Creation of Conflict-free Taxi Routes for Aircraft with Evolutionary Algorithms

Flight operations for aircraft are influenced by tools like arrival and departure managers, which create time constrained flight trajectories, but there is a lack of surveillance for ground operations. Therefore, DLR develops TRACC, a surface management system supporting trajectory based ground operations. It is able to create conflict-free “4D”-taxi routes using evolutionary algorithms, where especially the arrival time at the departure runway is optimized. TRACC creates the controller commands, controls deviations from the planned routes and analyses the impact on the ground taxi system

Traffic Network Identification Using Trajectory Intersection Clustering

The current airspace route system consists mainly of pre-defined routes with a low number of intersections to facilitate air traffic controllers to oversee the traffic. Our aim is a method to create an artificial and reliable route network based on planned or as-flown trajectories. The application possibilities of the resulting network are manifold, reaching from the assessment of new air traffic management (ATM) strategies or historical data to a basis for simulation systems. Trajectories are defined as sequences of common points at intersections with other trajectories. All common points of a traffic sample are clustered, and, after further optimization, the cluster centers are used as nodes in the new main-flow network. To build almost-realistic flight trajectories based on this network, additional parameters such as speed and altitude are added to the nodes and the possibility to take detours into account to avoid congested areas is introduced. As optimization criteria, the trajectory length and the structural complexity of the main-flow system are used. Based on these criteria, we develop a new cost function for the optimization process. In addition, we show how different traffic situations are covered by the network. To illustrate the capabilities of our approach, traffic is exemplarily divided into separate classes and class-dependent parameters are assigned. Applied to two real traffic scenarios, the approach was able to emulate the underlying route systems with a difference in median trajectory length of 0.2%, resp. 0.5% compared to the original routes

Performance Evaluation of Conflict-Free Trajectory Taxiing in Airport Ramp Area Using Fast-Time Simulations

The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been collaborating to conduct joint research addressing future surface traffic management challenges. The surface management tool from DLR, called Taxi Routing for Aircraft: Creation and Controlling (TRACC), was adapted to be integrated in NASA's fast-time simulation environment called Surface Operations Simulator and Scheduler (SOSS). The research described in this paper 1) applied TRACC to trajectory-based ramp traffic management, where TRACC generates conflict-free aircraft trajectories in a congested ramp area, 2) investigated the feasibility of the concept through the integrated TRACC-SOSS fast-time simulation, and 3) evaluated the performance of the integrated system. For this activity, TRACC was adapted for ramp operations at Charlotte Douglas International Airport, called TRACC_PB (TRACC for pushback optimization). TRACC_PB provides four-dimensional taxi trajectories with a command speed profile for each aircraft following standard taxi routes within the ramp area. In this study, departures are given the Target Movement Area entry Times (TMATs) provided by the baseline surface metering scheduler based on NASA's Spot and Runway Departure Advisor (SARDA). TRACC_PB also calculates optimal pushback times for departures, as well as the times when arrivals shall enter the ramp, the Target Movement area Exit Times (TMETs). The initial results showed that the TRACC_PB successfully generated conflict-free trajectories for the ramp area taxi operations and improved taxiing efficiency compared to the baseline results. TRACC_PB aimed to provide conflict-free taxi routes avoiding any stops while taxiing. This resulted in longer gate hold times for departures and postponed throughput values compared to the baseline simulation without trajectory optimization. Having conflict-free routes without stoppage also created shorter taxi times but required renegotiation of the given TMATs. TRACC_PB also achieved reductions in both fuel consumption and engine emissions (17% for departures and 10% for arrivals), which correlate with the ramp taxi time reduction

Performance Evaluation of the Approaches and Algorithms for Hamburg Airport Operations

The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted: one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft: Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective

THE AUTOMATION EVOLVES: CONCEPT FOR A HIGHLY AUTOMATED CONTROLLER WORKING POSITION

Air traffic controlling demands planning, coordination, and active management of airspace for safe flight operations. Human air traffic controllers are a highly skilled and trained workforce to perform air traffic control tasks augmented by system support. However, the growing air traffic volumes push human controllers to their limit in safely managing air traffic, compounded by difficulties in increasing the controller workforce. A feasible solution to meet the growing demand is to automate controller tasks by introducing the latest technology such as artificial intelligence and machine learning. Therefore, we propose a concept for highly automated Single Controller Operations (SCO) that provides a roadmap for future air traffic management systems to address this challenge, which was conceived as part of the project The Individual and Automated Air Traffic (DIAL)1. The most important ideas in the proposed concept are the introduction of the Digital co-Controller (DC) as an integral element of the new controller working position and the reduction of the number of human controllers to a single person. This paper describes the three-stage approach to evolve from a setting with two controllers (radar and planning) to a system consisting of a team with one human and one digital co-controller. Our paper presents the grouping of controller tasks along with the distribution of roles, responsibilities, and achievable automation levels in each stage. Furthermore, it discusses the necessary automation tools, the evolution of the role of the air traffic controller, and the technical background supporting the newly defined controller working position. Finally, fallback solutions are discussed in case the DC is unable to cope with an unexpected and complex situation

Enabling Digital Air Traffic Controller Assistant through Human-Autonomy Teaming Design

—The air traffic management domain has started to reap the benefits of Artificial Intelligence (AI) to support human controllers. However, the controller working position as the interface for managing air traffic is still limited to passively providing information, leaving the bulk of the tasks for human controllers, especially tasks involving decision-making. To meet the growing demands of air traffic, one way is to increase the level of automation in air traffic control systems. This requires a completely new task distribution for human controllers in combination with AI-based systems. Our paper will give an overview of our work related to the introduction of a digital Air Traffic Controller (ATCO) into an en-route controller working position. The digital ATCO is designed with the capabilities to perform several time-consuming tasks autonomously. The system is based on a meaningful distribution of tasks between a human and a digital ATCO. Several supporting tools and a Human-Autonomy Teaming (HAT) interface are described, which are able to handle different modes of HAT operations. Lastly, we describe a proof of concept setup of the system integrated in a controller working position that was presented at the AIRSPACE WORLD 2023

Colorectal cancer incidences in Lynch syndrome: a comparison of results from the prospective lynch syndrome database and the international mismatch repair consortium

Objective To compare colorectal cancer (CRC) incidences in carriers of pathogenic variants of the MMR genes in the PLSD and IMRC cohorts, of which only the former included mandatory colonoscopy surveillance for all participants. Methods CRC incidences were calculated in an intervention group comprising a cohort of confirmed carriers of pathogenic or likely pathogenic variants in mismatch repair genes (path_MMR) followed prospectively by the Prospective Lynch Syndrome Database (PLSD). All had colonoscopy surveillance, with polypectomy when polyps were identified. Comparison was made with a retrospective cohort reported by the International Mismatch Repair Consortium (IMRC). This comprised confirmed and inferred path_MMR carriers who were first- or second-degree relatives of Lynch syndrome probands. Results In the PLSD, 8,153 subjects had follow-up colonoscopy surveillance for a total of 67,604 years and 578 carriers had CRC diagnosed. Average cumulative incidences of CRC in path_MLH1 carriers at 70 years of age were 52% in males and 41% in females; for path_MSH2 50% and 39%; for path_MSH6 13% and 17% and for path_PMS2 11% and 8%. In contrast, in the IMRC cohort, corresponding cumulative incidences were 40% and 27%; 34% and 23%; 16% and 8% and 7% and 6%. Comparing just the European carriers in the two series gave similar findings. Numbers in the PLSD series did not allow comparisons of carriers from other continents separately. Cumulative incidences at 25 years were < 1% in all retrospective groups. Conclusions Prospectively observed CRC incidences (PLSD) in path_MLH1 and path_MSH2 carriers undergoing colonoscopy surveillance and polypectomy were higher than in the retrospective (IMRC) series, and were not reduced in path_MSH6 carriers. These findings were the opposite to those expected. CRC point incidence before 50 years of age was reduced in path_PMS2 carriers subjected to colonoscopy, but not significantly so

Psychosocial impact of undergoing prostate cancer screening for men with BRCA1 or BRCA2 mutations.

OBJECTIVES: To report the baseline results of a longitudinal psychosocial study that forms part of the IMPACT study, a multi-national investigation of targeted prostate cancer (PCa) screening among men with a known pathogenic germline mutation in the BRCA1 or BRCA2 genes. PARTICPANTS AND METHODS: Men enrolled in the IMPACT study were invited to complete a questionnaire at collaborating sites prior to each annual screening visit. The questionnaire included sociodemographic characteristics and the following measures: the Hospital Anxiety and Depression Scale (HADS), Impact of Event Scale (IES), 36-item short-form health survey (SF-36), Memorial Anxiety Scale for Prostate Cancer, Cancer Worry Scale-Revised, risk perception and knowledge. The results of the baseline questionnaire are presented. RESULTS: A total of 432 men completed questionnaires: 98 and 160 had mutations in BRCA1 and BRCA2 genes, respectively, and 174 were controls (familial mutation negative). Participants' perception of PCa risk was influenced by genetic status. Knowledge levels were high and unrelated to genetic status. Mean scores for the HADS and SF-36 were within reported general population norms and mean IES scores were within normal range. IES mean intrusion and avoidance scores were significantly higher in BRCA1/BRCA2 carriers than in controls and were higher in men with increased PCa risk perception. At the multivariate level, risk perception contributed more significantly to variance in IES scores than genetic status. CONCLUSION: This is the first study to report the psychosocial profile of men with BRCA1/BRCA2 mutations undergoing PCa screening. No clinically concerning levels of general or cancer-specific distress or poor quality of life were detected in the cohort as a whole. A small subset of participants reported higher levels of distress, suggesting the need for healthcare professionals offering PCa screening to identify these risk factors and offer additional information and support to men seeking PCa screening

Management of Time Based Taxi Trajectories coupling Departure and Surface Management Systems

This paper presents concept and results of the coupling of the surface management system research prototype “TRACC: Taxi Routing for Aircraft: Creation and Controlling” with the departure management system “CADEO: Controller Assistance for Departure Optimisation”. TRACC supports Air Traffic Controllers ) in creating optimized conflict-free taxi trajectories as well as with conflict detection and resolution. TRACC features speed control as new element of surface management and extends the concept of time-based trajectories to the ground. With up-to-date trajectories and therewith accurate taxi time prediction, the cooperation with the runway sequence optimizer prototype CADEO is enhanced. Within this paper both tools are introduced briefly and necessary adaptions of CADEO and TRACC for a combined application are described like push-back management and management of target start-up times. Results of first simulation runs are presented

GTRP: Generic Taxi Routing Program

Das Ziel dieses Berichtes ist es, einen Einblick in Ziele und verwendete Verfahren des Programms GTRP zu vermitteln. Hierbei soll auf die von GTRP zu lösende Problemstellung ebenso eingegangen werden, wie auf die verwendeten Routinen und Methoden, sowie den theoretischen Hintergrund hinter dem Lösungsansatz durch die Verwendung eines Evolutionären Algorithmus (EA). Zudem wird in diesem Dokument dargestellt, welche Tests zu der letztendlich gewählten Kombination von Parametern für den EA geführt haben und welche Eingabedaten verwendet wurden. Dieser Bericht dokumentiert den Stand der bisherigen Arbeiten und kann als Hilfsmittel verwendet werden, um beispielsweise einzelne Algorithmen (z.B. Routenfindung, Konfliktlösung) in andere Pro-gramme zu übernehmen