2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)最新文献

{"title":"An Approach to Autonomous Contingency Management in Urban Air Mobility: The Communication Network Awareness Machine System","authors":"Vincent E. Houston","doi":"10.1109/DASC50938.2020.9256460","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256460","url":null,"abstract":"Next Generation Air Transportation System (NextGen) has begun the modernization of the nation's air transportation system (NAS), with goals to improve system safety, increase operation efficiency and capacity, provide enhanced predictability, resilience and robustness [1]. The overall objective of the Air Traffic Management-eXploration (ATM-X) project is to facilitate the goals of NextGen by conducting research to enable the growing demand of new, mission variant, air vehicles with safe access to the NAS. The implementation and utilization of new and burgeoning technologies that are both flexible, scalable, and systematically user-focused are requisite for ATM-X to achieve its intention of NAS safe entry [2]. Researchers from NASA Langley's Flight Deck Integration Team have developed a system architecture that would allow ATM-X to leverage the necessary capabilities of an Increasingly Autonomous System (IAS), machine-agent that will promote the safe access and operation of air vehicles within what has become the byproduct of NextGen modernization, a Net-Centric airspace architecture and an Urban Air Mobility (UAM) community. Conducting flight operations within this type of architecture constrains the human-agent's natural ability to data manage. When the massive volume of data, its types, and the acquisition speed at which the data is ingested is observed it becomes evident that the human-agent will be functioning at an operational disadvantage. Therefore, the development and integration of intelligent machine-agents into the flight deck are a necessary implementation to achieve ATM-X overall objective of safe access and operation in the NAS.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133320552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning for drone operations: challenge accepted","authors":"E. Baskaya, M. Bronz","doi":"10.1109/DASC50938.2020.9256557","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256557","url":null,"abstract":"Machine learning is among the top research topics of the last decade in terms of practicality and popularity. Though often unnoticed, machine learning guides many aspects of our lives since its introduction via the big tech companies. Its abilities rise, defeating 9-dan Go professional, their accuracy increase, enabling smooth voice recognition, adding intelligence to our daily lives. However, its development is mostly supported by high tech companies for now rather than the public, or regulations, who show increasing concern about its usage. Despite some reluctance, machine learning has started to appear in aviation as well. Operational improvements were among the first applications. In this paper, we offer to present an introduction to machine learning, compare it with well known modeling techniques by giving an example from aviation and question their fitness for certification. We discuss the enablers and try to understand the limitations that might result or prevent the use of machine learning on certified safety systems. Similar considerations are held for systems that do not require certification, but need to be taken into account in risk analysis methods. The ultimate purpose of this paper is to highlight the existing challenges which prevent machine learning algorithms from having a wider role in drone avionics, and more generally in aviation.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133642111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Authentication and Authorization Challenges for Controller-Pilot Information Exchange Using Mobile Devices","authors":"P. Diffenderfer, Diane M. Baumgartner, Kevin Long, C. F. Pertsch, Sara D. Iacobucci","doi":"10.1109/DASC50938.2020.9256433","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256433","url":null,"abstract":"While most General Aviation (GA) pilots use some form of mobile application to file their flight plans and receive other pre-departure services, obtaining a departure clearance still requires voice communications, which can be time consuming and susceptible to errors. The MITRE Corporation's Center for Advanced Aviation System Development (MITRE CAASD) has been researching and prototyping ways to deliver departure clearances to pilots via their mobile devices without speaking a single word. Our more recent research involves studying the flight safety and information security aspects of providing voiceless Instrument Flight Rules (IFR) clearances, negotiation of IFR departure release at non-towered airports, and cancellation of IFR at non-towered airports using commercial mobile devices and technology. For brevity, we use the term “mobile IFR services” to describe these services intended for pilot use while aircraft are on the ground and not moving. Traditionally, information is exchanged between the Federal Aviation Administration (FAA) and certified avionics installed on an aircraft. The mobile IFR services environment will differ from this in several ways: •Information will be exchanged using readily available commercial hardware (e.g., mobile phones, tablets), services (e.g., wireless and mobile telecommunication networks), and applications (e.g., integrated into existing flight planning applications). •Data exchange will be performed by users acting on behalf of an aircraft (e.g., pilot, co-pilot, and dispatcher) and not by the aircraft avionics. •A single aircraft may be used by a multitude of pilots; for example, this is true of pilots who fly for a fleet of on-demand charter or fractional ownership aircraft, fly at a flight training school, or rent aircraft. There are many challenges to realizing mobile IFR services—particularly because the devices used to exchange information are not permanently bound to a single aircraft. Additional steps must be taken to ensure that users are who they say they are (authentication) and have the authority to act on behalf of a particular aircraft (authorization). Authentication and authorization are tightly coupled and must be considered together to ensure that information is exchanged only between the correct parties for a legitimate purpose. Understanding the burden required of service providers, users, and regulatory bodies, MITRE is researching practicable approaches for authentication and authorization within this new environment. This paper discusses various options currently being explored.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"56 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131772288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Operational Analysis of Vertiport Surface Topology","authors":"S. Zelinski","doi":"10.1109/DASC50938.2020.9256794","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256794","url":null,"abstract":"Urban Air Mobility (UAM) concepts and technologies are being developed to safely enable operations of small, electric-powered or hybrid, pilot-optional, vertical-takeoff-and-landing (VTOL) passenger and cargo aircraft at vertiport facilities in urban and suburban environments. It is likely that many of the highest demand locations for vertiports will be in space constrained urban environments, requiring vertiport designs to maximize throughput within a compact surface footprint. This paper presents several generic vertiport topology design approaches and evaluates their relative surface area utilization and operational efficiency under different wind constrained configurations while meeting safety driven spacing constraints derived from heliport design standards and subject matter expert interviews.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"249 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115073313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Avionics Testing with Artificial Intelligence Support","authors":"P. Paces","doi":"10.1109/DASC50938.2020.9256563","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256563","url":null,"abstract":"This paper describes a concept allowing for automated testing of avionics installed on a test bench where concepts of Artificial Intelligence are used. This test bench technology provides means for fast discovery of changes in behavior of new releases of avionics software where feature corrections can lead to modified behavior of other functions. The tested avionics is installed in a simulator test bench allowing to simulate behavior and systems of the respective airplane type. The test bench allows the pilot himself to test the functionality which can be repeated by the automation system itself. The technology behind the simulator collects all the data from the test bench internal buses under different conditions to be used as a reference to identity deviations from expected behavior of the avionic systems. The Artificial Intelligence methods used in our approach include state space search algorithms for determination of required control routines and data learning related to identification of deviations in behavior.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114685256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Building Trust in Autonomous System Competence – the DiTA Digital Tower Assistant for Multiple Remote Towers, an Early Concept Evaluation","authors":"C. Westin, Supathida Boonsong, B. Josefsson, Jonas Lundberg","doi":"10.1109/DASC50938.2020.9256759","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256759","url":null,"abstract":"A bottleneck of (future) multiple remote tower operations (MRTO) is for controllers to monitor traffic movements at two airports (or more) in real-time, at the same time. To address this, we propose an autonomous agent (digital colleague), the DiTA Digital Tower Assistant. The key issue addressed by the DiTA concept is simultaneous movements on the two airports. We present results from the first stages of concept design and evaluation of DiTA. We conducted two workshops with three fully licensed air traffic controllers. During the workshops the controllers evaluated the DiTA concept of operations through scenario walk-throughs using printed airspace maps. The outcome of the workshop series was a tentative concept of DiTA operations and key concerns for one MRTO scenario. We present and discuss the emerging picture of common concerns and views on acceptable concept of operations as the workshops progressed. We conclude that it is is vital that operators can place the right level of trust in autonomous system competence, especially when they manage safety critical movements. To achieve this, DiTA competence is a key concern. The build-up of operator trust and competence to assess DiTA comptence (re-skilling) could both rely on automation transparency and a stepwise introduction of the concept in operations.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114698406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding General Aviation Accidents in Terms of Safety Systems","authors":"Justin G. Fuller, L. Hook","doi":"10.1109/DASC50938.2020.9256778","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256778","url":null,"abstract":"This research provides a new, data-driven method that could be used to estimate the impact of integrating an automated safety system into a target class of general aviation aircraft. General Aviation (GA), that is, air travel apart from scheduled air carriers, is still more dangerous than automobile travel by several metrics. This fact should drive research to understand which safety systems might make significant improvements in GA aircraft safety. Pre-existing accident classification schemes are often very general and do not necessarily provide the insight necessary to judge the impact of a given safety technology. This paper attempts to use machine learning methods, applied to a novel transformation of the publicly available NTSB accident database, to create a model based on a set of pre-scored accident records that can be used to provide a notional estimate of the impact of an automatic ground collision avoidance system (Auto GCAS) in terms of fatal events that might have been prevented had such a system been installed. This study found that the number of fatality accidents that were predicted to be prevented by Auto GCAS was significant. The events that were thus predicted by the model spanned multiple CICTT Occurrence Categories, indicating that attempting to categorize the impact of the Auto GCAS system in terms of controlled flight into terrain (CFIT) alone, for example, would under-represent the potential benefit by not including saves cutting across the low altitude operations (LALT), unintended flight into instrument meteorological conditions (UIMC), and loss of control in-flight (LOC-I) categories.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124894460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulating ADS-B Attacks in Air Traffic Management","authors":"Anton Blåberg, G. Lindahl, A. Gurtov, B. Josefsson","doi":"10.1109/DASC50938.2020.9256438","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256438","url":null,"abstract":"In Air Traffic Management (ATM) training, simulations of real air traffic control (ATC) scenarios are a key part of practical teaching. On the internet one may find multiple different ATM simulators available to the public with open source code. Today most aircraft transmit data about position, altitude, and speed into the atmosphere that practically are unencrypted data points. This data is called automatic dependant surveillance broadcast (ADS-B) data. The lack of security means that potential attackers could project “fake” ADS-B data and spoof existing data to air traffic controllers (ATCO) if the right equipment is used. We see this as a security flaw and we want to prepare ATCO for cyberattacks by modifying an ATM simulator with cyberattacks. First, OpenScope was chosen as the ATM simulator to be modified. Subsequently, three types of attacks were chosen for the simulator to be equipped with, based on ADS-B weaknesses from existing literature: aircraft not responding to commands, aircraft with altering positional data, and aircraft with incorrect speed and altitude data. The recorded parameters were the written command lines and corresponding aircraft type it was applied to. Using this modified simulator, ATCO can now be evaluated against cyberattacks.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122991733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards Developing Formalized Assurance Cases","authors":"B. Meng, A. Moitra, A. Crapo, S. Paul, Kit Siu, Michael Durling, D. Prince, H. Herencia-Zapana","doi":"10.1109/DASC50938.2020.9256740","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256740","url":null,"abstract":"The ever-increasing complexity of cyber physical systems drives the need for assurance of critical infrastructure and embedded systems. Building assurance cases is a way to increase confidence in systems. In general, the construction of assurance cases is a manual process and the resulting artifacts are not machine analyzable. The High Assurance Systems team at GE Research is developing technology to support generation of formalized assurance cases for systems, which are both human-readable and machine-analyzable. We have developed a Semantic Application Design Language Assurance Toolkit (SADL-AT) including a semantic model to formalize the Goal Structuring Notation for assurance cases. This paper describes the toolkit SADL-AT and demonstrates the capabilities and effectiveness of SADL-AT by building security and safety assurance case fragments for an unmanned aerial vehicle-based example – a delivery drone.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123604319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing Autonomy in Aviation: A Holistic Approach","authors":"Stephen Cook, Anna Dietrich, L. Hook, W. Ryan, David M. Stevens","doi":"10.1109/DASC50938.2020.9256568","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256568","url":null,"abstract":"Safely implementing increased automation and autonomy in aviation systems offers the promise of improved operational safety, increased air mobility, and economic benefits for millions of people across the globe. However, many technical approaches to autonomy do not follow a holistic approach, taking into account the challenges associated with terminology, certification, fundamental design principles, and current human-centric regulations. Solving challenges in one or some of these areas will not be enough to move aviation into a high level of automation towards future autonomy. For example, even if the technology is available, the regulator must have evidence to know it is safe, and the flying public expects the regulator to certify the aircraft before entrusting their safety to it. Thus, as aviation moves into the age of autonomy, it is essential to have consensus standards that understand the need for a holistic approach to support the safe and effective use of autonomous aircraft. To meet these challenges, in 2017 ASTM International established Task Group AC377 for “Autonomy Design and Operations in Aviation.” The AC377 Task Group has the responsibility for harmonizing terminology, certification requirements constructs, and fundamental autonomy concepts among ASTM aviation committees that produce consensus standards for aviation – F37 for Light Sport Aircraft, F38 for Unmanned Aircraft Systems, F39 for Aircraft Systems, and F44 for General Aviation – with the goal of promoting consistency and transferability in standards relating to aviation autonomy. ASTM AC377 uses a holistic approach to develop guidance materials in the form of technical reports. This paper will discuss the progress to date in addressing these challenges and recommend next steps to close remaining gaps.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130777910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}