Pub Date : 2020-09-01DOI: 10.1109/ICNS50378.2020.9222911
Tao Li
It has been shown that flights can potentially achieve a significant amount of fuel burn reduction by flying the wind-optimal trajectories. This study estimates the benefits of flying the wind-optimal trajectory in the Pacific airspace using a simulation approach. Using the forecast of the 2020 traffic in the airspace, we found that airlines can save about 14,600 flight hours and 14 million gallons of fuel by using the wind-optimal trajectories inside the airspace. Depending on the Jet-A fuel price, the monetary value of the fuel savings ranges from 13 million dollars to 30 million dollars. There will also be a significant reduction in the workload of air traffic controllers and pilots.
{"title":"Evaluating the Benefits of Flying Wind-Optimal Trajectory Inside the Pacific Airspace","authors":"Tao Li","doi":"10.1109/ICNS50378.2020.9222911","DOIUrl":"https://doi.org/10.1109/ICNS50378.2020.9222911","url":null,"abstract":"It has been shown that flights can potentially achieve a significant amount of fuel burn reduction by flying the wind-optimal trajectories. This study estimates the benefits of flying the wind-optimal trajectory in the Pacific airspace using a simulation approach. Using the forecast of the 2020 traffic in the airspace, we found that airlines can save about 14,600 flight hours and 14 million gallons of fuel by using the wind-optimal trajectories inside the airspace. Depending on the Jet-A fuel price, the monetary value of the fuel savings ranges from 13 million dollars to 30 million dollars. There will also be a significant reduction in the workload of air traffic controllers and pilots.","PeriodicalId":424869,"journal":{"name":"2020 Integrated Communications Navigation and Surveillance Conference (ICNS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125686353","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}
Pub Date : 2020-09-01DOI: 10.1109/ICNS50378.2020.9222891
Tao Li
The hemispherical rules require that eastbound flights should use odd thousands flight levels (FLs) and westbound flights should use even thousands FLs. Though these rules improve safety, they could also negatively impact flight efficiency by, for example, reducing the available FLs that can be used to improve efficiency. With improved surveillance and communication capabilities in oceanic airspace, it is possible to use the FLs that do not comply with the hemispherical rules (non-complying FLs). The paper investigates whether doing so in the Pacific airspace could bring benefits to airlines and air traffic controllers. Our analysis showed mixed results. We found that fuel savings would increase as more flights accept non-complying FLs. If all flights accept non-complying FLs, the annual total fuel savings could reach 12.2 million gallons within the Oakland and Anchorage Flight Information Region (FIR). Depending on the price of Jet-A fuel, the monetary value of these fuel savings ranges from 11.25 to 25.66 million dollars. However, we also found that the annual total travel time inside the two FIRs would increase by about 2,070 flight hours. In addition, the workload of air traffic controllers and pilots may also increase as more flights accept non-complying FLs.
{"title":"Evaluating the Benefits of Accepting Cruising Flight Levels That Are Not in Compliance with the Hemispherical Rules in the Pacific Airspace","authors":"Tao Li","doi":"10.1109/ICNS50378.2020.9222891","DOIUrl":"https://doi.org/10.1109/ICNS50378.2020.9222891","url":null,"abstract":"The hemispherical rules require that eastbound flights should use odd thousands flight levels (FLs) and westbound flights should use even thousands FLs. Though these rules improve safety, they could also negatively impact flight efficiency by, for example, reducing the available FLs that can be used to improve efficiency. With improved surveillance and communication capabilities in oceanic airspace, it is possible to use the FLs that do not comply with the hemispherical rules (non-complying FLs). The paper investigates whether doing so in the Pacific airspace could bring benefits to airlines and air traffic controllers. Our analysis showed mixed results. We found that fuel savings would increase as more flights accept non-complying FLs. If all flights accept non-complying FLs, the annual total fuel savings could reach 12.2 million gallons within the Oakland and Anchorage Flight Information Region (FIR). Depending on the price of Jet-A fuel, the monetary value of these fuel savings ranges from 11.25 to 25.66 million dollars. However, we also found that the annual total travel time inside the two FIRs would increase by about 2,070 flight hours. In addition, the workload of air traffic controllers and pilots may also increase as more flights accept non-complying FLs.","PeriodicalId":424869,"journal":{"name":"2020 Integrated Communications Navigation and Surveillance Conference (ICNS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133781032","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}
Pub Date : 2020-09-01DOI: 10.1109/ICNS50378.2020.9223004
Yutong Chen, Lei Yang, Haoran Zhang, Zheng Zhao, Minghua Hu
Aiming at achieving the autonomous Air Traffic Management (ATM) in the Trajectory-Based Operation (TBO) context, a two-stage real-time autonomous four-dimensional trajectory conflict detection and resolution method in restricted Free Route Airspace (FRA) supporting the synchronized air-ground situational awareness was proposed. Cellular concept was used for airspace discretization to balance the accuracy and computation cost. At stage one, the desired trajectory for each upcoming flight is generated by searching a path in a network constructed based on the entry and exit point, as well as boundary points of each restricted area inside the airspace. At stage two, in order to avoid conflict during travelling, the Space-Time Prism model, which is capable of visualizing the conflict situation for both controllers and pilots, is introduced to generate the feasible conflict-free trajectories while keeping the Controlled Time of Arrival (CTA) in mind. A case study based on a typical en route sector in Western China was carried out to test the effectiveness of the proposed method. In the end, sensitivity of cell size was investigated in terms of computational cost and operational efficiency. Results showed that the proposed autonomous trajectory planning would be a promising solution for future autonomous ATM system.
{"title":"Real-Time Autonomous Trajectory Conflict Detection and Resolution in Restricted Airspace","authors":"Yutong Chen, Lei Yang, Haoran Zhang, Zheng Zhao, Minghua Hu","doi":"10.1109/ICNS50378.2020.9223004","DOIUrl":"https://doi.org/10.1109/ICNS50378.2020.9223004","url":null,"abstract":"Aiming at achieving the autonomous Air Traffic Management (ATM) in the Trajectory-Based Operation (TBO) context, a two-stage real-time autonomous four-dimensional trajectory conflict detection and resolution method in restricted Free Route Airspace (FRA) supporting the synchronized air-ground situational awareness was proposed. Cellular concept was used for airspace discretization to balance the accuracy and computation cost. At stage one, the desired trajectory for each upcoming flight is generated by searching a path in a network constructed based on the entry and exit point, as well as boundary points of each restricted area inside the airspace. At stage two, in order to avoid conflict during travelling, the Space-Time Prism model, which is capable of visualizing the conflict situation for both controllers and pilots, is introduced to generate the feasible conflict-free trajectories while keeping the Controlled Time of Arrival (CTA) in mind. A case study based on a typical en route sector in Western China was carried out to test the effectiveness of the proposed method. In the end, sensitivity of cell size was investigated in terms of computational cost and operational efficiency. Results showed that the proposed autonomous trajectory planning would be a promising solution for future autonomous ATM system.","PeriodicalId":424869,"journal":{"name":"2020 Integrated Communications Navigation and Surveillance Conference (ICNS)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133479070","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}
Pub Date : 2020-09-01DOI: 10.1109/ICNS50378.2020.9222886
E. Theunissen, W. Zijlstra
Minimum Detect and avoid Well Clear (DWC) guidance provides the pilot with information on the directions in which DWC is predicted to be lost and how soon. Different guidance algorithms are analyzed for their ability to provide guidance after DWC is lost. Command and status-based concepts for guidance to regain-DWC in case the loss was not prevented are compared from a conceptual, regulatory and performance perspective. The guidance decisions and associated performance are analyzed using TCPA-DCPA traces and guidance band time-histories. Based on the results, recommendations are provided.
{"title":"Comparing Regain Well Clear Guidance","authors":"E. Theunissen, W. Zijlstra","doi":"10.1109/ICNS50378.2020.9222886","DOIUrl":"https://doi.org/10.1109/ICNS50378.2020.9222886","url":null,"abstract":"Minimum Detect and avoid Well Clear (DWC) guidance provides the pilot with information on the directions in which DWC is predicted to be lost and how soon. Different guidance algorithms are analyzed for their ability to provide guidance after DWC is lost. Command and status-based concepts for guidance to regain-DWC in case the loss was not prevented are compared from a conceptual, regulatory and performance perspective. The guidance decisions and associated performance are analyzed using TCPA-DCPA traces and guidance band time-histories. Based on the results, recommendations are provided.","PeriodicalId":424869,"journal":{"name":"2020 Integrated Communications Navigation and Surveillance Conference (ICNS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114942714","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}
Pub Date : 2020-09-01DOI: 10.1109/ICNS50378.2020.9222863
Jungmin Seo, A. Izadi, A. Trani
The Federal Aviation Administration (FAA) Weather Technology in the Cockpit (WTIC) program has sponsored an operational demonstration to provide satellite-based meteorological information to commercial flights in remote and oceanic regions. This effort is called the Remote Oceanic Meteorology Information Operational (ROMIO) demonstration. For this effort, the National Center of Atmospheric Research (NCAR) developed two weather products: 1) Cloud Top Height (CTH), and 2) Convection Diagnosis Oceanic (CDO). The CTH product displays cloud top contours at flight altitudes of FL320, FL340, FL360, FL380, and FL400. The CDO product displays hazards associated with the storm updraft, lightning, and overshooting tops in four intensity levels (medium, high, severe, and extreme).In this paper, we study the potential benefits of the ROMIO demonstration through survey analysis to measure pilots’ acceptance and the ROMIO-aided behavior during en-route convective weather avoidance. We created a post-flight pilot survey to have a qualitative measure of the benefits of using the ROMIO application and to assess users' acceptance of the new airborne information technology. The questions in the questionnaire were mainly categorized into five groups: 1) decision-making, 2) workload, 3) situational awareness, 4) efficiency, and 5) quality of information. We applied Wilcoxon’s rank-sum test to analyze Likert scale responses. The study includes 105 pilot survey responses. The results of this study improve our understanding of the potential benefits of new airborne weather information technology from the pilots’ perspective and allow us to identify potential areas for further improvement of the ROMIO demonstration.
{"title":"Operational Benefits of Remote Oceanic Meteorology Information Operational (Romio) Demonstration: A Survey-Based Analysis","authors":"Jungmin Seo, A. Izadi, A. Trani","doi":"10.1109/ICNS50378.2020.9222863","DOIUrl":"https://doi.org/10.1109/ICNS50378.2020.9222863","url":null,"abstract":"The Federal Aviation Administration (FAA) Weather Technology in the Cockpit (WTIC) program has sponsored an operational demonstration to provide satellite-based meteorological information to commercial flights in remote and oceanic regions. This effort is called the Remote Oceanic Meteorology Information Operational (ROMIO) demonstration. For this effort, the National Center of Atmospheric Research (NCAR) developed two weather products: 1) Cloud Top Height (CTH), and 2) Convection Diagnosis Oceanic (CDO). The CTH product displays cloud top contours at flight altitudes of FL320, FL340, FL360, FL380, and FL400. The CDO product displays hazards associated with the storm updraft, lightning, and overshooting tops in four intensity levels (medium, high, severe, and extreme).In this paper, we study the potential benefits of the ROMIO demonstration through survey analysis to measure pilots’ acceptance and the ROMIO-aided behavior during en-route convective weather avoidance. We created a post-flight pilot survey to have a qualitative measure of the benefits of using the ROMIO application and to assess users' acceptance of the new airborne information technology. The questions in the questionnaire were mainly categorized into five groups: 1) decision-making, 2) workload, 3) situational awareness, 4) efficiency, and 5) quality of information. We applied Wilcoxon’s rank-sum test to analyze Likert scale responses. The study includes 105 pilot survey responses. The results of this study improve our understanding of the potential benefits of new airborne weather information technology from the pilots’ perspective and allow us to identify potential areas for further improvement of the ROMIO demonstration.","PeriodicalId":424869,"journal":{"name":"2020 Integrated Communications Navigation and Surveillance Conference (ICNS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121149639","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}
Pub Date : 2020-09-01DOI: 10.1109/ICNS50378.2020.9222944
A. Young, David Luong, B. Balaji, S. Rajan
The detection and parametric estimation of low-SNR radar signals, particularly linear frequency modulated (LFM) radar signals, is a problem of considerable interest. In prior work, this problem has been investigated using various signal processing techniques, such as maximum likelihood estimation, fractional Fourier transform and Wigner-Ville-based methods, to analyze the signal parameters of a complex linear frequency modulated signal. Other work has focused on applying deep learning to automatically recognize various radar waveform types and their features, such as linear frequency modulation (LFM), Barker code and rectangular waveforms. In this paper, we investigate this problem from a machine learning perspective for multiple LFM radar signals given a priori information. We explore the use of naive Bayes, support vector machine and neural network classifiers to identify the LFM chirp rate, out of a set of known chirp rates, from a specific radar emitter under varying SNR conditions. Simulation results demonstrate the viability of this technique to identify the radar LFM mode in very low signal-to-noise ratio conditions down to -20 dB where using existing approaches (e.g., Wigner-Ville) fail.
{"title":"Machine Learning Approach to Chirp Rate Estimation of Linear Frequency Modulated Radars","authors":"A. Young, David Luong, B. Balaji, S. Rajan","doi":"10.1109/ICNS50378.2020.9222944","DOIUrl":"https://doi.org/10.1109/ICNS50378.2020.9222944","url":null,"abstract":"The detection and parametric estimation of low-SNR radar signals, particularly linear frequency modulated (LFM) radar signals, is a problem of considerable interest. In prior work, this problem has been investigated using various signal processing techniques, such as maximum likelihood estimation, fractional Fourier transform and Wigner-Ville-based methods, to analyze the signal parameters of a complex linear frequency modulated signal. Other work has focused on applying deep learning to automatically recognize various radar waveform types and their features, such as linear frequency modulation (LFM), Barker code and rectangular waveforms. In this paper, we investigate this problem from a machine learning perspective for multiple LFM radar signals given a priori information. We explore the use of naive Bayes, support vector machine and neural network classifiers to identify the LFM chirp rate, out of a set of known chirp rates, from a specific radar emitter under varying SNR conditions. Simulation results demonstrate the viability of this technique to identify the radar LFM mode in very low signal-to-noise ratio conditions down to -20 dB where using existing approaches (e.g., Wigner-Ville) fail.","PeriodicalId":424869,"journal":{"name":"2020 Integrated Communications Navigation and Surveillance Conference (ICNS)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134030182","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}
Pub Date : 2020-09-01DOI: 10.1109/ICNS50378.2020.9222908
James Keller, B. Deng, David Gore
Effective surveillance of non-cooperative targets is necessary to enable Beyond Visual Line of Sight (BVLOS) flights for small Unmanned Aerial Systems (sUAS). We examine several approaches to develop effective surveillance for non-cooperative targets within the typical sUAS operations arena (low altitude, Class G airspace), to determine suitability for situational awareness and Detect and Avoid (DAA). This ongoing research includes analysis of sensor performance and determination of applicability to the sUAS mission. Effective surveillance for cooperative manned targets is easier to achieve using ADS-B; however, there is no current solution for cooperatively tracking sUAS, which have been restricted from using ADS-B. Until Remote ID is available, surveillance of UAS must be performed through non-cooperative means. While the safety focus is on situational awareness and DAA for manned aircraft, we also consider UAS non-cooperative surveillance as part of the study. We provide initial conclusions and outline a path for additional research.
{"title":"Effective Non-Cooperative Surveillance for UAS Situational Awareness","authors":"James Keller, B. Deng, David Gore","doi":"10.1109/ICNS50378.2020.9222908","DOIUrl":"https://doi.org/10.1109/ICNS50378.2020.9222908","url":null,"abstract":"Effective surveillance of non-cooperative targets is necessary to enable Beyond Visual Line of Sight (BVLOS) flights for small Unmanned Aerial Systems (sUAS). We examine several approaches to develop effective surveillance for non-cooperative targets within the typical sUAS operations arena (low altitude, Class G airspace), to determine suitability for situational awareness and Detect and Avoid (DAA). This ongoing research includes analysis of sensor performance and determination of applicability to the sUAS mission. Effective surveillance for cooperative manned targets is easier to achieve using ADS-B; however, there is no current solution for cooperatively tracking sUAS, which have been restricted from using ADS-B. Until Remote ID is available, surveillance of UAS must be performed through non-cooperative means. While the safety focus is on situational awareness and DAA for manned aircraft, we also consider UAS non-cooperative surveillance as part of the study. We provide initial conclusions and outline a path for additional research.","PeriodicalId":424869,"journal":{"name":"2020 Integrated Communications Navigation and Surveillance Conference (ICNS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131950068","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}
Pub Date : 2020-09-01DOI: 10.1109/ICNS50378.2020.9222959
R. Christien, K. Zeghal, E. Hoffman
This paper presents initial investigations on the prediction of conflict free aircraft trajectories using supervised machine learning. The motivation is to generate trajectory proposals to resolve conflicts based on current practices (imitation learning) as a way to get controller acceptability. The paper explores two distinct approaches. The first one takes a pilot point of view with a flight centred representation of the surrounding traffic, while the second one takes a controller point of view with a sector-based representation of the traffic. In addition, for the first approach, the traffic input is represented by an image going into a convolutional neural network, while in the second it is represented by a list of flights parameters going into a feed forward neural network.The case study addressed is to predict conflict free trajectories with a 5 minutes look-ahead. It relies on recorded traffic data from 2018 from a busy European en-route centre (Maastricht UAC) used to draw a 250k data set. This dataset was split in two 50% sub-sets: one with no change in vertical and/or horizontal dimension, the other with a change (change thresholds of 1000ft and 2NM determined statistically). The performance of both models is compared to a baseline to ensure a learning has been achieved. For the best model (sector based), the median deviations between the prediction and the true future locations are 0.4NM and 23ft "with no change", and 1.3NM and 500ft "with change". These results show that relevant information has been extracted and a mapping between inputs and outputs achieved. However, the prediction error remains quite significant compared to separation standards (5NM, 1000ft).Future work will investigate further both models, in particular analyze error (focus on bad performance cases patterns) and improving them, and later, adding other information (e.g. military areas, meteo).
{"title":"Predicting Conflict Free Trajectories Using Supervised Machine Learning, Initial Investigations","authors":"R. Christien, K. Zeghal, E. Hoffman","doi":"10.1109/ICNS50378.2020.9222959","DOIUrl":"https://doi.org/10.1109/ICNS50378.2020.9222959","url":null,"abstract":"This paper presents initial investigations on the prediction of conflict free aircraft trajectories using supervised machine learning. The motivation is to generate trajectory proposals to resolve conflicts based on current practices (imitation learning) as a way to get controller acceptability. The paper explores two distinct approaches. The first one takes a pilot point of view with a flight centred representation of the surrounding traffic, while the second one takes a controller point of view with a sector-based representation of the traffic. In addition, for the first approach, the traffic input is represented by an image going into a convolutional neural network, while in the second it is represented by a list of flights parameters going into a feed forward neural network.The case study addressed is to predict conflict free trajectories with a 5 minutes look-ahead. It relies on recorded traffic data from 2018 from a busy European en-route centre (Maastricht UAC) used to draw a 250k data set. This dataset was split in two 50% sub-sets: one with no change in vertical and/or horizontal dimension, the other with a change (change thresholds of 1000ft and 2NM determined statistically). The performance of both models is compared to a baseline to ensure a learning has been achieved. For the best model (sector based), the median deviations between the prediction and the true future locations are 0.4NM and 23ft \"with no change\", and 1.3NM and 500ft \"with change\". These results show that relevant information has been extracted and a mapping between inputs and outputs achieved. However, the prediction error remains quite significant compared to separation standards (5NM, 1000ft).Future work will investigate further both models, in particular analyze error (focus on bad performance cases patterns) and improving them, and later, adding other information (e.g. military areas, meteo).","PeriodicalId":424869,"journal":{"name":"2020 Integrated Communications Navigation and Surveillance Conference (ICNS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123899944","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}
Pub Date : 2020-09-01DOI: 10.1109/ICNS50378.2020.9222872
Brandon J. Daniel, Anuja Verma
The capability to properly assess the risks associated with the integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) is critical to ensuring UAS operations are introduced in a safe and responsible manner. Key to this capability is the accurate determination of the likelihood of collision between UAS and other aircraft. Likelihood of such collisions are not well understood and, in many cases, are assessed in a subjective and qualitative manner, resulting in potentially inaccurate assumptions and evaluation of risk and/or allocation of limiting mitigations that decrease the efficiency and effectiveness of UAS operations. Quantification of the likelihood of these collision risk elements will transform the way UAS integration is evaluated and approvedThis paper focuses on a methodology to quantify and analyze the likelihood of unmitigated aircraft collisions within defined airspace volumes. This methodology, developed by The MITRE Corporation (MITRE), will enable a more objective, standardized, and comprehensive assessment of the collision risk posed by the integration of UAS into the NAS with the ability to statistically assess the differences between distributions of risk across multiple airspace volumes. Leveraging this methodology will speed the determination of airspace risk associated with integration and will specifically assist in the identification of mitigations to reduce identified risk to an acceptable level.
{"title":"Likelihood of Unmitigated Collision Risks for Uas in Defined Airspace Volumes","authors":"Brandon J. Daniel, Anuja Verma","doi":"10.1109/ICNS50378.2020.9222872","DOIUrl":"https://doi.org/10.1109/ICNS50378.2020.9222872","url":null,"abstract":"The capability to properly assess the risks associated with the integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) is critical to ensuring UAS operations are introduced in a safe and responsible manner. Key to this capability is the accurate determination of the likelihood of collision between UAS and other aircraft. Likelihood of such collisions are not well understood and, in many cases, are assessed in a subjective and qualitative manner, resulting in potentially inaccurate assumptions and evaluation of risk and/or allocation of limiting mitigations that decrease the efficiency and effectiveness of UAS operations. Quantification of the likelihood of these collision risk elements will transform the way UAS integration is evaluated and approvedThis paper focuses on a methodology to quantify and analyze the likelihood of unmitigated aircraft collisions within defined airspace volumes. This methodology, developed by The MITRE Corporation (MITRE), will enable a more objective, standardized, and comprehensive assessment of the collision risk posed by the integration of UAS into the NAS with the ability to statistically assess the differences between distributions of risk across multiple airspace volumes. Leveraging this methodology will speed the determination of airspace risk associated with integration and will specifically assist in the identification of mitigations to reduce identified risk to an acceptable level.","PeriodicalId":424869,"journal":{"name":"2020 Integrated Communications Navigation and Surveillance Conference (ICNS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114524557","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}
Pub Date : 2020-09-01DOI: 10.1109/ICNS50378.2020.9222969
Kailin Chen, Shaoyu Wang, Jianfeng Mao
In this paper, we consider predicting travel time for aircraft operated in multi-airport systems by modeling and simulating a multiclass queuing network, which can systematically capture the complicated coupling relationship among multiple airports and terminal airspace and the complex nature of flight trajectories following different traffic flow patterns. In this multiclass queuing network model, each class of queuing network, named a class of customers, is modeled with the data of a traffic flow pattern, which is identified for a cluster of flight trajectories. Airports and airspace sectors are correspondingly modeled as networked servers with nonhomogeneous and time-varying arrival rate, service rate and server capacity to serve those classes of customers following their specific routing probabilities. Then, all of the parameters for setting up the multiclass queuing network model can be properly estimated using historical 4D flight trajectory data. To illustrate the superiority of this model, both average travel time for each class of customers, i.e., aircraft following a particular flow pattern, and the arrival time for an individual flight are predicted via simulations of a multiclass queuing network, and furthermore, compared with the real travel time. A typical example of a multi-airport system, the Guangdong-Hong Kong-Macau Greater Bay Area in China, is utilized to showcase the prediction performance of the proposed multiclass queuing network simulation model. The simulation experiments of the case study demonstrate that the proposed model well fits this multi-airports system. For most of the time periods, the percentage error (PE) of simulated average travel time and real average travel time is less than 5%. The travel time prediction for a random individual flight can achieve around 1% of the percentage error in terms of point estimation.
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