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Demand for 30/20 GHz satellite systems over the next two decades is projected. Topics include a profile of the communications market, switched, dedicated, and packet transmission modes, deferred and real-time traffic, quality and reliability considerations, the capacity of competing transmission media, and scenarios for the growth and development of 30/20 GHz satellite communications.
In response to severe weather conditions, traffic management coordinators specify reroutes to route air traffic around affected regions of airspace. Providing analysis and recommendations of available reroute options would assist the traffic management coordinators in making more efficient rerouting decisions. These recommendations can be developed by examining historical data to determine which previous reroute options were used in similar weather and traffic conditions. Essentially, using previous information to inform future decisions. This paper describes the initial steps and methodology used towards this goal. A method to extract relevant features from the large volume of weather data to quantify the convective weather scenario during a particular time range is presented. Similar routes are clustered. A description of the algorithm to identify which cluster of reroute advisories were actually followed by pilots is described. Models built for fifteen of the top twenty most frequently used reroute clusters correctly predict the use of the cluster for over 60 of the test examples. Results are preliminary but indicate that the methodology is worth pursuing with modifications based on insight gained from this analysis.
A concept of operations for air traffic management consists of a set of flight rules and procedures aimed to keep aircraft safely separated. This paper reports on the formal verification of separation properties of the NASA's Small Aircraft Transportation System, Higher Volume Operations (SATS HVO) concept for non-towered, non-radar airports. Based on a geometric description of the SATS HVO air space, we derive analytical formulas to compute spacing requirements on nominal approaches. Then, we model the operational concept by a hybrid non-deterministic asynchronous state transition system. Using an explicit state exploration technique, we show that the spacing requirements are always satisfied on nominal approaches. All the mathematical development presented in this paper has been formally verified in the Prototype Verification System (PVS). Keywords. Formal verification, hybrid systems, air traffic management, theorem proving
Common-carrier parcel lockers present a solution for decreasing delivery times, traffic congestion, and emissions in dense urban areas through consolidation of deliveries. Multi-story residential buildings with large number of residents, and thus a high volume of online package orders, are one of the best venues for installing parcel lockers. But what is the right size for a residential building locker that would suit the residents’ and building managers’ needs? Because of the novelty of parcel lockers, there is no clear guideline for determining the right locker size and configuration for a residential building given the resident population. A small locker would result in packages exceeding capacity and being left in the lobby, increasing the building manager’s workload and confusing and inconveniencing users. On the other hand, a large locker is more expensive, more difficult to install, and unappealing to residents. To answer this question, we installed a common-carrier parcel locker in a residential building in downtown Seattle, WA, U.S.A. Through collecting detailed data on locker usage from the locker provider company, we studied and quantified carriers’ delivery patterns and residents’ online shopping and package pickup behaviors. We then used this information to model the locker delivery and pickup process, and simulated several locker configurations to find the one that best suits the delivery needs of the building. These findings could aid urban planners and building managers in choosing the right size for residential building lockers that meet delivery demand while minimizing costs and contributing to environmental benefits.
This volume contains cost, schedule, and technical information on the following B-70 aircraft subsystems: air induction system, flight control, personnel accommodation and escape, alighting and arresting, mission and traffic control, flight indication, test instrumentation, and installation, checkout, and pre-flight.
Voice applications, data applications, video applications, impacted baseline forecasts, market distribution, potential CPS (customers premises services) user classes, net long haul forecasts, CPS cost analysis, overall satellite forecast, CPS satellite market, Ka-band CPS satellite forecast, nationwide traffic distribution model, and intra-urban topology are discussed.
Performance modeling of Urban Air Mobility vehicles in support of Air Traffic Management research poses new challenges. These aircraft often rely on a combination of fixed-wing and rotorcraft performance capabilities to enable a new and still-evolving concept of high-volume operations in densely populated areas. These characteristics lead to variability in performance model format and functionality, complicating model development and leading to difficulties for users integrating the models into their applications. This paper describes an interface specification for performance models that is intended to help address this issue. The interface aims to support the core functionality of performance models while also providing the necessary flexibility to both model developers and users. The specification describes the required model documentation, required inputs to the model, and required outputs from the model in general terms that are adaptable to most programming languages. The utilization of an appropriate interface specification will support the development of an Urban Air Mobility performance model database and help to improve interoperability of these models for a broad array of user applications.
Performance modeling of Urban Air Mobility vehicles in support of Air Traffic Management research poses new challenges. These aircraft often rely on a combination of fixed-wing and rotorcraft performance capabilities to enable a new and still-evolving concept of high-volume operations in densely populated areas. These characteristics lead to variability in performance model format and functionality, complicating model development and leading to difficulties for users integrating the models into their applications. This paper describes an interface specification for performance models that is intended to help address this issue. The interface aims to support the core functionality of performance models while also providing the necessary flexibility to both model developers and users. The specification describes the required model documentation, required inputs to the model, and required outputs from the model in general terms that are adaptable to most programming languages. The utilization of an appropriate interface specification will support the development of an Urban Air Mobility performance model database and help to improve interoperability of these models for a broad array of user applications.
Despite the robust structure of the Internet, it is still susceptible to disruptive routing updates that prevent network traffic from reaching its destination. Our research shows that BGP announcements that are associated with disruptive updates tend to occur in groups of relatively high frequency, followed by periods of infrequent activity. We hypothesize that we may use these bursty characteristics to detect anomalous routing incidents. In this work, we use manually verified ground truth metadata and volume of announcements as a baseline measure, and propose a burstiness measure that detects prior anomalous incidents with high recall and better precision than the volume baseline. We quantify the burstiness of inter-arrival times around the date and times of four large-scale incidents: the Indosat hijacking event in April 2014, the Telecom Malaysia leak in June 2015, the Bharti Airtel Ltd. hijack in November 2015, and the MainOne leak in November 2018; and three smaller scale incidents that led to traffic interception: the Belarusian traffic direction in February 2013, the Icelandic traffic direction in July 2013, and the Russian telecom that hijacked financial services in April 2017. Our method leverages the burstiness of disruptive update messages to detect these incidents. We describe limitations, open challenges, and how this method can be used for routing anomaly detection.
Space Station Freedom presents a unique opportunity for technology developers to conduct research in the space environment. Research can be conducted in the pressurized volume of the Space Station's laboratories or attached to the Space Station truss in the vacuum of space. Technology developers, represented by the Office of Aeronautics and Space Technology (OAST), will have 12 percent of the available Space Station resources (volume, power, data, crew, etc.) to use for their research. Most technologies can benefit from research on Space Station Freedom and all these technologies are represented in the OAST proposed traffic model. This traffic model consists of experiments that have been proposed by technology developers but not necessarily selected for flight. Experiments to be flown in space will be selected through an Announcement of Opportunity (A.O.) process. The A.O. is expected to be released in August, 1992. Experiments will generally fall into one of the 3 following categories: (1) Individual technology experiments; (2) Instrumented Space Station; and (3) Guest investigator program. The individual technology experiments are those that do not instrument the Space Station nor directly relate to the development of technologies for evolution of Space Station or development of advanced space platforms. The Instrumented Space Station category is similar to the Orbiter Experiments Program and allows the technology developer to instrument subsystems on the Station or develop instrumentation packages that measure products or processes of the Space Station for the advancement of space platform technologies. The guest investigator program allows the user to request data from Space Station or other experiments for independent research. When developing an experiment, a developer should consider all the resources and infrastructure that Space Station Freedom can provide and take advantage of these to the maximum extent possible. Things like environment, accommodations, carriers, and integration should all be taken into account. In developing experiments at Langley Research Center, an iterative approach is proving useful. This approach uses Space Station utilization and subsystem experts to advise and critique experiment designs to take advantage of everything the Space Station has to offer. Also, solid object modeling and animation computer tools are used to fully visualize the experiment and its processes. This process is very useful for attached payloads and allows problems to be detected early in the experiment design phase.
The development is described of the platform configurations, support subsystems, mission equipment, and servicing concepts. A common support module is developed; subsystem concepts are traded off; data relay, TDRS, earth observational, astro-physics, and advanced navigation and traffic control mission equipment concepts are postulated; and ancillary equipment required for delivery and on-orbit servicing interfaces with geosynchronous platforms is grossly defined. The general approach was to develop a platform concept capable of evolving through three on-orbit servicing modes: remote, EVA, and shirtsleeve. The definition of the equipment is to the assembly level. Weight, power, and volumetric data are compiled for all the platforms.
A cross impact model of the U.S. telecommunications system was developed. It was necessary to prepare forecasts of the major segments of the telecommunications system, such as satellites, telephone, TV, CATV, radio broadcasting, etc. In addition, forecasts were prepared of the traffic generated by a variety of new or expanded services, such as electronic check clearing and point of sale electronic funds transfer. Finally, the interactions among the forecasts were estimated (the cross impact). Both the forecasts and the cross impacts were used as inputs to the cross impact model, which could then be used to stimulate the future growth of the entire U.S. telecommunications system. By varying the inputs, technology changes or policy decisions with regard to any segment of the system could be evaluated in the context of the remainder of the system. To illustrate the operation of the model, a specific study was made of the deployment of fiber optics throughout the telecommunications system.
The design and development of a communications/navigation facility for operation aboard space stations and space shuttles are discussed. The objectives of the facility are as follows: (1) to develop and demonstrate satellite and spacecraft technology applicable to space communications, navigation, and traffic control, (2) to optimize the use of the electromagnetic spectrum for communications and navigation satellite systems, and (3) to provide fundamental understanding of the space communications and navigation sciences to permit application of this discipline to government and industry.
One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on current and forecast of traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. In this paper, a methodology using supervised learning is developed to build a predictive model for RCM decision-support from large volumes of historical data. Data from two full years (2018 and 2019) related to current and forecast weather, demand/capacity, etc. is collected, analyzed, and fused together. A variety of supervised learning algorithms are tested for predicting runway configuration and hyperparameter tuning is carried out to select the best performing model. The validation process involves two airports of low (Charlotte Douglas International Airport, CLT) and high (Denver International Airport, DEN) complexity of configuration decision-making. The results show significant promise for the two airports with test accuracy of 93% (CLT) and 73% (DEN). The methodology is scalable and generalizable to other airports across the U.S. National Airspace System.
One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on current and forecast of traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. In this paper, a methodology using supervised learning is developed to build a predictive model for RCM decision-support from large volumes of historical data. Data from two full years (2018 and 2019) related to current and forecast weather, demand/capacity, etc. is collected, analyzed, and fused together. A variety of supervised learning algorithms are tested for predicting runway configuration and hyperparameter tuning is carried out to select the best performing model. The validation process involves two airports of low (Charlotte Douglas International Airport, CLT) and high (Denver International Airport, DEN) complexity of configuration decision-making. The results show significant promise for the two airports with test accuracy of 93% (CLT) and 73% (DEN). The methodology is scalable and generalizable to other airports across the U.S. National Airspace System.
The scheduling algorithm for mission planning and logistics evaluation (SAMPLE) is presented. Two major subsystems are included: The mission payloads program; and the set covering program. Formats and parameter definitions for the payload data set (payload model), feasible combination file, and traffic model are documented.
Developments in aviation, including new surveillance technologies and quicker, more economical small aircraft, have been identified as driving factors in a potential expansion of the use of non-towered, non-radar airports. The Small Aircraft Transportation System (SATS) project has developed the Higher Volume Operations (HVO) concept that enables pilots to safely arrive and depart these airports in instrument conditions at an increased rate as compared to today's procedures. This is achieved by transferring some traffic management tasks to centralized, ground-based automation, while assigning others to participating pilots aided by on-board tools. This paper describes strategies and lessons learned while training pilots to fly these innovative operations. Pilot approaches to using the experimental displays and dynamic altering systems during training are discussed. Potential operational benefits as well as pit-falls and frustrations expressed by subjects while learning to fly these new procedures are presented. Generally, pilots were comfortable with the procedures and the training process, and expressed interest in its near-term implementation.
Convective weather is currently the largest contributor to air traffic delays in the United States. In order to make effective traffic flow management decisions to mitigate these delays, weather forecasts must be made as early and as accurately as possible. A forecast product that could be used to mitigate convective weather impacts is the Consolidated Storm Prediction for Aviation. This product provides forecasts of cloud water content and convective top heights at 0- to 8-hour look-ahead times. The objective of this study was to examine a method of predicting the impact of convective weather on air traffic sector capacities using these forecasts. Polygons representing forecast convective weather were overlaid at multiple flight levels on a sector map to calculate the fraction of each sector covered by weather. The fractional volume coverage was used as the primary metric to determine convection s impact on sectors. Results reveal that the forecasts can be used to predict the probability and magnitude of weather impacts on sector capacity up to eight hours in advance.