Aplicacions Intel·ligents d'ajuda als pilots

Aconseguir una aeronau més segura amb un únic pilot a la cabina és tot un repte en què estan treballant els principals fabricants d'aeronaus. Investigadors del Departament de Telecomunicació i Enginyeria de Sistemes de la UAB estan coordinant el projecte Europeu E-PILOTS, per aconseguir noves aplicacions intel·ligents que permetin reduir la càrrega de treball del pilot per sota d'un cert llindar.Conseguir una aeronave más segura con un único piloto en la cabina es todo un reto en el que están trabajando los principales fabricantes de aeronaves. Investigadores del Departamento de Telecomunicación e Ingeniería de Sistemas de la UAB están coordinando el proyecto Europeo E-PILOTS, para lograr nuevas aplicaciones inteligentes que permitan reducir la carga de trabajo del piloto por debajo de un cierto umbral

Multi-UAV Conflict Resolution with Graph Convolutional Reinforcement Learning

Safety is the primary concern when it comes to air traffic. In-flight safety between Unmanned Aircraft Vehicles (UAVs) is ensured through pairwise separation minima, utilizing conflict detection and resolution methods. Existing methods mainly deal with pairwise conflicts, however, due to an expected increase in traffic density, encounters with more than two UAVs are likely to happen. In this paper, we model multi-UAV conflict resolution as a multiagent reinforcement learning problem. We implement an algorithm based on graph neural networks where cooperative agents can communicate to jointly generate resolution maneuvers. The model is evaluated in scenarios with 3 and 4 present agents. Results show that agents are able to successfully solve the multi-UAV conflicts through a cooperative strategy

Simulation-Based Evolutionary Optimization of Air Traffic Management

In the context of aerospace engineering, the optimization of processes may often require to solve multi-objective optimization problems, including mixed variables, multi-modal and non-differentiable quantities, possibly involving highly-expensive objective function evaluations. In Air Traffic Management (ATM), the optimization of procedures and protocols becomes even more complicated, due to the involve-ment of human controllers, which act as final decision points in the control chain. In this article, we propose the use of computational intelligence techniques, such as Agent-Based Modelling and Simulation (ABMS)and Evolutionary Computing (EC), to design a simulation-based distributed architecture to optimize control plans and procedures in the context of ATM. We rely on Agent-Based fast-time simulations to carry out offline what-if analysis of multiple scenarios, also taking into account human-related decisions, during the strategic or pre-tactical phases. The scenarios are constructed using real-world traffic data traces, while multiple optimization variables governed by an EC algorithm allow to explore the search space to identify the best solutions. Our optimization approach relies on ad-hoc multi-objective performance metrics which allow to assess the goodness of the control of aircraft and air traffic regulations. We present experimental results which prove the viability of our approach, comparing them with real-world data traces, and proving their meaningfulness from an Air Traffic Control perspective

Aplicacions Intel·ligents d'ajuda als pilots

Aconseguir una aeronau més segura amb un únic pilot a la cabina és tot un repte en què estan treballant els principals fabricants d'aeronaus. Investigadors del Departament de Telecomunicació i Enginyeria de Sistemes de la UAB estan coordinant el projecte Europeu E-PILOTS, per aconseguir noves aplicacions intel·ligents que permetin reduir la càrrega de treball del pilot per sota d'un cert llindar.Conseguir una aeronave más segura con un único piloto en la cabina es todo un reto en el que están trabajando los principales fabricantes de aeronaves. Investigadores del Departamento de Telecomunicación e Ingeniería de Sistemas de la UAB están coordinando el proyecto Europeo E-PILOTS, para lograr nuevas aplicaciones inteligentes que permitan reducir la carga de trabajo del piloto por debajo de un cierto umbral

Multi-UAV Conflict Resolution with Graph Convolutional Reinforcement Learning

Safety is the primary concern when it comes to air traffic. In-flight safety between Unmanned Aircraft Vehicles (UAVs) is ensured through pairwise separation minima, utilizing conflict detection and resolution methods. Existing methods mainly deal with pairwise conflicts, however, due to an expected increase in traffic density, encounters with more than two UAVs are likely to happen. In this paper, we model multi-UAV conflict resolution as a multiagent reinforcement learning problem. We implement an algorithm based on graph neural networks where cooperative agents can communicate to jointly generate resolution maneuvers. The model is evaluated in scenarios with 3 and 4 present agents. Results show that agents are able to successfully solve the multi-UAV conflicts through a cooperative strategy

Spatiotemporal graph indicators for air traffic complexity analysis

There has been extensive research in formalising air traffic complexity, but existing works focus mainly on a metric to tie down the peak air traffic controllers workload rather than a dynamic approach to complexity that could guide both strategical, pre-tactical and tactical actions for a smooth flow of aircraft. In this paper, aircraft interdependencies are formalized using graph theory and four complexity indicators are described, which combine spatiotemporal topological information with the severity of the interdependencies. These indicators can be used to predict the dynamic evolution of complexity, by not giving one single score, but measuring complexity in a time window. Results show that these indicators can capture complex spatiotemporal areas in a sector and give a detailed and nuanced view of sector complexity

Sistema de transports intel·ligents : diferències de difusió a Europa i els EUA

La mobilitat compartida, la mobilitat com a servei i el vehicle autònom s'han proposat com dues solucions adients que contribuiran al gaudi de ciutats més eficients i amb una millor qualitat de vida per als seus habitants. Investigadors de la UAB estudien en el projecte europeu Newbits, han comparat Europa i els Estats Units (EUA) per conèixer els factors crítics en la seva difusió entre la població. Reticències a l'ús de tecnologies de seguiment o el suport d'autoritats locals en mobilitat compartida i la ciberseguretat i l'ètica en el vehicle autònom en són alguns dels que han detectat.La movilidad compartida, la movilidad como servicio y el vehículo autónomo se han propuesto como dos soluciones adecuadas que contribuirán al disfrute de ciudades más eficientes y con una mejor calidad de vida para sus habitantes. Investigadores de la UAB estudian en el proyecto europeo Newbits, han comparado Europa y los Estados Unidos (EE.UU.) para conocer los factores críticos en su difusión entre la población. Algunos de los factores que han detectado son reticencias al uso de tecnologías de seguimiento, el apoyo de autoridades locales en movilidad compartida y la ciberseguridad y la ética en el vehículo autónomo.Sharing mobility, mobility as a service and autonomous vehicles have been proposed as two suitable solutions that will contribute to the enjoyment of more efficient cities and with a better living quality for its inhabitants. Researchers of the UAB participating in the European project Newbits have compared Europe and the United States (US) to discover the critical factors in its diffusion among the population. Reluctance to the use of tracking technologies and the support of local authorities in sharing mobility and cybersecurity, as well as ethics in the autonomous vehicle are some factors that have been detected

Sistema de transports intel·ligents : diferències de difusió a Europa i els EUA

La mobilitat compartida, la mobilitat com a servei i el vehicle autònom s'han proposat com dues solucions adients que contribuiran al gaudi de ciutats més eficients i amb una millor qualitat de vida per als seus habitants. Investigadors de la UAB estudien en el projecte europeu Newbits, han comparat Europa i els Estats Units (EUA) per conèixer els factors crítics en la seva difusió entre la població. Reticències a l'ús de tecnologies de seguiment o el suport d'autoritats locals en mobilitat compartida i la ciberseguretat i l'ètica en el vehicle autònom en són alguns dels que han detectat.La movilidad compartida, la movilidad como servicio y el vehículo autónomo se han propuesto como dos soluciones adecuadas que contribuirán al disfrute de ciudades más eficientes y con una mejor calidad de vida para sus habitantes. Investigadores de la UAB estudian en el proyecto europeo Newbits, han comparado Europa y los Estados Unidos (EE.UU.) para conocer los factores críticos en su difusión entre la población. Algunos de los factores que han detectado son reticencias al uso de tecnologías de seguimiento, el apoyo de autoridades locales en movilidad compartida y la ciberseguridad y la ética en el vehículo autónomo.Sharing mobility, mobility as a service and autonomous vehicles have been proposed as two suitable solutions that will contribute to the enjoyment of more efficient cities and with a better living quality for its inhabitants. Researchers of the UAB participating in the European project Newbits have compared Europe and the United States (US) to discover the critical factors in its diffusion among the population. Reluctance to the use of tracking technologies and the support of local authorities in sharing mobility and cybersecurity, as well as ethics in the autonomous vehicle are some factors that have been detected

Cos4Cloud - Integrating Citizen Science in the European Open Science Cloud: Challenges and opportunities for developing a new generation of Citizen Science Observatories

5th Annual International Conference on Participatory Research, Citizen Sciences, Crowd-Innovation and Fab Labs for Peace and Development - 12th Geneva Forum, 7-11 December 2020Citizen science is one of the eight priorities of the European Open Science Agenda, together with the creation of the European Open Science Cloud (EOSC). EOSC incorporates the European Commission’s vision of an extensive infrastructure to support and develop open science and open innovation in Europe and beyond. This new ecosystem provides a virtual environment for all researchers to store, manage, analyze, and re-use their products (software, data, among others.) for research, innovation, and educational purposes. Within this framework, the H2020 ‘Co-designed Citizen Observatories Services for the EOS-Cloud’ project (2019-2022) aspires to integrate citizen science in the EOSC ecosystem. COS4CLOUD aims to develop essential research and technology to co-design and prototype innovative services to address critical challenges faced by citizen observatories. The final goal is to improve the implementation of existing and future citizen observatories and to contribute to ensuring their sustainability. Based on several citizen observatories currently widely in use in Europe and some new ones such as the EU-Citizen.Science, a range of innovative services, will be co-designed, prototyped, and implemented. These innovative services range from tools for improving data and information quality using deep machine learning, automatic video recognition, advanced mobile app interfaces, and other cutting-edge technologies, as well as mechanisms to ensure the visibility and recognition of data contributors and the tools to improve networking between various stakeholders. The design of these new services is user-oriented, engaging a wide range of stakeholders in society (public sector, industry, SMEs, academia, education, and research agencies) to co-design requirements and satisfy user needs. For co-design, developing, and testing services, COS4CLOUD will develop a diverse range of activities from datathons, hackathons, among others; as well as creating a space for knowledge exchange and sharing best practice. These activities could be a useful space for promoting the collaborative work between citizen observatories, especially in common challenges about infrastructure and technology. Likewise, enhance the networking between them and search for opportunities and solutions for their sustainability. Apart from inviting the citizen science community to involve in COS4CLOUD, we will share the progress in some of the questions that COS4CLOUD is working on like: How these innovative services could contribute to the implementation of Open Science in Europe? Which are the potential connections with other ongoing initiatives (i.e. Eu-Citizen.Science, ...) ? What are the challenges faced by citizen observatories in terms of quality and interoperability? What are the opportunities that new technologies are bringing? How to implement FAIR data approach in citizen science and what is lacking in this approach from the perspective of citizen science?Peer reviewe