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

{"title":"3D Modeling of the airport environment for fast and accurate LiDAR semantic segmentation of apron operations","authors":"Hannes Brassel, A. Zouhar, H. Fricke","doi":"10.1109/DASC50938.2020.9256495","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256495","url":null,"abstract":"Airport ground operations must be safe and should avoid capacity backlogs. To that end, the availability of reliable surveillance data capturing important semantic information about the local traffic situation and the operating conditions on the apron and the maneuvering area are essential. Along those lines, LiDAR sensors combined with computer vision algorithms for semantic scene understanding were recently identified to offer a cost-effective, noncooperative surveillance solution that is expected to contribute to the operational goals mentioned above. However little work exists dealing with fast and accurate LiDAR semantic segmentation of such environments. This is partly due to the fact, that state-of-the-art algorithms in LiDAR semantic segmentation heavily rely on large-scale data sets with fine-grained labels. Although some hand-labeled data sets are publicly available, the point-wise annotation of 3D point clouds requires painstakingly work that is extremely cumbersome. Consequently, we propose a simulation-based approach to generate synthetic training data of the apron using a virtual airport environment that integrates a LiDAR sensor model. In this way, arbitrary scenarios captured under different operational conditions including static objects and moving aircraft provide labeled point data. This way, we trained and tested successfully a LiDAR semantic segmentation model emphasizing on aircraft approaching/leaving the gate after arrival/departure, thin structures (poles), airport buildings, and ground-plane. The developed technique provides an important baseline for the expected performance of the trained model on real data. We believe that the resulting framework provides additional visual cues capturing relevant semantic information that potentially assist the controller in complex situations.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"276 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":"116161752","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":"A Human-in-the-Loop Evaluation of ACAS Xu","authors":"R. Rorie, Casey L. Smith, Garrett G. Sadler, Kevin J Monk, Terence L Tyson, Jillian Keeler","doi":"10.1109/DASC50938.2020.9256618","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256618","url":null,"abstract":"Detect and avoid (DAA) systems provide unmanned aircraft systems (UAS) with an alternative means of compliance with the see-and-avoid requirements associated with operations in the National Airspace System (NAS). Previous studies have examined the efficacy of different DAA alerting and guidance structures and formats. Prior research has also investigated the integration of DAA information with the alerting and guidance generated by the Traffic Alert and Collision Avoidance System (TCAS II). The next-generation replacement for TCAS II – the Airborne Collision Avoidance System X (ACAS X) – includes a variant to be used by UAS (ACAS Xu) that will provide both DAA and Collision Avoidance (CA) guidance. The alerting and guidance issued by ACAS Xu differs from previous DAA and CA systems, a result of new capabilities that were not available to earlier systems. Differences include the removal of warning-level DAA alerting and guidance, as well as the issuance of new types of CA guidance, referred to as Resolution Advisories (RAs). Whereas TCAS II only issues vertical RAs, ACAS Xu adds horizontal and blended (i.e., simultaneous vertical and horizontal) RAs. The current study assessed pilots' ability to respond to and comply with the DAA and RA alerting and guidance generated by ACAS Xu in a human-in-the-loop simulation. Sixteen active UAS pilots participated in the study and were tasked with responding to scripted DAA and RA traffic conflicts. Results showed that pilots were effective at making timely maneuvers against DAA threats. The proportion of losses of DAA well clear against noncooperative intruders was found to be significantly higher than the proportion of losses against cooperative intruders, a result of the limited declaration range of the simulated onboard RADAR. Results also demonstrated that pilots could consistently meet the five second response time requirement for initial RAs. Rapid responses to RAs had the corresponding effect of minimizing the severity of losses of DAA well clear. While pilots complied with initial RAs at a high rate, compliance dropped substantially when the target heading was updated during a horizontal RA. Pilot performance with ACAS Xu will be presented alongside results from prior DAA research.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"129 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":"122428270","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":"Initial Control Strategies for Conflicting Automatic Safety Systems in General Aviation","authors":"Zack Kirkendoll, L. Hook, N. Hutchins","doi":"10.1109/DASC50938.2020.9256772","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256772","url":null,"abstract":"Despite improvements in technology and safety systems, general aviation remains a relatively unsafe method of travel. According to 2019 US government statistics, Controlled Flight Into Terrain (CFIT) and Loss of Control Inflight (LOC-I) are the top two contributors for aircraft total loses and number of fatalities in general aviation. Fortunately, automatic safety systems which have the potential to decrease terrain collision accidents have been recently introduced into production as are automatic methods to avoid aerodynamic stall and other precursors to loss of control accidents. However, the union of these systems into a single control mechanism carries as-of-yet unquantified risk and potential for emergent or undesired behavior. Therefore, the research presented in this paper focuses on potential control strategies for combining automatic terrain avoidance and automatically securing controlled flight which maximizes certain desirable characteristics. This work presents initial analyses of conflicting safety constraints and architectural choices, and their impacts on the overall safety of a fixed-wing general aviation aircraft. The primary interest of this paper is to address the sequence of states and control inputs in which both safety systems request control of the aircraft concurrently leading to a conflict compromising the vehicle's safety and will evaluate the benefits and drawbacks of using specific switching strategies and control blending. After the initial phase of identifying relevant cases of conflicts, we analyze those cases to show the effectiveness of a mitigation approach based on switched-system control. The paper will also provide data in order to direct system designers as to the best approach to solve these types of problems given their individual set of requirements. The study is conducted in a realtime six degree of freedom (6DoF) flight simulation using a Cessna 172 aircraft model.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"26 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":"125999559","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":"Flight Testing GLS Approaches using SBAS with the DLR A320 Advanced Technology Research Aircraft","authors":"T. Dautermann, T. Ludwig, R. Geister, Lutz Ehmke, Richard M. Unkelbach","doi":"10.1109/DASC50938.2020.9256631","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256631","url":null,"abstract":"We designed and built a system intended to combine the advantages of both the ground based and the satellite based augmentation systems (GBAS, SBAS) by using a converter between them. We installed a prototype system at Salzburg Airport and flight tested it on 12th of February 2020 using DLR's A320 test aircraft equipped with flight test instrumentation. Using our system, 3D GLS type approaches are possible at any airport within the coverage of the SBAS. The system includes an SBAS-capable global navigation satellite systems receiver with a database and a GBAS-compatible data link. The correction and integrity data received from the SBAS satellite are automatically translated into GBAS compatible structures and sent to the airborne GBAS receiver using the final approach segment data block Without SBAS the system can revert to differential GPS. In both GBAS and SBAS, instant integrity information is provided by estimating protection levels, a high probability bound for the computed position. This is then compared to the alert limit of the respective system. Since both systems are quite similar, and the SBAS signal can nowadays be decoded even by low cost receivers, one can receive the augmentation data from the SBAS, slightly modify it to fit into the GBAS data structure and broadcast this data to a GBAS equipped aircraft. Said aircraft could execute a RNP approach with the Localizer Performance and Vertical guidance (LPV) final approach segment which would otherwise not be available. This may come especially handy in places where no non-precision minima are published, such as the RNP-E approach into Innsbruck and Salzburg. Since there are slight differences between the two systems, we made sure that integrity for the safety-of-life approach service is ensured. We named the system GLASS (GLS Approaches using SbaS), built a prototype and tested it with real GBAS avionics hardware. We performed 4 approaches to Salzburg Airport in Austria (LOWS). Salzburg is now equipped with a RNP approach using LPV only to runway 15 with significantly a lower minimum than the RNP approach with LNAV minimum called the RNP E 15. This is due to the location of the new missed approach point. Using the GLASS system, all GLS equipped aircraft would be able to take advantage of this new minimum line. We followed the approach track using FMS guidance and recorded the ARINC 429 output from the Collins GLU925 Multimode Receiver (MMR). The GLASS guidance was provided to the pilot on the electronic flight bag display for reference. We show a complete analysis of integrity data, MMR status information and MMR output guidance. We compare the GLS data from the MMR with standard SBAS data from an onboard Septentrio PolaRx3 receiver. The GLASS system provides the LPV final approach segment to GLS-only equipped aircraft such as the Boeing 737-800. This can enable increased access to airports that are currently not equipped with an xLS type approach such as Innsbruck (LOWI). Especiall","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"40 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":"124373814","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":"Vision-based State Estimation and Collision Alerts Generation for Detect-and-Avoid","authors":"Jaehyun Lee, Hanseob Lee, D. Shim","doi":"10.1109/DASC50938.2020.9256797","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256797","url":null,"abstract":"This paper proposed a method to estimate non-cooperative intruder's state using Electro-Optical (EO) sensors and to generate conflict alerts to avoid the traffic. In civil area, expensive and noble sensors are not suitable to use for Detect-and-Avoid purpose. Low Cost, Size, Weight, and Power (C-SWaP) sensors as a detection sensors are should be used due to market's require. The demand of Low C-SWaP sensor is growing but the technology is not matured so far. The image-processing based robust aircraft detection algorithm is popular using neural network and the algorithm is applied in this research. The detected aircraft's flight state is estimated by Kalman Filter based on vision information to display collision risk. The concept of Distance at Closet Point of Approach (DCPA) is applied to keep DAA Well Clear (DWC). Overall, this paper shows whole process to implement DAA for non-cooperative aircraft using Low C-SWaP EO sensor. For this research, Conflict Prediction and Display System (CPDS) is applied to generate collision alerts and the CDPS is provided by General Atomics Aeronautical Systems Inc. (GA-ASI).","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"41 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":"132629951","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":"Terrain Referenced Integrity Monitor for an Unmanned Aircraft Systems Precision Approach","authors":"Andrew Videmsek, M. U. de Haag","doi":"10.1109/DASC50938.2020.9256636","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256636","url":null,"abstract":"This paper discusses the use of an on-board radar altimeter and Digital Elevation Model (DEM) for terrain referenced integrity monitoring during an Unmanned Aircraft Systems precision approach and landing. For operation of commercial UAS in the National Airspace System (NAS), a Performance Based Navigation (PBN) system applicable to all phases of flight is needed for unrestricted airspace and airport access. Methods, such as Radar Altimeter (RALT) Aiding, are currently being researched to create a Global Navigation Satellite System (GNSS) based navigation system with sufficient positional accuracy for a CAT-IIIc like precision approach and landing. While these systems have successfully addressed the vertical accuracy, horizontal accuracy, and vertical integrity requirements, further development for horizontal integrity is needed. This paper builds on previous work by the authors on radar altimeter augmentation to GNSS and discusses additional measures to improve the horizontal integrity of the navigation system. Performance of the proposed system is assessed in nominal and off-nominal conditions using data collected with a DC-3 aircraft at the Ohio University airport.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"36 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":"130422016","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":"Incorporating Agile Methodologies into DoD Software Sustainment Operations","authors":"Lacey Schley, R. Shehab, J. Antonio","doi":"10.1109/DASC50938.2020.9256629","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256629","url":null,"abstract":"The DoD is increasingly employing agile methods in efforts to rapidly produce software. However, the specific domain of agile methodologies as applied to the sustainment of embedded systems remains in need of further research. One initial area examined here is the relationship between agile principles and the policies and practices used by DoD sustainment organizations. It is shown that current sustainment policy for the Air Force Sustainment Center is compatible with agile principles. Challenges specific to sustainment operations can be resolved through careful consideration of the scope and organizational levels at which agile principles and practices are implemented.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"27 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132237761","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":"Aircraft Weight Estimation During Take-off Using Declarative Machine Learning","authors":"Sinclair Gurny, Jason Falvo, Carlos A. Varela","doi":"10.1109/DASC50938.2020.9256454","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256454","url":null,"abstract":"Aircraft sensors measure physical quantities to help pilots and flight automation systems with situational awareness and decision making. Unfortunately, some important quantities of interest (QoI), e.g., aircraft weight, cannot be directly measured by sensors. This may lead to accidents, exemplified by Tuninter 1153 and Cessna 172R N4207P, where the airplanes were underweight (not enough fuel) and overweight (6% over maximum gross weight) respectively. Learning models to infer QoI from other aircraft sensor data is thus critical to safety through analytical redundancy. In this paper, we extend PILOTS, our declarative programming language for stream analytics, to learn models from data. We illustrate the supervised machine learning extensions to PILOTS with an example where we use take-off speed profiles under different density altitudes and runway conditions to estimate aircraft weight. Using data collected from the X-Plane flight simulator for a Cessna 172SP, we compare the results of several models on accuracy and timeliness. We also consider ensemble learning to improve the accuracy of weight estimation during takeoff from 94.3% (single model) to 97% (multiple models). Given that the average length of a take-off is 26.75s, this model was able to converge within 10% of the correct weight after 10.7s and converge within 5% after 17.7s. On August 25th, 2014, a Cessna 172R, N4207P, crashed killing the pilot and three passengers. The National Transportation Safety Board (NTSB) report calculated the aircraft to be 1.06 times the maximum gross weight. We simulated the take-off in X-Plane using information from the report. We were able to estimate within 5% error after 8s, which is less than 200ft down the runway, and at the point of take-off, 27s, had an error of 3%. This implies that our model could have alerted the pilot of an overweight condition well before the aircraft became airborne, leaving more than 2000ft of runway to come to a stop. If this system were to be implemented in any fixed wing aircraft, it would create a larger safety net. Pilots would have a greater chance of catching errors thus increasing the probability of survival for crew and passengers.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"18 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":"134133162","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":"Rule-Based Conflict Management for Unmanned Traffic Management Scenarios","authors":"A. Alharbi, Arturo Poujade, Konstantinos Malandrakis, I. Petrunin, Dimitrios Panagiotakopoulos, A. Tsourdos","doi":"10.1109/DASC50938.2020.9256690","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256690","url":null,"abstract":"The growing use of Unmanned Aerial Vehicles (UAVs) operations will require effective conflict management to keep the shared airspace safe and avoid conflicts among airspace users. Conflicts pose high risk and hazard to human lives and assets as they ma may result in financial and human loss. The proposed rule-based conflict management model consists of three main stages. The first stage includes strategic deconfliction during the flight plan generation. The second stage, pre-tactical deconfliction, applies a ground delay to the agent to resolve the conflict. The third stage corresponds to the tactical deconfliction, where the drone hovers or loiter in the last waypoint before the conflict area until the conflict time window passes. The proposed method differs from most existing conflict management approaches in that it applies deconfliction methods sequentially using a rule-based strategy. Furthermore, a high number of published studies do not consider realistic airspace constraints and potential airspace modernization concepts such as dynamic flight restrictions Assessment and validation are performed in three simulation scenarios that consider different patterns of the airspace availability in the areas where flights may be restricted, such as airfields, recreational areas, and prisons. The Particle Swarm Optimization (PSO) algorithm was used for drone path planning. For the simulated scenarios all of the conflicts were resolved after implementation of the proposed method. The implemented method is simple, flexible and suitable for the management of more complex and dense airspaces.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"855 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":"132981412","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":"CDO Sensitivity Analysis for Robust Trajectory Planning under Uncertain Weather Prediction","authors":"Shumpei Kamo, J. Rosenow, H. Fricke","doi":"10.1109/DASC50938.2020.9256699","DOIUrl":"https://doi.org/10.1109/DASC50938.2020.9256699","url":null,"abstract":"When planning and predicting a flight trajectory, uncertainties are inherent both in the current values of various influencing factors and in their evolution. These uncertainties can turn initially “optimized” trajectories into impossible or at least less attractive solutions later when it is executed. In order to support a more robust trajectory planning for Continuous Descent Operations (CDO), this paper investigates how variations of those influencing factors impact the trajectory optimization fidelity. For this purpose, a set of optimal trajectories are generated for each of the variations and their sensitivities are analyzed. The trajectory optimization is formalized as a multi-phase optimal control problem and is numerically solved with the Legendre-Gauss Pseudospectral Method (LGPM). An iterative process is proposed to determine the required number of collocation points to grant a pre-set level of convergence. Case studies are carried out for International Standard Atmosphere (ISA) baseline conditions as well as for wind and temperature variations as relevant representatives of the weather prediction uncertainties. The numerical simulation results show shifts from the reference trajectory depending on wind and temperature variation. Uncertain wind speed caused a larger solution space and more variation in fuel burn than temperature errors. The designed solution spaces, especially the earliest and latest ToD locations, give pilots and air traffic controllers a good reference where their aircraft is expected to match best CDO goals under the individually prevailing uncertainties. We believe that such additional flight envelope information should complement current vertical path displays in glass cockpits to foster robust flight planning and execution.","PeriodicalId":112045,"journal":{"name":"2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC)","volume":"58 47","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113936700","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}