18 resultados para System Management
em Universidad Politécnica de Madrid
Resumo:
Transport climate change impacts have become a worldwide concern. The use of Intelligent Transport Systems (ITS) could contribute to a more effective use of resources in toll road networks. Management of toll plazas is central to the reduction of greenhouse gas (GHG) emissions, as it is there that bottlenecks and congestion occur. This study focuses on management strategies aimed at reducing climate change impacts of toll plazas by managing toll collection systems. These strategies are based on the use of different collection system technologies – Electronic Toll Collection (ETC) and Open Road Tolling (ORT) – and on queue management. The carbon footprint of various toll plazas is determined by a proposed integrated methodology which estimates the carbon dioxide (CO2) emissions of the different operational stages at toll plazas (deceleration, service time, acceleration, and queuing) for the different toll collection systems. To validate the methodology, two main-line toll plazas of a Spanish toll highway were evaluated. The findings reveal that the application of new technologies to toll collection systems is an effective management strategy from an environmental point of view. The case studies revealed that ORT systems lead to savings of up to 70% of CO2 emissions at toll plazas, while ETC systems save 20% comparing to the manual ones. Furthermore, queue management can offer a 16% emissions savings when queue time is reduced by 116 seconds. The integrated methodology provides an efficient environmental management tool for toll plazas. The use of new technologies is the future of the decarbonization of toll plazas.
Resumo:
Esta Tesis realiza una contribución metodológica al estudio del impacto del cambio climático sobre los usos del agua, centrándose particularmente en la agricultura. Tomando en consideración su naturaleza distinta, la metodología aborda de forma integral los impactos sobre la agricultura de secano y la agricultura de regadío. Para ello incorpora diferentes modelos agrícolas y de agua que conjuntamente con las simulaciones de los escenarios climáticos permiten determinar indicadores de impacto basados en la productividad de los cultivos, para el caso de la agricultura de secano, e indicadores de impacto basados en la disponibilidad de agua para irrigación, para el caso de la agricultura de regadío. La metodología toma en consideración el efecto de la variabilidad climática en la agricultura, evaluando las necesidades de adaptación y gestión asociadas a los impactos medios y a la variabilidad en la productividad de los cultivos y el efecto de la variabilidad hidrológica en la disponibilidad de agua para regadío. Considerando la gran cantidad de información proporcionada por las salidas de las simulaciones de los escenarios climáticos y su complejidad para procesarla, se ha desarrollado una herramienta de cálculo automatizada que integra diferentes escenarios climáticos, métodos y modelos que permiten abordar el impacto del cambio climático sobre la agricultura, a escala de grandes extensiones. El procedimiento metodológico parte del análisis de los escenarios climáticos en situación actual (1961-1990) y futura (2071-2100) para determinar su fiabilidad y conocer qué dicen exactamente las proyecciones climáticas a cerca de los impactos esperados en las principales variables que intervienen en el ciclo hidrológico. El análisis hidrológico se desarrolla en los ámbitos territoriales de la planificación hidrológica en España, considerando la disponibilidad de información para validar los resultados en escenario de control. Se utilizan como datos observados las series de escorrentía en régimen natural estimadas el modelo hidrológico SIMPA que está calibrado en la totalidad del territorio español. Al trabajar a escala de grandes extensiones, la limitada disponibilidad de datos o la falta de modelos hidrológicos correctamente calibrados para obtener los valores de escorrentía, muchas veces dificulta el proceso de evaluación, por tanto, en este estudio se plantea una metodología que compara diferentes métodos de interpolación y alternativas para generar series anuales de escorrentía que minimicen el sesgo con respecto a los valores observados. Así, en base a la alternativa que genera los mejores resultados, se obtienen series mensuales corregidas a partir de las simulaciones de los modelos climáticos regionales (MCR). Se comparan cuatro métodos de interpolación para obtener los valores de las variables a escala de cuenca hidrográfica, haciendo énfasis en la capacidad de cada método para reproducir los valores observados. Las alternativas utilizadas consideran la utilización de la escorrentía directa simulada por los MCR y la escorrentía media anual calculada utilizando cinco fórmulas climatológicas basadas en el índice de aridez. Los resultados se comparan además con la escorrentía global de referencia proporcionada por la UNH/GRDC que en la actualidad es el “mejor estimador” de la escorrentía actual a gran escala. El impacto del cambio climático en la agricultura de secano se evalúa considerando el efecto combinado de los riesgos asociados a las anomalías dadas por los cambios en la media y la variabilidad de la productividad de los cultivos en las regiones agroclimáticas de Europa. Este procedimiento facilita la determinación de las necesidades de adaptación y la identificación de los impactos regionales que deben ser abordados con mayor urgencia en función de los riesgos y oportunidades identificadas. Para ello se utilizan funciones regionales de productividad que han sido desarrolladas y calibradas en estudios previos en el ámbito europeo. Para el caso de la agricultura de regadío, se utiliza la disponibilidad de agua para irrigación como un indicador del impacto bajo escenarios de cambio climático. Considerando que la mayoría de estudios se han centrado en evaluar la disponibilidad de agua en régimen natural, en este trabajo se incorpora el efecto de las infraestructuras hidráulicas al momento de calcular el recurso disponible bajo escenarios de cambio climático Este análisis se desarrolla en el ámbito español considerando la disponibilidad de información, tanto de las aportaciones como de los modelos de explotación de los sistemas hidráulicos. Para ello se utiliza el modelo de gestión de recursos hídricos WAAPA (Water Availability and Adaptation Policy Assessment) que permite calcular la máxima demanda que puede atenderse bajo determinados criterios de garantía. Se utiliza las series mensuales de escorrentía observadas y las series mensuales de escorrentía corregidas por la metodología previamente planteada con el objeto de evaluar la disponibilidad de agua en escenario de control. Se construyen proyecciones climáticas utilizando los cambios en los valores medios y la variabilidad de las aportaciones simuladas por los MCR y también utilizando una fórmula climatológica basada en el índice de aridez. Se evalúan las necesidades de gestión en términos de la satisfacción de las demandas de agua para irrigación a través de la comparación entre la disponibilidad de agua en situación actual y la disponibilidad de agua bajo escenarios de cambio climático. Finalmente, mediante el desarrollo de una herramienta de cálculo que facilita el manejo y automatización de una gran cantidad de información compleja obtenida de las simulaciones de los MCR se obtiene un proceso metodológico que evalúa de forma integral el impacto del cambio climático sobre la agricultura a escala de grandes extensiones, y a la vez permite determinar las necesidades de adaptación y gestión en función de las prioridades identificadas. ABSTRACT This thesis presents a methodological contribution for studying the impact of climate change on water use, focusing particularly on agriculture. Taking into account the different nature of the agriculture, this methodology addresses the impacts on rainfed and irrigated agriculture, integrating agricultural and water planning models with climate change simulations scenarios in order to determine impact indicators based on crop productivity and water availability for irrigation, respectively. The methodology incorporates the effect of climate variability on agriculture, assessing adaptation and management needs associated with mean impacts, variability in crop productivity and the effect of hydrologic variability on water availability for irrigation. Considering the vast amount of information provided by the outputs of the regional climate model (RCM) simulations and also its complexity for processing it, a tool has been developed to integrate different climate scenarios, methods and models to address the impact of climate change on agriculture at large scale. Firstly, a hydrological analysis of the climate change scenarios is performed under current (1961-1990) and future (2071-2100) situation in order to know exactly what the models projections say about the expected impact on the main variables involved in the hydrological cycle. Due to the availability of information for validating the results in current situation, the hydrological analysis is developed in the territorial areas of water planning in Spain, where the values of naturalized runoff have been estimated by the hydrological model SIMPA, which are used as observed data. By working in large-scale studies, the limited availability of data or lack of properly calibrated hydrological model makes difficult to obtain runoff time series. So as, a methodology is proposed to compare different interpolation methods and alternatives to generate annual times series that minimize the bias with respect to observed values. Thus, the best alternative is selected in order to obtain bias-corrected monthly time series from the RCM simulations. Four interpolation methods for downscaling runoff to the basin scale from different RCM are compared with emphasis on the ability of each method to reproduce the observed behavior of this variable. The alternatives consider the use of the direct runoff of the RCMs and the mean annual runoff calculated using five functional forms of the aridity index. The results are also compared with the global runoff reference provided by the UNH/GRDC dataset, as a contrast of the “best estimator” of current runoff on a large scale. Secondly, the impact of climate change on rainfed agriculture is assessed considering the combined effect of the risks associated with anomalies given by changes in the mean and variability of crop productivity in the agro-climatic regions of Europe. This procedure allows determining adaptation needs based on the regional impacts that must be addressed with greater urgency in light of the risks and opportunities identified. Statistical models of productivity response are used for this purpose which have been developed and calibrated in previous European study. Thirdly, the impact of climate change on irrigated agriculture is evaluated considering the water availability for irrigation as an indicator of the impact. Given that most studies have focused on assessing water availability in natural regime, the effect of regulation is incorporated in this approach. The analysis is developed in the Spanish territory considering the available information of the observed stream flows and the regulation system. The Water Availability and Adaptation Policy Assessment (WAAPA) model is used in this study, which allows obtaining the maximum demand that could be supplied under certain conditions (demand seasonal distribution, water supply system management, and reliability criteria) for different policy alternatives. The monthly bias corrected time series obtained by previous methodology are used in order to assess water availability in current situation. Climate change projections are constructed taking into account the variation in mean and coefficient of variation simulated by the RCM. The management needs are determined by the agricultural demands satisfaction through the comparison between water availability under current conditions and under climate change projections. Therefore, the methodology allows evaluating the impact of climate change on agriculture to large scale, using a tool that facilitates the process of a large amount of complex information provided by the RCM simulations, in order to determine the adaptation and management needs in accordance with the priorities of the indentified impacts.
Resumo:
La computación ubicua está extendiendo su aplicación desde entornos específicos hacia el uso cotidiano; el Internet de las cosas (IoT, en inglés) es el ejemplo más brillante de su aplicación y de la complejidad intrínseca que tiene, en comparación con el clásico desarrollo de aplicaciones. La principal característica que diferencia la computación ubicua de los otros tipos está en como se emplea la información de contexto. Las aplicaciones clásicas no usan en absoluto la información de contexto o usan sólo una pequeña parte de ella, integrándola de una forma ad hoc con una implementación específica para la aplicación. La motivación de este tratamiento particular se tiene que buscar en la dificultad de compartir el contexto con otras aplicaciones. En realidad lo que es información de contexto depende del tipo de aplicación: por poner un ejemplo, para un editor de imágenes, la imagen es la información y sus metadatos, tales como la hora de grabación o los ajustes de la cámara, son el contexto, mientras que para el sistema de ficheros la imagen junto con los ajustes de cámara son la información, y el contexto es representado por los metadatos externos al fichero como la fecha de modificación o la de último acceso. Esto significa que es difícil compartir la información de contexto, y la presencia de un middleware de comunicación que soporte el contexto de forma explícita simplifica el desarrollo de aplicaciones para computación ubicua. Al mismo tiempo el uso del contexto no tiene que ser obligatorio, porque si no se perdería la compatibilidad con las aplicaciones que no lo usan, convirtiendo así dicho middleware en un middleware de contexto. SilboPS, que es nuestra implementación de un sistema publicador/subscriptor basado en contenido e inspirado en SIENA [11, 9], resuelve dicho problema extendiendo el paradigma con dos elementos: el Contexto y la Función de Contexto. El contexto representa la información contextual propiamente dicha del mensaje por enviar o aquella requerida por el subscriptor para recibir notificaciones, mientras la función de contexto se evalúa usando el contexto del publicador y del subscriptor. Esto permite desacoplar la lógica de gestión del contexto de aquella de la función de contexto, incrementando de esta forma la flexibilidad de la comunicación entre varias aplicaciones. De hecho, al utilizar por defecto un contexto vacío, las aplicaciones clásicas y las que manejan el contexto pueden usar el mismo SilboPS, resolviendo de esta forma la incompatibilidad entre las dos categorías. En cualquier caso la posible incompatibilidad semántica sigue existiendo ya que depende de la interpretación que cada aplicación hace de los datos y no puede ser solucionada por una tercera parte agnóstica. El entorno IoT conlleva retos no sólo de contexto, sino también de escalabilidad. La cantidad de sensores, el volumen de datos que producen y la cantidad de aplicaciones que podrían estar interesadas en manipular esos datos está en continuo aumento. Hoy en día la respuesta a esa necesidad es la computación en la nube, pero requiere que las aplicaciones sean no sólo capaces de escalar, sino de hacerlo de forma elástica [22]. Desgraciadamente no hay ninguna primitiva de sistema distribuido de slicing que soporte un particionamiento del estado interno [33] junto con un cambio en caliente, además de que los sistemas cloud actuales como OpenStack u OpenNebula no ofrecen directamente una monitorización elástica. Esto implica que hay un problema bilateral: cómo puede una aplicación escalar de forma elástica y cómo monitorizar esa aplicación para saber cuándo escalarla horizontalmente. E-SilboPS es la versión elástica de SilboPS y se adapta perfectamente como solución para el problema de monitorización, gracias al paradigma publicador/subscriptor basado en contenido y, a diferencia de otras soluciones [5], permite escalar eficientemente, para cumplir con la carga de trabajo sin sobre-provisionar o sub-provisionar recursos. Además está basado en un algoritmo recientemente diseñado que muestra como añadir elasticidad a una aplicación con distintas restricciones sobre el estado: sin estado, estado aislado con coordinación externa y estado compartido con coordinación general. Su evaluación enseña como se pueden conseguir notables speedups, siendo el nivel de red el principal factor limitante: de hecho la eficiencia calculada (ver Figura 5.8) demuestra cómo se comporta cada configuración en comparación con las adyacentes. Esto permite conocer la tendencia actual de todo el sistema, para saber si la siguiente configuración compensará el coste que tiene con la ganancia que lleva en el throughput de notificaciones. Se tiene que prestar especial atención en la evaluación de los despliegues con igual coste, para ver cuál es la mejor solución en relación a una carga de trabajo dada. Como último análisis se ha estimado el overhead introducido por las distintas configuraciones a fin de identificar el principal factor limitante del throughput. Esto ayuda a determinar la parte secuencial y el overhead de base [26] en un despliegue óptimo en comparación con uno subóptimo. Efectivamente, según el tipo de carga de trabajo, la estimación puede ser tan baja como el 10 % para un óptimo local o tan alta como el 60 %: esto ocurre cuando se despliega una configuración sobredimensionada para la carga de trabajo. Esta estimación de la métrica de Karp-Flatt es importante para el sistema de gestión porque le permite conocer en que dirección (ampliar o reducir) es necesario cambiar el despliegue para mejorar sus prestaciones, en lugar que usar simplemente una política de ampliación. ABSTRACT The application of pervasive computing is extending from field-specific to everyday use. The Internet of Things (IoT) is the shiniest example of its application and of its intrinsic complexity compared with classical application development. The main characteristic that differentiates pervasive from other forms of computing lies in the use of contextual information. Some classical applications do not use any contextual information whatsoever. Others, on the other hand, use only part of the contextual information, which is integrated in an ad hoc fashion using an application-specific implementation. This information is handled in a one-off manner because of the difficulty of sharing context across applications. As a matter of fact, the application type determines what the contextual information is. For instance, for an imaging editor, the image is the information and its meta-data, like the time of the shot or camera settings, are the context, whereas, for a file-system application, the image, including its camera settings, is the information and the meta-data external to the file, like the modification date or the last accessed timestamps, constitute the context. This means that contextual information is hard to share. A communication middleware that supports context decidedly eases application development in pervasive computing. However, the use of context should not be mandatory; otherwise, the communication middleware would be reduced to a context middleware and no longer be compatible with non-context-aware applications. SilboPS, our implementation of content-based publish/subscribe inspired by SIENA [11, 9], solves this problem by adding two new elements to the paradigm: the context and the context function. Context represents the actual contextual information specific to the message to be sent or that needs to be notified to the subscriber, whereas the context function is evaluated using the publisher’s context and the subscriber’s context to decide whether the current message and context are useful for the subscriber. In this manner, context logic management is decoupled from context management, increasing the flexibility of communication and usage across different applications. Since the default context is empty, context-aware and classical applications can use the same SilboPS, resolving the syntactic mismatch that there is between the two categories. In any case, the possible semantic mismatch is still present because it depends on how each application interprets the data, and it cannot be resolved by an agnostic third party. The IoT environment introduces not only context but scaling challenges too. The number of sensors, the volume of the data that they produce and the number of applications that could be interested in harvesting such data are growing all the time. Today’s response to the above need is cloud computing. However, cloud computing applications need to be able to scale elastically [22]. Unfortunately there is no slicing, as distributed system primitives that support internal state partitioning [33] and hot swapping and current cloud systems like OpenStack or OpenNebula do not provide elastic monitoring out of the box. This means there is a two-sided problem: 1) how to scale an application elastically and 2) how to monitor the application and know when it should scale in or out. E-SilboPS is the elastic version of SilboPS. I t is the solution for the monitoring problem thanks to its content-based publish/subscribe nature and, unlike other solutions [5], it scales efficiently so as to meet workload demand without overprovisioning or underprovisioning. Additionally, it is based on a newly designed algorithm that shows how to add elasticity in an application with different state constraints: stateless, isolated stateful with external coordination and shared stateful with general coordination. Its evaluation shows that it is able to achieve remarkable speedups where the network layer is the main limiting factor: the calculated efficiency (see Figure 5.8) shows how each configuration performs with respect to adjacent configurations. This provides insight into the actual trending of the whole system in order to predict if the next configuration would offset its cost against the resulting gain in notification throughput. Particular attention has been paid to the evaluation of same-cost deployments in order to find out which one is the best for the given workload demand. Finally, the overhead introduced by the different configurations has been estimated to identify the primary limiting factor for throughput. This helps to determine the intrinsic sequential part and base overhead [26] of an optimal versus a suboptimal deployment. Depending on the type of workload, this can be as low as 10% in a local optimum or as high as 60% when an overprovisioned configuration is deployed for a given workload demand. This Karp-Flatt metric estimation is important for system management because it indicates the direction (scale in or out) in which the deployment has to be changed in order to improve its performance instead of simply using a scale-out policy.
Resumo:
This paper describes the design and development of a system for cardio rehabilitation of patients that suffered a myocardial infarction. The proposed solution focuses on exercise prescriptions and the encouragement of healthy behaviors. The innovative strategy of the design takes into account health promotion models to provide safe, assistive exercise training sessions, personalized feedbacks, and educational contents.
Resumo:
A useful strategy for improving disaster risk management is sharing spatial data across different technical organizations using shared information systems. However, the implementation of this type of system requires a large effort, so it is difficult to find fully implemented and sustainable information systems that facilitate sharing multinational spatial data about disasters, especially in developing countries. In this paper, we describe a pioneer system for sharing spatial information that we developed for the Andean Community. This system, called SIAPAD (Andean Information System for Disaster Prevention and Relief), integrates spatial information from 37 technical organizations in the Andean countries (Bolivia, Colombia, Ecuador, and Peru). SIAPAD was based on the concept of a thematic Spatial Data Infrastructure (SDI) and includes a web application, called GEORiesgo, which helps users to find relevant information with a knowledge-based system. In the paper, we describe the design and implementation of SIAPAD together with general conclusions and future directions which we learned as a result of this work.
Resumo:
European public administrations must manage citizens' digital identities, particularly considering interoperability among different countries. Owing to the diversity of electronic identity management (eIDM) systems, when users of one such system seek to communicate with governments using a different system, both systems must be linked and understand each other. To achieve this, the European Union is working on an interoperability framework. This article provides an overview of eIDM systems' current state at a pan-European level. It identifies and analyzes issues on which agreement exists, as well as those that aren't yet resolved and are preventing the adoption of a large-scale model.
Resumo:
This paper describes an automatic-dependent surveillance-broadcast (ADS-B) implementation for air-to-air and ground-based experimental surveillance within a prototype of a fully automated air traffic management (ATM) system, under a trajectory-based-operations paradigm. The system is built using an air-inclusive implementation of system wide information management (SWIM). This work describes the relations between airborne and ground surveillance (SURGND), the prototype surveillance systems, and their algorithms. System's performance is analyzed with simulated and real data. Results show that the proposed ADS-B implementation can fulfill the most demanding surveillance accuracy requirements.
Resumo:
As it is defined in ATM 2000+ Strategy (Eurocontrol 2001), the mission of the Air Traffic Management (ATM) System is: “For all the phases of a flight, the ATM system should facilitate a safe, efficient, and expedite traffic flow, through the provision of adaptable ATM services that can be dimensioned in relation to the requirements of all the users and areas of the European air space. The ATM services should comply with the demand, be compatible, operate under uniform principles, respect the environment and satisfy the national security requirements.” The objective of this paper is to present a methodology designed to evaluate the status of the ATM system in terms of the relationship between the offered capacity and traffic demand, identifying weakness areas and proposing solutions. The first part of the methodology relates to the characterization and evaluation of the current system, while a second part proposes an approach to analyze the possible development limit. As part of the work, general criteria are established to define the framework in which the analysis and diagnostic methodology presented is placed. They are: the use of Air Traffic Control (ATC) sectors as analysis unit, the presence of network effects, the tactical focus, the relative character of the analysis, objectivity and a high level assessment that allows assumptions on the human and Communications, Navigation and Surveillance (CNS) elements, considered as the typical high density air traffic resources. The steps followed by the methodology start with the definition of indicators and metrics, like the nominal criticality or the nominal efficiency of a sector; scenario characterization where the necessary data is collected; network effects analysis to study the relations among the constitutive elements of the ATC system; diagnostic by means of the “System Status Diagram”; analytical study of the ATC system development limit; and finally, formulation of conclusions and proposal for improvement. This methodology was employed by Aena (Spanish Airports Manager and Air Navigation Service Provider) and INECO (Spanish Transport Engineering Company) in the analysis of the Spanish ATM System in the frame of the Spanish airspace capacity sustainability program, although it could be applied elsewhere.
Resumo:
Energy Efficiency is one of the goals of the Smart Building initiatives. This paper presents an Open Energy Management System which consists of an ontology-based multi-technology platform and a wireless transducer network using 6LoWPAN communication technology. The system allows the integration of several building automation protocols and eases the development of different kind of services to make use of them. The system has been implemented and tested in the Energy Efficiency Research Facility at CeDInt-UPM.
Resumo:
First, this paper describes a future layered Air Traffic Management (ATM) system centred in the execution phase of flights. The layered ATM model is based on the work currently performed by SESAR [1] and takes into account the availability of accurate and updated flight information ?seen by all? across the European airspace. This shared information of each flight will be referred as Reference Business Trajectory (RBT). In the layered ATM system, exchanges of information will involve several actors (human or automatic), which will have varying time horizons, areas of responsibility and tasks. Second, the paper will identify the need to define the negotiation processes required to agree revisions to the RBT in the layered ATM system. Third, the final objective of the paper is to bring to the attention of researchers and engineers the communalities between multi-player games and Collaborative Decision Making processes (CDM) in a layered ATM system
Resumo:
Cloud computing and, more particularly, private IaaS, is seen as a mature technology with a myriad solutions tochoose from. However, this disparity of solutions and products has instilled in potential adopters the fear of vendor and data lock-in. Several competing and incompatible interfaces and management styles have given even more voice to these fears. On top of this, cloud users might want to work with several solutions at the same time, an integration that is difficult to achieve in practice. In this paper, we propose a management architecture that tries to tackle these problems; it offers a common way of managing several cloud solutions, and an interface that can be tailored to the needs of the user. This management architecture is designed in a modular way, and using a generic information model. We have validated our approach through the implementation of the components needed for this architecture to support a sample private IaaS solution: OpenStack
Resumo:
This work introduces a web-based learning environment to facilitate learning in Project Management. The proposed web-based support system integrates methodological procedures and information systems, allowing to promote learning among geographically-dispersed students. Thus, students who are enrolled in different universities at different locations and attend their own project management courses, share a virtual experience in executing and managing projects. Specific support systems were used or developed to automatically collect information about student activities, making it possible to monitor the progress made on learning and assess learning performance as established in the defined rubric.
Resumo:
Cloud computing and, more particularly, private IaaS, is seen as a mature technol- ogy with a myriad solutions to choose from. However, this disparity of solutions and products has instilled in potential adopters the fear of vendor and data lock- in. Several competing and incompatible interfaces and management styles have increased even more these fears. On top of this, cloud users might want to work with several solutions at the same time, an integration that is difficult to achieve in practice. In this Master Thesis I propose a management architecture that tries to solve these problems; it provides a generalized control mechanism for several cloud infrastructures, and an interface that can meet the requirements of the users. This management architecture is designed in a modular way, and using a generic infor- mation model. I have validated the approach through the implementation of the components needed for this architecture to support a sample private IaaS solution: OpenStack.
Resumo:
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.
Resumo:
This paper describes an agent-based approach for the simulation of air traffic management (ATM) in Europe that was designed to help analyze proposals for future ATM systems. This approach is able to represent new collaborative deci-sion processes for flow traffic management, it uses an intermediate level of ab-straction (useful for simulations at larger scales), and was designed to be a practi-cal tool (open and reusable) for the development of different ATM studies. It was successfully applied in three studies related to the design of future ATM systems in Europe.