Early warning system of natural hazards and decrease of climat impact from aviation; ALARM funded project

Aviation safety can be jeopardised by multiple hazards arising from natural phenomena, e.g., severe weather, aerosols/gases from natural hazard, and space weather. Furthermore, there are the anthropogenic emissions and climate impact of aviation that could be reduced. To mitigate such risk and/or to decrease climate impact, tactical decision-making processes could be enhanced through the development of multihazard monitoring and Early Warning System (EWS). With this objective in mind, ALARM consortium has implemented alert products (i.e., observations, detection and data access in near realtime) and tailored product (notifications, flight level — FL contamination, risk area, and visualization of emission/risk level) related to Natural Airborne Hazard (NAH, i.e., volcanic, dust and smoke clouds) and environmental hotspots. New selective detection, nowcasting and forecasts of such risks for aviation have been implemented as part of ALARM prototype EWS. This system has two functionalities. One is to provide alerts on a global coverage using remote sensing from satellites and models (focus on NAH, space weather activity and environmental hotspots). A second focuses on detecting severe weather and exceptional SO2 conditions around a selection of few airports, on providing nowcasts and forecasts of risk conditions

Human Computer Interactions in Next-Generation of Aircraft Smart Navigation Management Systems: Task Analysis and Architecture under an Agent-Oriented Methodological Approach

The limited efficiency of current air traffic systems will require a next-generation of Smart Air Traffic System (SATS) that relies on current technological advances. This challenge means a transition toward a new navigation and air-traffic procedures paradigm, where pilots and air traffic controllers perform and coordinate their activities according to new roles and technological supports. The design of new Human-Computer Interactions (HCI) for performing these activities is a key element of SATS. However efforts for developing such tools need to be inspired on a parallel characterization of hypothetical air traffic scenarios compatible with current ones. This paper is focused on airborne HCI into SATS where cockpit inputs came from aircraft navigation systems, surrounding traffic situation, controllers' indications, etc. So the HCI is intended to enhance situation awareness and decision-making through pilot cockpit. This work approach considers SATS as a system distributed on a large-scale with uncertainty in a dynamic environment. Therefore, a multi-agent systems based approach is well suited for modeling such an environment. We demonstrate that current methodologies for designing multi-agent systems are a useful tool to characterize HCI. We specifically illustrate how the selected methodological approach provides enough guidelines to obtain a cockpit HCI design that complies with future SATS specifications.This work was supported in part by Projects MINECO TEC2011-28626-C02-01/02, by program CENIT-ATLANTIDA (cofinanced by Indra and Boeing R&TE), and by ULPGC Precompetitive Research Project (ULPGC Own Program).Publicad

Active Traffic Management Case Study: Phase 1

This study developed a systematic approach for using data from multiple sources to provide active traffic management solutions. The feasibility of two active traffic management solutions is analyzed in this report: ramp-metering and real-time crash risk estimation and prediction. Using a combined dataset containing traffic, weather, and crash data, this study assessed crash likelihood on urban freeways and evaluated the economic feasibility of providing a ramp metering solution. A case study of freeway segments in Omaha, Nebraska, was conducted. The impact of rain, snow, congestion, and other factors on crash risk was analyzed using a binary probit model, and one of the major findings from the sensitivity analysis was that a one-mile-per-hour increase in speed is associated with a 7.5% decrease in crash risk. FREEVAL was used to analyze the economic feasibility of the ramp metering implementation strategy. A case study of a 6.3 mile segment on I-80 near downtown Omaha showed that, after applying ramp metering, travel time decreased from 9.3 minutes to 8.1 minutes and crash risk decreased by 37.5% during the rush hours. The benefits of reducing travel time and crash cost can easily offset the cost of implementing ramp metering for this road section. The results from the real-time crash risk prediction models developed for the studied road section are promising. A sensitivity analysis was conducted on different models and different temporal and spatial windows to estimate/predict crash risk. An adaptive boosting (AdaBoost) model using a 10 minute historical window of speeds obtained from 0.25 miles downstream and 0.75 miles upstream was found to be the most accurate estimator of crash risk

Analysis of the Cyber Attacks against ADS-B Perspective of Aviation Experts

Käesolev töö loob põhjaliku ülevaate lennunduses valitsevatest küberjulgeoleku ohtudest. Tsiviillennunduse lennuliiklusteenindus ja õhuseire on üleminekufaasis valmistudes kasutusele võtma uue põlvkonna tehnoloogiaid, mis tulevikus asendavad praeguse radaripõhise lennukite jälgimissüsteemi uue satelliitpõhise süsteemiga. Lennunduse sideteenuste moderniseerimine loob aluse uuetele turvalisusega seotud ohtudele, mille võimalikke negatiivseid tagajärgi ei ole suudetud veel maandada. Magistritöö eesmärk on koostada kvalitatiivne süstemaatiline analüüs võimalikest küberrünnakutest uue satelliitpõhise automaatse sõltuva seire üldsaade (Automatic dependent surveillance-broadcast –ADS-B) vastu. Analüüs ühendab teadmised küberturvalisuse ja lennunduse valdkonnast, mille koos käsitlemine on oluline turvalise tagamise sesiukohalt. Töö fokusseerub ADS-B süsteemis esinevatele kitsaskohtadele, mis küberturvalise seisukohalt võivad kätkeda ohte või häirida tõsiselt lennuliiklusteeniduse tööd. Potentsiaalsed ohud ADS- S süsteemi vastu on kirjeldatud ja liigitatud sõltuvalt ohuastmest. Analüüsi põhiosa moodustab lennundus spetsialistide seas läbiviidud küsitlus, mille põhjal on hinnatud ohu tõsidust, selle mõju lennundussüsteemile ja milliseid toiminguid on vajalik rakendada ohu esinemise korral. Töö analüüs hindab mõned käsitletud ohtudest ebaoluliseks, mis ei kujuta endast märkisväärset probleemi süsteemi operaatoritele. Sellegi poolest esineb teatava keerulisuse astmega ohustsenaariumeid, mille tagajärjel on süsteem tugevalt häiritud või millega võib kaasneda ulatuslik kahju. Läbiviidud küsitluse põhjal on esitatud meetmeid, kuidas maandada võimalikke negatiivseid mõjusid ohuolukorras. Töö tulemused on olulised pööramaks tähelepanu lennunduses esinevatele küberohtudele. Töö on kirjutatud inglise keeles ja sisaldab 58 lehekülge, 5 peatükki, 17 joonist ja 15 tabelit.The present paper has a profound literature review of the relation between cyber security, aviation and the vulnerabilities prone by the increasing use of information systems in avia-tion realm. Civil aviation is in the process of evolution of the air traffic management sys-tem through the introduction of new technologies. Therefore, the modernization of aero-nautical communications are creating network security issues in aviation that have not been mitigated yet. The purpose of this thesis is to make a systematic qualitative analysis of the cyber-attacks against Automatic Dependent Surveillance Broadcast. With this analysis, the paper combines the knowledge of two fields which are meant to deal together with the security issues in aviation. The thesis focuses on the exploitation of the vulnerabilities of ADS-B and presents an analysis taking into account the perspective of cyber security and aviation experts. The threats to ADS-B are depicted, classified and evaluated by aviation experts, making use of interviews in order to determine the possible impact, and the ac-tions that would follow in case a cyber-attack occurs. The results of the interviews show that some attacks do not really represent a real problem for the operators of the system and that other attacks may create enough confusion due to their complexity. The experience is a determinant factor for the operators of ADS-B, because based on that a set of mitiga-tions was proposed by aviation experts that can help to cope in a cyber-attack situation. This analysis can be used as a reference guide to understand the impact of cyber security threats in aviation and the need of the research and aviation communities to broaden the knowledge and to increase the level of expertise in order to face the challenges posed by network security issues. The thesis is in English and contains 58 pages of text, 5 chapters, 17 figures, 15 tables

A machine learning approach based on generative topographic mapping for disruption prevention and avoidance at JET

The need for predictive capabilities greater than 95% with very limited false alarms are demanding requirements for reliable disruption prediction systems in tokamaks such as JET or, in the near future, ITER. The prediction of an upcoming disruption must be provided sufficiently in advance in order to apply effective disruption avoidance or mitigation actions to prevent the machine from being damaged. In this paper, following the typical machine learning workflow, a generative topographic mapping (GTM) of the operational space of JET has been built using a set of disrupted and regularly terminated discharges. In order to build the predictive model, a suitable set of dimensionless, machine-independent, physics-based features have been synthesized, which make use of 1D plasma profile information, rather than simple zero-D time series. The use of such predicting features, together with the power of the GTM in fitting the model to the data, obtains, in an unsupervised way, a 2D map of the multi-dimensional parameter space of JET, where it is possible to identify a boundary separating the region free from disruption from the disruption region. In addition to helping in operational boundaries studies, the GTM map can also be used for disruption prediction exploiting the potential of the developed GTM toolbox to monitor the discharge dynamics. Following the trajectory of a discharge on the map throughout the different regions, an alarm is triggered depending on the disruption risk of these regions. The proposed approach to predict disruptions has been evaluated on a training and an independent test set and achieves very good performance with only one tardive detection and a limited number of false detections. The warning times are suitable for avoidance purposes and, more important, the detections are consistent with physical causes and mechanisms that destabilize the plasma leading to disruptions.Peer reviewe

Conflict Detection and Resolution for Future Air Transportation Management

With a Free Flight policy, the emphasis for air traffic control is shifting from active control to passive air traffic management with a policy of intervention by exception. Aircraft will be allowed to fly user preferred routes, as long as safety Alert Zones are not violated. If there is a potential conflict, two (or more) aircraft must be able to arrive at a solution for conflict resolution without controller intervention. Thus, decision aid tools are needed in Free Flight to detect and resolve conflicts, and several problems must be solved to develop such tools. In this report, we analyze and solve problems of proximity management, conflict detection, and conflict resolution under a Free Flight policy. For proximity management, we establish a system based on Delaunay Triangulations of aircraft at constant flight levels. Such a system provides a means for analyzing the neighbor relationships between aircraft and the nearby free space around air traffic which can be utilized later in conflict resolution. For conflict detection, we perform both 2-dimensional and 3-dimensional analyses based on the penetration of the Protected Airspace Zone. Both deterministic and non-deterministic analyses are performed. We investigate several types of conflict warnings including tactical warnings prior to penetrating the Protected Airspace Zone, methods based on the reachability overlap of both aircraft, and conflict probability maps to establish strategic Alert Zones around aircraft

Advances in Data Mining Knowledge Discovery and Applications

Advances in Data Mining Knowledge Discovery and Applications aims to help data miners, researchers, scholars, and PhD students who wish to apply data mining techniques. The primary contribution of this book is highlighting frontier fields and implementations of the knowledge discovery and data mining. It seems to be same things are repeated again. But in general, same approach and techniques may help us in different fields and expertise areas. This book presents knowledge discovery and data mining applications in two different sections. As known that, data mining covers areas of statistics, machine learning, data management and databases, pattern recognition, artificial intelligence, and other areas. In this book, most of the areas are covered with different data mining applications. The eighteen chapters have been classified in two parts: Knowledge Discovery and Data Mining Applications