulation are validated using existing crowd modelling standards. Tests are also performed to illustrate how different agent perception and priorities influence the value of architectural spaces. Monte Carlo simulations are created for simple terminal layouts to illustrate how changing the floor plan of a security area affects the architectural value for departing passengers. Finally, the architectural values of two real airport terminals are compared against an established passenger experience survey in a basic simulation model. The results of the testing shows that the agent simulation can differentiate between different architectural conditions, within reason, depending on the passengers’ priorities

Understanding the Use of HIT Catchers and Crowd Knowledge Sharing: A Case Study of Crowdworkers on Amazon Mechanical Turk

Crowdsourcing platforms have become a vital component of the modern digital economy, offering a wide range of HIT (Human Intelligence Task) opportunities to workers worldwide. Meanwhile, crowdworkers' use of scripting tools and their communication with each other are continuously shaping the entire crowdsourcing ecosystem. This thesis explores the use of HIT catchers by crowdworkers and their sharing of skill-based knowledge that facilitates the popularity of such scripting tools. It is revealed that the use of HIT catchers affects the completion speed and HIT-worker diversity for the whole HIT group, while depriving job opportunities from others. This potentially undermines the stability of the platform under the current reputation system relying on numbers of approvals and approval rates. Subsequently, another study explored how work strategies under the use of HIT catchers, including HIT acceptance, backlog, and completion, affect HIT availability, completion time, and result quality. The study also found differences in work behaviours between workers using and not using HIT catchers. Finally, this thesis investigates the skill-based knowledge sharing behaviour of crowdworkers, which promotes the blooming of scripting tools including HIT catchers, to improve the fairness of work opportunities and mitigate its negative impact on HIT completion. Using PLS-SEM, we assess the factors influencing knowledge sharing in the domain of skills. The study reveals the significance of high performance expectation, low effort expectation, and the joy and satisfaction in motivating the crowd skill-based knowledge sharing. Overall, this study provides an in-depth exploration around these two types of collective behaviour, highlighting the important role of tool use and knowledge sharing in shaping the crowdsourcing ecosystem

Manipulador aéreo con brazos antropomórficos de articulaciones flexibles

[Resumen] Este artículo presenta el primer robot manipulador aéreo con dos brazos antropomórficos diseñado para aplicarse en tareas de inspección y mantenimiento en entornos industriales de difícil acceso para operarios humanos. El robot consiste en una plataforma aérea multirrotor equipada con dos brazos antropomórficos ultraligeros, así como el sistema de control integrado de la plataforma y los brazos. Una de las principales características del manipulador es la flexibilidad mecánica proporcionada en todas las articulaciones, lo que aumenta la seguridad en las interacciones físicas con el entorno y la protección del propio robot. Para ello se ha introducido un compacto y simple mecanismo de transmisión por muelle entre el eje del servo y el enlace de salida. La estructura en aluminio de los brazos ha sido cuidadosamente diseñada de forma que los actuadores estén aislados frente a cargas radiales y axiales que los puedan dañar. El manipulador desarrollado ha sido validado a través de experimentos en base fija y en pruebas de vuelo en exteriores.Ministerio de Economía y Competitividad; DPI2014-5983-C2-1-