Development of a 3-Dimensional Mathematical Collision Risk Model Based on Recorded Aircraft Trajectories to Estimate the Safety Level in High Density En-Route Airspaces

Como en todos los medios de transporte, la seguridad en los viajes en avión es de primordial importancia. Con los aumentos de tráfico aéreo previstos en Europa para la próxima década, es evidente que el riesgo de accidentes necesita ser evaluado y monitorizado cuidadosamente de forma continúa. La Tesis presente tiene como objetivo el desarrollo de un modelo de riesgo de colisión exhaustivo como método para evaluar el nivel de seguridad en ruta del espacio aéreo europeo, considerando todos los factores de influencia. La mayor limitación en el desarrollo de metodologías y herramientas de monitorización adecuadas para evaluar el nivel de seguridad en espacios de ruta europeos, donde los controladores aéreos monitorizan el tráfico aéreo mediante la vigilancia radar y proporcionan instrucciones tácticas a las aeronaves, reside en la estimación del riesgo operacional. Hoy en día, la estimación del riesgo operacional está basada normalmente en reportes de incidentes proporcionados por el proveedor de servicios de navegación aérea (ANSP). Esta Tesis propone un nuevo e innovador enfoque para evaluar el nivel de seguridad basado exclusivamente en el procesamiento y análisis trazas radar. La metodología propuesta ha sido diseñada para complementar la información recogida en las bases de datos de accidentes e incidentes, mediante la provisión de información robusta de los factores de tráfico aéreo y métricas de seguridad inferidas del análisis automático en profundidad de todos los eventos de proximidad. La metodología 3-D CRM se ha implementado en un prototipo desarrollado en MATLAB © para analizar automáticamente las trazas radar y planes de vuelo registrados por los Sistemas de Procesamiento de Datos Radar (RDP) e identificar y analizar todos los eventos de proximidad (conflictos, conflictos potenciales y colisiones potenciales) en un periodo de tiempo y volumen del espacio aéreo. Actualmente, el prototipo 3-D CRM está siendo adaptado e integrado en la herramienta de monitorización de prestaciones de Aena (PERSEO) para complementar las bases de accidentes e incidentes ATM y mejorar la monitorización y proporcionar evidencias de los niveles de seguridad. ABSTRACT As with all forms of transport, the safety of air travel is of paramount importance. With the projected increases in European air traffic in the next decade and beyond, it is clear that the risk of accidents needs to be assessed and carefully monitored on a continuing basis. The present thesis is aimed at the development of a comprehensive collision risk model as a method of assessing the European en-route risk, due to all causes and across all dimensions within the airspace. The major constraint in developing appropriate monitoring methodologies and tools to assess the level of safety in en-route airspaces where controllers monitor air traffic by means of radar surveillance and provide aircraft with tactical instructions lies in the estimation of the operational risk. The operational risk estimate normally relies on incident reports provided by the air navigation service providers (ANSPs). This thesis proposes a new and innovative approach to assessing aircraft safety level based exclusively upon the process and analysis of radar tracks. The proposed methodology has been designed to complement the information collected in the accident and incident databases, thereby providing robust information on air traffic factors and safety metrics inferred from the in depth assessment of proximate events. The 3-D CRM methodology is implemented in a prototype tool in MATLAB © in order to automatically analyze recorded aircraft tracks and flight plan data from the Radar Data Processing systems (RDP) and identify and analyze all proximate events (conflicts, potential conflicts and potential collisions) within a time span and a given volume of airspace. Currently, the 3D-CRM prototype is been adapted and integrated in AENA’S Performance Monitoring Tool (PERSEO) to complement the information provided by the ATM accident and incident databases and to enhance monitoring and providing evidence of levels of safety.

Radar track segmentation with cubic splines for collision risk models in high density terminal areas

This paper presents a method to segment airplane radar tracks in high density terminal areas where the air traffic follows trajectories with several changes in heading, speed and altitude. The radar tracks are modelled with different types of segments, straight lines, cubic spline function and shape preserving cubic function. The longitudinal, lateral and vertical deviations are calculated for terminal manoeuvring area scenarios. The most promising model of the radar tracks resulted from a mixed interpolation using straight lines for linear segments and spline cubic functions for curved segments. A sensitivity analysis is used to optimise the size of the window for the segmentation process.

Metagenomic Anlaysis of microsymbiont selection by the legume plant host

Rhizobium leguminosarum bv.viciae is able to establish nitrogen-fixing symbioses with legumes of the genera Pisum, Lens, Lathyrus and Vicia. Classic studies using trap plants (Laguerre et al., Young et al.) provided evidence that different plant hosts are able to select different rhizobial genotypes among those available in a given soil. However, these studies were necessarily limited by the paucity of relevant biodiversity markers. We have now reappraised this problem with the help of genomic tools. A well-characterized agricultural soil (INRA Bretennieres) was used as source of rhizobia. Plants of Pisum sativum, Lens culinaris, Vicia sativa and V. faba were used as traps. Isolates from 100 nodules were pooled, and DNA from each pool was sequenced (BGI-Hong Kong; Illumina Hiseq 2000, 500 bp PE libraries, 100 bp reads, 12 Mreads). Reads were quality filtered (FastQC, Trimmomatic), mapped against reference R. leguminosarum genomes (Bowtie2, Samtools), and visualized (IGV). An important fraction of the filtered reads were not recruited by reference genomes, suggesting that plant isolates contain genes that are not present in the reference genomes. For this study, we focused on three conserved genomic regions: 16S-23S rDNA, atpD and nodDABC, and a Single Nucleotide Polymorphism (SNP) analysis was carried out with meta / multigenomes from each plant. Although the level of polymorphism varied (lowest in the rRNA region), polymorphic sites could be identified that define the specific soil population vs. reference genomes. More importantly, a plant-specific SNP distribution was observed. This could be confirmed with many other regions extracted from the reference genomes (data not shown). Our results confirm at the genomic level previous observations regarding plant selection of specific genotypes. We expect that further, ongoing comparative studies on differential meta / multigenomic sequences will identify specific gene components of the plant-selected genotypes

Effect of the Legume Plant Host on Rhizobial Soil Population Dynamics

Rhizobium leguminosarum bv viciae (Rlv) is a soil bacterium able to establish specific root-nodule symbioses with legumes of four different genera: Pisum, Vicia, Lens and Lathyrus. Rlv isolates from nodules of any of these legumes can nodulate any of them; however, it has been shown that plants select specific rhizobial genotypes from those present in the soil (1,2). We have previously shown this at the genomic level by following a population genomics approach. Pool genomic sequences from 100 isolates from each of four plant species: P. sativum, L. culinaris, V. faba and V. sativa, show different, specific profiles at the single nucleotide polymorphism (SNP) level for relevant genes. In this work, the extent of Rlv selection from a well-characterized soil population by different legume plant hosts: P. sativum, L. culinaris, V. faba and V. sativa, after a medium-term mesocosm study is described. Direct soil isolates from each of these mesocosm studies have been tested for specific rhizobial genes (glnII and fnrN) and symbiotic genes (nodC and nifH). Different populations were characterized further by Sanger sequencing of both the rpoB phylogenetic marker gene and the symbiotic genes nodC and nifH. The distribution and size of the rhizobial population for each legume host showed changes during the medium-term mesocosm study. Particularly, a non-symbiotic group of rhizobia was enriched by all four hosts, in contrast to the symbiotic rhizobia profile, which was specific for each legume plant host.

The Pangenome of the Plant-Selected Rhizobium leguminosarum bv viciae Sub-popuations

Rhizobium leguminosarum bv viciae (Rlv) is a bacterium able to establish effective symbioses with four different legume genera: Pisum, Lens, Lathyrus and Vicia. Classic studies using trap plants have previously shown that, given a choice, different plants prefer specific genotypes of rhizobia, which are adapted to the host (1, 2). In previous work we have performed a Pool-Seq analysis bases on pooled DNA samples from Rlv nodule isolates obtained from Pisum sativum, Lens culinaris, Vicia fava and V. sativa plants, used as rhizobial traps. This experiment allowed us to test the host preference hypothesis: different plant hosts select specific sub-populations of rhizobia from the available population present in a given soil. We have observed that plant-selected sub-populations are different at the single nucleotide polymorphism (SNP) level. We have selected individual isolates from each sub-population (9 fava-bean isolates, 14 pea isolates 9 vetch isolates and 9 lentil isolates) and sequenced their genomes at draft level (ca. 30x, 90 contigs). Genomic analyses have been carried out using J-species and CMG-Biotools. All the isolates had similar genome size (7.5 Mb) and number of genes (7,300). The resulting Average Nucleotide Identity (ANIm) tree showed that Rhizobium leguminosarum bv viciae is a highly diverse group. Each plant-selected subpopulation showed a closed pangenome and core genomes of similar size (11,500 and 4,800 genes, respectively). The addition of all four sub-population results in a larger, closed pangenome of 19,040 genes and a core genome of similar size (4,392 genes). Each sub-population contains a characteristic set of genes but no universal, plant-specific genes were found. The core genome obtained from all four sub-populations is probably a representative core genome for Rhizobium leguminosarum, given that the reference genome (Rhizobium leguminosarum bv. viciae strain 3841) contains most of the core genome. We have also analyzed the symbiotic cluster (nod), and different nod cluster genotypes were found in each sub-population. Supported by MINECO (Consolider-Ingenio 2010, MICROGEN Project, CSD2009-00006).