Pub Date : 2017-09-01DOI: 10.1109/DASC.2017.8102112
L. Schalk, M. Herrmann
The increasing availability of cheap and powerful drones for various applications is likely to cause a heavy usage of the very low level airspace in metropolitan areas with hundreds of simultaneously airborne drones per square kilometer in the near future. Certainly, the predicted large number of drones presents a major challenge to future UTM and especially to supporting communications systems. However, a robust and reliable communications system for drone-to-infrastructure communications is inevitably needed to grant all drones access to various services provided by UTM. In previous works, it has already been shown that commercial LTE networks are capable of providing connectivity to drones flying at low altitudes in principle. However, airborne drones which transmit data to the UTM infrastructure produce severe inter-cell interference since they have a strong line-of-sight connection to multiple LTE base stations at a time. Hence, we investigate further the suitability of the LTE uplink for drone-to-infrastructure communications in very low level airspace by LTE system-level simulations in this work. In particular, we identify the maximum drone density that can be thoroughly monitored and safely coordinated by a UTM system with LTE communication links. Our simulations show that an LTE system with 5 Mhz uplink bandwidth can support a message delivery ratio of more than 95% for drone densities of up to 200 drones per square kilometer assuming that all drones have to periodically transmit messages of 300 bytes at a rate of 10 Hz. It is concluded that future research has to focus on the mitigation of inter-cell interference so even a larger number of drones can get reliable access to all UTM services.
{"title":"Suitability of LTE for drone-to-infrastructure communications in very low level airspace","authors":"L. Schalk, M. Herrmann","doi":"10.1109/DASC.2017.8102112","DOIUrl":"https://doi.org/10.1109/DASC.2017.8102112","url":null,"abstract":"The increasing availability of cheap and powerful drones for various applications is likely to cause a heavy usage of the very low level airspace in metropolitan areas with hundreds of simultaneously airborne drones per square kilometer in the near future. Certainly, the predicted large number of drones presents a major challenge to future UTM and especially to supporting communications systems. However, a robust and reliable communications system for drone-to-infrastructure communications is inevitably needed to grant all drones access to various services provided by UTM. In previous works, it has already been shown that commercial LTE networks are capable of providing connectivity to drones flying at low altitudes in principle. However, airborne drones which transmit data to the UTM infrastructure produce severe inter-cell interference since they have a strong line-of-sight connection to multiple LTE base stations at a time. Hence, we investigate further the suitability of the LTE uplink for drone-to-infrastructure communications in very low level airspace by LTE system-level simulations in this work. In particular, we identify the maximum drone density that can be thoroughly monitored and safely coordinated by a UTM system with LTE communication links. Our simulations show that an LTE system with 5 Mhz uplink bandwidth can support a message delivery ratio of more than 95% for drone densities of up to 200 drones per square kilometer assuming that all drones have to periodically transmit messages of 300 bytes at a rate of 10 Hz. It is concluded that future research has to focus on the mitigation of inter-cell interference so even a larger number of drones can get reliable access to all UTM services.","PeriodicalId":130890,"journal":{"name":"2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129712619","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 : 2017-09-01DOI: 10.1109/DASC.2017.8102003
Paul Berthier, José M. Fernandez, Jean-Marc Robert
Automated Dependent Surveillance — Broadcast (ADS-B) is an aircraft surveillance technology introduced as part of the US Next-Generation Air Transportation System (NextGen) initiative, in which aircraft broadcast their position based on satellite navigation (e.g. GPS). This information can then be used by other aircraft for traffic awareness and collision avoidance (TCAS), and by ground personnel to provide air traffic control (ATC) services. Unfortunately, ADS-B presents important security problems, since there are no integral mechanisms for message authentication nor message integrity verification. In this paper, we propose SAT, a secure, backward-compatible replacement for ADS-B. SAT uses the TESLA broadcast authentication protocol, a hybrid solution that combines the advantages of symmetric cryptography (low use of bandwidth) with those of asymmetric cryptography (no shared keys). Our proposal adapts the TESLA constructs in order to make it suitable for use in ATC and collision avoidance. In particular, we replace the synchronization mechanism of TESLA with the use of satellite time, thus making the implementation more lightweight. We also use a public key infrastructure based on the air traffic control hierarchy (including national civil aviation authorities and potentially ICAO), in order to allow for SAT to be used not only for aircraft authentication but also for aircraft flight authorization. We implemented the SAT protocol on SDR and performed laboratory experiments in order to measure computation and transmission overheads, and to determine the shortest authentication delay we could achieve. In particular, we explored the trade-off between interval duration and bandwidth use. Finally, we tested our new protocol on SDR.
{"title":"SAT : Security in the air using Tesla","authors":"Paul Berthier, José M. Fernandez, Jean-Marc Robert","doi":"10.1109/DASC.2017.8102003","DOIUrl":"https://doi.org/10.1109/DASC.2017.8102003","url":null,"abstract":"Automated Dependent Surveillance — Broadcast (ADS-B) is an aircraft surveillance technology introduced as part of the US Next-Generation Air Transportation System (NextGen) initiative, in which aircraft broadcast their position based on satellite navigation (e.g. GPS). This information can then be used by other aircraft for traffic awareness and collision avoidance (TCAS), and by ground personnel to provide air traffic control (ATC) services. Unfortunately, ADS-B presents important security problems, since there are no integral mechanisms for message authentication nor message integrity verification. In this paper, we propose SAT, a secure, backward-compatible replacement for ADS-B. SAT uses the TESLA broadcast authentication protocol, a hybrid solution that combines the advantages of symmetric cryptography (low use of bandwidth) with those of asymmetric cryptography (no shared keys). Our proposal adapts the TESLA constructs in order to make it suitable for use in ATC and collision avoidance. In particular, we replace the synchronization mechanism of TESLA with the use of satellite time, thus making the implementation more lightweight. We also use a public key infrastructure based on the air traffic control hierarchy (including national civil aviation authorities and potentially ICAO), in order to allow for SAT to be used not only for aircraft authentication but also for aircraft flight authorization. We implemented the SAT protocol on SDR and performed laboratory experiments in order to measure computation and transmission overheads, and to determine the shortest authentication delay we could achieve. In particular, we explored the trade-off between interval duration and bandwidth use. Finally, we tested our new protocol on SDR.","PeriodicalId":130890,"journal":{"name":"2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121549601","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 : 2017-09-01DOI: 10.1109/DASC.2017.8102120
M. Waheed, Michael Cheng
The expanding global data communication infrastructures, data networking technologies and wide use of mobile computing devices is having commercial aircraft designs to include external connectivity. The external connectivity facilitates aircraft maintenance activities and allows airlines to provide internet access to passengers, but also makes the aircraft vulnerable to cybersecurity attacks. Cyber security attacks on an aircraft could impact the safety-of-flight systems and/or the systems supporting the business of the airlines. Proposed industry standards require logging security event failures that are to be managed as part of the maintenance activities [1]. This paper describes a simple configurable system to collect, monitor and report security event failures on an aircraft in real time to help detect and/or prevent cyber security attacks.
{"title":"A system for real-time monitoring of cybersecurity events on aircraft","authors":"M. Waheed, Michael Cheng","doi":"10.1109/DASC.2017.8102120","DOIUrl":"https://doi.org/10.1109/DASC.2017.8102120","url":null,"abstract":"The expanding global data communication infrastructures, data networking technologies and wide use of mobile computing devices is having commercial aircraft designs to include external connectivity. The external connectivity facilitates aircraft maintenance activities and allows airlines to provide internet access to passengers, but also makes the aircraft vulnerable to cybersecurity attacks. Cyber security attacks on an aircraft could impact the safety-of-flight systems and/or the systems supporting the business of the airlines. Proposed industry standards require logging security event failures that are to be managed as part of the maintenance activities [1]. This paper describes a simple configurable system to collect, monitor and report security event failures on an aircraft in real time to help detect and/or prevent cyber security attacks.","PeriodicalId":130890,"journal":{"name":"2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127714566","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 : 2017-09-01DOI: 10.1109/DASC.2017.8102091
David W. Miller
The National Airspace System (NAS) is a highly complex system-of-systems evolving at an incremental rate. NASA has an interest in ab initio airspace system architectures that leapfrog today's evolutionary constraints enabling airspace operations of the future — 2035 and beyond. A clean-sheet approach to designing a future Airspace System leads to a myriad of possible architectures. Common concepts exist across all future alternatives. For example, each architecture must contain aircraft, aerodromes (both large and small), and airspace. The common concepts are captured in an ontology for a future Airspace System. The Airspace System ontology is composed of a collection of entities, properties and relationships representing the key system concepts. It separates the domain knowledge from the operational, thus enabling the development of architectural variations derived from a common language and understanding of the Airspace System.
{"title":"An ontology for future airspace system architectures","authors":"David W. Miller","doi":"10.1109/DASC.2017.8102091","DOIUrl":"https://doi.org/10.1109/DASC.2017.8102091","url":null,"abstract":"The National Airspace System (NAS) is a highly complex system-of-systems evolving at an incremental rate. NASA has an interest in ab initio airspace system architectures that leapfrog today's evolutionary constraints enabling airspace operations of the future — 2035 and beyond. A clean-sheet approach to designing a future Airspace System leads to a myriad of possible architectures. Common concepts exist across all future alternatives. For example, each architecture must contain aircraft, aerodromes (both large and small), and airspace. The common concepts are captured in an ontology for a future Airspace System. The Airspace System ontology is composed of a collection of entities, properties and relationships representing the key system concepts. It separates the domain knowledge from the operational, thus enabling the development of architectural variations derived from a common language and understanding of the Airspace System.","PeriodicalId":130890,"journal":{"name":"2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126352871","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 : 2017-09-01DOI: 10.1109/DASC.2017.8102049
Mevlut Uzun, Barış Başpınar, E. Koyuncu, G. Inalhan
The increasing demand in the air transportation has been bringing about increased workload to air traffic controllers. Reducing the workload, hence increasing the airspace capacity could be enabled by developing automated air traffic management tools. Our previous work presented a new hybrid system description, namely automated AT Co, modeling the decision process of the air traffic controllers in en-route and approach operations. The developed tool also considers enhanced air traffic and aircraft dynamics. The hybrid system provides realistic conflict resolution maneuvers in 3D space in reasonable computation times. The trajectory prediction infrastructure behind the developed tool accepts mainly flight plans and aircraft performance variables (i.e. initial conditions, performance model) as inputs to yield trajectories. However, some aircraft specific parameters are not exactly known for ground based systems. These can be described as random variables. This phenomena results in uncertainties in trajectory prediction. In this paper, trajectory predictions during climb phase are improved through model driven state estimation. The algorithm uses observed track of an aircraft obtained from a period of time and recovers the take-off mass error considering the conservation of energy rates. It is shown that trajectories are improved in both in time and spatial terms compared to predictions with nominal states.
{"title":"Takeoff weight error recovery for tactical trajectory prediction automaton of air traffic control operator","authors":"Mevlut Uzun, Barış Başpınar, E. Koyuncu, G. Inalhan","doi":"10.1109/DASC.2017.8102049","DOIUrl":"https://doi.org/10.1109/DASC.2017.8102049","url":null,"abstract":"The increasing demand in the air transportation has been bringing about increased workload to air traffic controllers. Reducing the workload, hence increasing the airspace capacity could be enabled by developing automated air traffic management tools. Our previous work presented a new hybrid system description, namely automated AT Co, modeling the decision process of the air traffic controllers in en-route and approach operations. The developed tool also considers enhanced air traffic and aircraft dynamics. The hybrid system provides realistic conflict resolution maneuvers in 3D space in reasonable computation times. The trajectory prediction infrastructure behind the developed tool accepts mainly flight plans and aircraft performance variables (i.e. initial conditions, performance model) as inputs to yield trajectories. However, some aircraft specific parameters are not exactly known for ground based systems. These can be described as random variables. This phenomena results in uncertainties in trajectory prediction. In this paper, trajectory predictions during climb phase are improved through model driven state estimation. The algorithm uses observed track of an aircraft obtained from a period of time and recovers the take-off mass error considering the conservation of energy rates. It is shown that trajectories are improved in both in time and spatial terms compared to predictions with nominal states.","PeriodicalId":130890,"journal":{"name":"2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130058138","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 : 2017-09-01DOI: 10.1109/dasc.2017.8102132
Ramon Dalmau, M. Pérez-Batlle, X. Prats
State-of-the-art weather data obtained from numerical weather predictions are unlikely to satisfy the requirements of the future air traffic management system. A potential approach to improve the resolution and accuracy of the weather predictions could consist on using airborne aircraft as meteorological sensors, which would provide up-to-date weather observations to the surrounding aircraft and ground systems. This paper proposes to use Kriging, a geostatistical interpolation technique, to create short-term weather predictions from scattered weather observations derived from surveillance data. Results show that this method can accurately capture the spatio-temporal distribution of the temperature and wind fields, allowing to obtain high-quality local, short-term weather predictions and providing at the same time a measure of the uncertainty associated with the prediction.
{"title":"Estimation and prediction of weather variables from surveillance data using spatio-temporal Kriging","authors":"Ramon Dalmau, M. Pérez-Batlle, X. Prats","doi":"10.1109/dasc.2017.8102132","DOIUrl":"https://doi.org/10.1109/dasc.2017.8102132","url":null,"abstract":"State-of-the-art weather data obtained from numerical weather predictions are unlikely to satisfy the requirements of the future air traffic management system. A potential approach to improve the resolution and accuracy of the weather predictions could consist on using airborne aircraft as meteorological sensors, which would provide up-to-date weather observations to the surrounding aircraft and ground systems. This paper proposes to use Kriging, a geostatistical interpolation technique, to create short-term weather predictions from scattered weather observations derived from surveillance data. Results show that this method can accurately capture the spatio-temporal distribution of the temperature and wind fields, allowing to obtain high-quality local, short-term weather predictions and providing at the same time a measure of the uncertainty associated with the prediction.","PeriodicalId":130890,"journal":{"name":"2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)","volume":"270 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133934074","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 : 2017-09-01DOI: 10.1109/DASC.2017.8102098
D. Kulkarni
Recently, the ATM community has made important progress in collaborative trajectory management through the introduction of a new FAA traffic management initiative called a Collaborative Trajectory Options Program (CTOP). FAA can use CTOPs to manage air traffic under multiple constraints (manifested as flow constrained areas or FCAs) in the system, and it allows flight operators to indicate their preferences for routing and delay options. CTOPs also permit better management of the overall trajectory of flights by considering both routing and departure delay options simultaneously. However, adoption of CTOPs in airspace has been hampered by many factors that include challenges in how to identify constrained areas and how to set rates for the FCAs. Decision support tools (DST) providing assistance would be particularly helpful in effective use of CTOPs. Such tools would need models of demand and capacity in the presence of multiple constraints. This study examines different approaches to using historical data to create and validate models of aircraft counts in sectors and other airspace regions in the presence of multiple constraints. A challenge in creating an empirical model of aircraft counts under multiple constraints is a lack of sufficient historical data that captures diverse situations involving combinations of multiple constraints especially those with severe weather. The approach taken here to deal with this is two-fold. First, we create a generalized sector model encompassing multiple sectors rather than individual sectors in order to increase the amount of data used for creating the model by an order of magnitude. Secondly, we decompose the problem so that the amount of data needed is reduced. This involves creating a baseline demand model plus a separate weather constrained sector count reduction model and then composing these into a single integrated model. A nominal demand model is a sector aircraft count model (gdem) in the presence of clear local weather. This defines the flow as a function of weather constraints in neighboring regions, airport constraints and weather in locations that can cause re-routes to a location of interest. A weather constrained flow reduction model (fwx-red) is a model of reduction in baseline counts as a function of local weather. Because the number of independent variables associated with each of the two decomposed models is smaller than that with a single model, need for amount of data is reduced. Finally, a composite model that combines these two can be represented as fwx-red (gdem(e), l) where e represents non-local constraints and l represents local weather. The approaches studied to developing these models are divided into three categories: (1) Point estimation models (2) Empirical models (3) Theoretical models. Errors in predictions of these different types of models have been estimated. In situations when there is abundant data, point estimation models tend to be very accurate. Also, empirical mode
{"title":"Models of maximum flows in airspace sectors in the presence of multiple constraints","authors":"D. Kulkarni","doi":"10.1109/DASC.2017.8102098","DOIUrl":"https://doi.org/10.1109/DASC.2017.8102098","url":null,"abstract":"Recently, the ATM community has made important progress in collaborative trajectory management through the introduction of a new FAA traffic management initiative called a Collaborative Trajectory Options Program (CTOP). FAA can use CTOPs to manage air traffic under multiple constraints (manifested as flow constrained areas or FCAs) in the system, and it allows flight operators to indicate their preferences for routing and delay options. CTOPs also permit better management of the overall trajectory of flights by considering both routing and departure delay options simultaneously. However, adoption of CTOPs in airspace has been hampered by many factors that include challenges in how to identify constrained areas and how to set rates for the FCAs. Decision support tools (DST) providing assistance would be particularly helpful in effective use of CTOPs. Such tools would need models of demand and capacity in the presence of multiple constraints. This study examines different approaches to using historical data to create and validate models of aircraft counts in sectors and other airspace regions in the presence of multiple constraints. A challenge in creating an empirical model of aircraft counts under multiple constraints is a lack of sufficient historical data that captures diverse situations involving combinations of multiple constraints especially those with severe weather. The approach taken here to deal with this is two-fold. First, we create a generalized sector model encompassing multiple sectors rather than individual sectors in order to increase the amount of data used for creating the model by an order of magnitude. Secondly, we decompose the problem so that the amount of data needed is reduced. This involves creating a baseline demand model plus a separate weather constrained sector count reduction model and then composing these into a single integrated model. A nominal demand model is a sector aircraft count model (gdem) in the presence of clear local weather. This defines the flow as a function of weather constraints in neighboring regions, airport constraints and weather in locations that can cause re-routes to a location of interest. A weather constrained flow reduction model (fwx-red) is a model of reduction in baseline counts as a function of local weather. Because the number of independent variables associated with each of the two decomposed models is smaller than that with a single model, need for amount of data is reduced. Finally, a composite model that combines these two can be represented as fwx-red (gdem(e), l) where e represents non-local constraints and l represents local weather. The approaches studied to developing these models are divided into three categories: (1) Point estimation models (2) Empirical models (3) Theoretical models. Errors in predictions of these different types of models have been estimated. In situations when there is abundant data, point estimation models tend to be very accurate. Also, empirical mode","PeriodicalId":130890,"journal":{"name":"2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133935951","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 : 2017-09-01DOI: 10.1109/DASC.2017.8102093
J. Shortle, Seungwon Noh, L. Sherry
This paper investigates an airspace architecture in which the core requirement is maintaining a target level of collision risk throughout the airspace, accounting for a diversity of aircraft types and a diversity of collision avoidance capabilities in different regions of the airspace. Because collision risk depends on both the density of aircraft and the collision avoidance capabilities of the aircraft involved, aircraft with better collision avoidance capabilities are able to fly in regions of higher density. Conversely, aircraft with lesser collision avoidance capabilities are restricted to less dense airspace or off-peak hours. This paper provides a framework for evaluating the proposed architecture, including a framework for evaluating collision risk based on the numbers and types of aircraft in the airspace and a framework for specifying the corresponding airspace admittance function. Properties of the airspace admittance function are explored and airspace designs are suggested based on the results. In particular, if high-equipped aircraft are not adversely affected by low-equipped aircraft, from a collision avoidance perspective, then the aircraft should fly together in the same airspace to maximize capacity. But otherwise, it may be better to segregate the aircraft types into distinct regions of airspace.
{"title":"Collision risk analysis for alternate airspace architectures","authors":"J. Shortle, Seungwon Noh, L. Sherry","doi":"10.1109/DASC.2017.8102093","DOIUrl":"https://doi.org/10.1109/DASC.2017.8102093","url":null,"abstract":"This paper investigates an airspace architecture in which the core requirement is maintaining a target level of collision risk throughout the airspace, accounting for a diversity of aircraft types and a diversity of collision avoidance capabilities in different regions of the airspace. Because collision risk depends on both the density of aircraft and the collision avoidance capabilities of the aircraft involved, aircraft with better collision avoidance capabilities are able to fly in regions of higher density. Conversely, aircraft with lesser collision avoidance capabilities are restricted to less dense airspace or off-peak hours. This paper provides a framework for evaluating the proposed architecture, including a framework for evaluating collision risk based on the numbers and types of aircraft in the airspace and a framework for specifying the corresponding airspace admittance function. Properties of the airspace admittance function are explored and airspace designs are suggested based on the results. In particular, if high-equipped aircraft are not adversely affected by low-equipped aircraft, from a collision avoidance perspective, then the aircraft should fly together in the same airspace to maximize capacity. But otherwise, it may be better to segregate the aircraft types into distinct regions of airspace.","PeriodicalId":130890,"journal":{"name":"2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)","volume":"66 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131514160","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 : 2017-09-01DOI: 10.1109/DASC.2017.8102075
M. Castillo-Effen, L. Ren, Han Yu, C. Ippolito
An Unmanned Aircraft System (UAS) Traffic Management System (UTM) relies significantly on automation, introducing the need for efficient and accurate trajectory computation to enable coordination and safety. The main objective of this paper is to present and to organize prior work and relevant concepts with the goal of developing a framework for UAS trajectory prediction in the presence of anomalous events. Literature documenting UAS safety and risk assessment has provided multiple pointers for identification and characterization of system failures that cause trajectory deviations or changes to its associated qualities. A UAS trajectory modeling framework considering endogenous and exogenous factors affecting the trajectory is introduced and used in this exposition. In addition, a general formulation of the trajectory computation challenge is presented along with key requirements for potential solution approaches.
{"title":"Off-nominal trajectory computation applied to unmanned aircraft system traffic management","authors":"M. Castillo-Effen, L. Ren, Han Yu, C. Ippolito","doi":"10.1109/DASC.2017.8102075","DOIUrl":"https://doi.org/10.1109/DASC.2017.8102075","url":null,"abstract":"An Unmanned Aircraft System (UAS) Traffic Management System (UTM) relies significantly on automation, introducing the need for efficient and accurate trajectory computation to enable coordination and safety. The main objective of this paper is to present and to organize prior work and relevant concepts with the goal of developing a framework for UAS trajectory prediction in the presence of anomalous events. Literature documenting UAS safety and risk assessment has provided multiple pointers for identification and characterization of system failures that cause trajectory deviations or changes to its associated qualities. A UAS trajectory modeling framework considering endogenous and exogenous factors affecting the trajectory is introduced and used in this exposition. In addition, a general formulation of the trajectory computation challenge is presented along with key requirements for potential solution approaches.","PeriodicalId":130890,"journal":{"name":"2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129376319","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 : 2017-09-01DOI: 10.1109/DASC.2017.8102018
B. Josefsson, Tatiana Polishchuk, V. Polishchuk, Christiane Schmidt
Remote Tower Service (RTS) is one of the technological and operational solutions delivered for deployment by the Single European Sky ATM Research (SESAR) Programme. This new concept fundamentally changes how operators provide Air Traffic Services, as it becomes possible to control several airports from a single remote center. In such settings an air traffic controller works at a so-called “multiple position” at the Remote Tower Center (RTC), which means that he/she can handle two or more airports from one Remote Tower Module (controller working position). In this paper, we present an optimization framework designed for automation of staff planning at the RTC. We highlight the problems experienced with real airport flight schedules, and present optimal shift assignments for five Swedish airports that were chosen for remote operation.
{"title":"Scheduling air traffic controllers at the remote tower center","authors":"B. Josefsson, Tatiana Polishchuk, V. Polishchuk, Christiane Schmidt","doi":"10.1109/DASC.2017.8102018","DOIUrl":"https://doi.org/10.1109/DASC.2017.8102018","url":null,"abstract":"Remote Tower Service (RTS) is one of the technological and operational solutions delivered for deployment by the Single European Sky ATM Research (SESAR) Programme. This new concept fundamentally changes how operators provide Air Traffic Services, as it becomes possible to control several airports from a single remote center. In such settings an air traffic controller works at a so-called “multiple position” at the Remote Tower Center (RTC), which means that he/she can handle two or more airports from one Remote Tower Module (controller working position). In this paper, we present an optimization framework designed for automation of staff planning at the RTC. We highlight the problems experienced with real airport flight schedules, and present optimal shift assignments for five Swedish airports that were chosen for remote operation.","PeriodicalId":130890,"journal":{"name":"2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127431526","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}
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