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NASA NTRS2016

Operational Characteristics Identification and Simulation Model Verification for Incheon International Airport

Incheon International Airport (ICN) is one of the hub airports in East Asia. Airport operations at ICN have been growing more than 5% per year in the past five years. According to the current airport expansion plan, a new passenger terminal will be added and the current cargo ramp will be expanded in 2018. This expansion project will bring 77 new stands without adding a new runway to the airport. Due to such continuous growth in airport operations and future expansion of the ramps, it will be highly likely that airport surface traffic will experience more congestion, and therefore, suffer from efficiency degradation. There is a growing awareness in aviation research community of need for strategic and tactical surface scheduling capabilities for efficient airport surface operations. Specific to ICN airport operations, a need for A-CDM (Airport - Collaborative Decision Making) or S-CDM(Surface - Collaborative Decision Making), and controller decision support tools for efficient air traffic management has arisen since several years ago. In the United States, there has been independent research efforts made by academia, industry, and government research organizations to enhance efficiency and predictability of surface operations at busy airports. Among these research activities, the Spot and Runway Departure Advisor (SARDA) developed and tested by National Aeronautics and Space Administration (NASA) is a decision support tool to provide tactical advisories to the controllers for efficient surface operations. The effectiveness of SARDA concept, was successfully verified through the human-in-the-loop (HITL) simulations for both spot release and runway operations advisories for ATC Tower controllers of Dallas/Fort Worth International Airport (DFW) in 2010 and 2012, and gate pushback advisories for the ramp controller of Charlotte/Douglas International Airport (CLT) in 2014. The SARDA concept for tactical surface scheduling is further enhanced and is being integrated into NASA's Airspace Technology Demonstration - 2 (ATD-2) project for technology demonstration of Integrated Arrival/Departure/Surface (ADS) operations at CLT. This study is a part of the international research collaboration between KAIA (Korea Agency for Infrastructure Technology Advancement)/KARI (Korea Aerospace Research Institute) and NASA, which is being conducted to validate the effectiveness of SARDA concept as a controller decision support tool for departure and surface management of ICN. This paper presents the preliminary results of the collaboration effort. It includes investigation of the operational environment of ICN, data analysis for identification of the operational characteristics of the airport, construction and verification of airport simulation model using Surface Operations Simulator and Scheduler (SOSS), NASA's fast-time simulation tool.

scheduling↗

NASA NTRS2016

Operational Characteristics Identification and Simulation Model Verification for Incheon International Airport

Incheon International Airport (ICN) is one of the hub airports in East Asia. Airport operations at ICN have been growing more than 5 percent per year in the past five years. According to the current airport expansion plan, a new passenger terminal will be added and the current cargo ramp will be expanded in 2018. This expansion project will bring 77 new stands without adding a new runway to the airport. Due to such continuous growth in airport operations and future expansion of the ramps, it will be highly likely that airport surface traffic will experience more congestion, and therefore, suffer from efficiency degradation. There is a growing awareness in aviation research community of need for strategic and tactical surface scheduling capabilities for efficient airport surface operations. Specific to ICN airport operations, a need for A-CDM (Airport - Collaborative Decision Making) or S-CDM (Surface - Collaborative Decision Making), and controller decision support tools for efficient air traffic management has arisen since several years ago. In the United States, there has been independent research efforts made by academia, industry, and government research organizations to enhance efficiency and predictability of surface operations at busy airports. Among these research activities, the Spot and Runway Departure Advisor (SARDA) developed and tested by National Aeronautics and Space Administration (NASA) is a decision support tool to provide tactical advisories to the controllers for efficient surface operations. The effectiveness of SARDA concept, was successfully verified through the human-in-the-loop (HITL) simulations for both spot release and runway operations advisories for ATC Tower controllers of Dallas-Fort Worth International Airport (DFW) in 2010 and 2012, and gate pushback advisories for the ramp controller of Charlotte-Douglas International Airport (CLT) in 2014. The SARDA concept for tactical surface scheduling is further enhanced and is being integrated into NASA's Airspace Technology Demonstration-2 (ATD-2) project for technology demonstration of Integrated Arrival-Departure-Surface (IADS) operations at CLT. This study is a part of the international research collaboration between KAIA (Korea Agency for Infrastructure Technology Advancement), KARI (Korea Aerospace Research Institute) and NASA, which is being conducted to validate the effectiveness of SARDA concept as a controller decision support tool for departure and surface management of ICN. This paper presents the preliminary results of the collaboration effort. It includes investigation of the operational environment of ICN, data analysis for identification of the operational characteristics of the airport, construction and verification of airport simulation model using Surface Operations Simulator and Scheduler (SOSS), NASA's fast-time simulation tool.

surface operations analysis↗

NASA NTRS2006

Emerging Definition of Next-Generation of Aeronautical Communications

Aviation continues to experience rapid growth. In regions such as the United States and Europe air traffic congestion is constraining operations, leading to major new efforts to develop methodologies and infrastructures to enable continued aviation growth through transformational air traffic management systems. Such a transformation requires better communications linking airborne and ground-based elements. Technologies for next-generation communications, the required capacities, frequency spectrum of operation, network interconnectivity, and global interoperability are now receiving increased attention. A number of major planning and development efforts have taken place or are in process now to define the transformed airspace of the future. These activities include government and industry led efforts in the United States and Europe, and by international organizations. This paper will review the features, approaches, and activities of several representative planning and development efforts, and identify the emerging global consensus on requirements of next generation aeronautical communications systems for air traffic control.

Kerczewski, Robert J.↗

NASA NTRS2018

Airspace Technology Demonstration 3 (ATD-3): Dynamic Weather Routes (DWR) Technology Transfer Document Summary Version 2.0

This summary document and accompanying technology artifacts satisfy the first of three Research Transition Products (RTPs) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. The original transfer, completed in September 2016, consisted of NASA's legacy Dynamic Weather Routes (DWR) work for efficient routing for en-route weather avoidance. This transfer updates the Concept of Operations document to a publicly-available NASA Technical Memorandum. Dynamic Weather Routes (DWR) is a ground-based trajectory automation system that continuously and automatically analyzes active in-flight aircraft in en route airspace to identify opportunities for simple corrections to flight plan routes that can save significant flying time, at least five minutes wind-corrected, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions.

DWR↗

NASA NTRS2018

Performance Evaluation of Conflict-Free Trajectory Taxiing in Airport Ramp Area Using Fast-Time Simulations

The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been collaborating to conduct joint research addressing future surface traffic management challenges. The surface management tool from DLR, called Taxi Routing for Aircraft: Creation and Controlling (TRACC), was adapted to be integrated in NASA's fast-time simulation environment called Surface Operations Simulator and Scheduler (SOSS). The research described in this paper 1) applied TRACC to trajectory-based ramp traffic management, where TRACC generates conflict-free aircraft trajectories in a congested ramp area, 2) investigated the feasibility of the concept through the integrated TRACC-SOSS fast-time simulation, and 3) evaluated the performance of the integrated system. For this activity, TRACC was adapted for ramp operations at Charlotte Douglas International Airport, called TRACC_PB (TRACC for pushback optimization). TRACC_PB provides four-dimensional taxi trajectories with a command speed profile for each aircraft following standard taxi routes within the ramp area. In this study, departures are given the Target Movement Area entry Times (TMATs) provided by the baseline surface metering scheduler based on NASA's Spot and Runway Departure Advisor (SARDA). TRACC_PB also calculates optimal pushback times for departures, as well as the times when arrivals shall enter the ramp, the Target Movement area Exit Times (TMETs). The initial results showed that the TRACC_PB successfully generated conflict-free trajectories for the ramp area taxi operations and improved taxiing efficiency compared to the baseline results. TRACC_PB aimed to provide conflict-free taxi routes avoiding any stops while taxiing. This resulted in longer gate hold times for departures and postponed throughput values compared to the baseline simulation without trajectory optimization. Having conflict-free routes without stoppage also created shorter taxi times but required renegotiation of the given TMATs. TRACC_PB also achieved reductions in both fuel consumption and engine emissions (17% for departures and 10% for arrivals), which correlate with the ramp taxi time reduction.

trajectory-based taxi operations↗

NASA NTRSDate not supplied

Designing for Advanced Aerial Mobility: Human-Autonomy Teaming and In-Time System-Wide Safety Assurance

The continued growth of aviation shall require new innovative technologies and operational concepts to meet the ever-increasing demands on air transportation. The NASA Advanced Air Mobility (AAM) project focuses on emerging aviation markets, such as Urban Air Mobility (UAM). UAM is defined as “...a safe and efficient system for air passenger and cargo transportation within an urban area. It is inclusive of small package delivery and other urban unmanned aerial system services and supports a mix of onboard/ground-piloted and increasingly autonomous operations” ([1]). The AAM project emphasizes technology development and validating system-level concepts and solutions in coordination with other NASA Aeronautics Research Mission Directorate (ARMD) projects to enable UAM metro- and micro-plex vertiport and airspace concepts of operations. The NASA AAM research portfolio includes the concepts of Remote Supervisor-in-Command (RSC) and Fleet and Airspace Manager (FAM) as possible human roles for consumer fleet providers. NASA research in RSC is focused on development of guidelines and standards for remote pilots/operators passively and actively controlling a large fleet of autonomous aircraft. For FAM, flight and ground system concepts and technologies to enable high density homogeneous operations at increased scale from vertiport(s), and coordination with other humans in the systems (e.g., UAM urban airspace manager, Air Traffic Control) are key research areas. The envisioned UAM operations are posited to require autonomous systems to enable functions ranging from fleet and resource management to vehicle control. Although automation has become increasingly sophisticated and ubiquitous in civil aviation, autonomy represents a significant evolution in automation, which has generally been limited in functional scope and capability. As autonomy takes on increasing responsibilities, humans and machines will be required to work together in new and different ways [2], rather than traditional design approaches focused on how machines (i.e., autonomy) can do the work of people. The emerging field of human-autonomy teaming (HAT) represents a comprehensive and prioritized research-driven approach to enable the success of future emerging aviation market applications through capabilities and principles that facilitate humans and machine working and thinking better together. The NASA Transformational Tools and Technologies (TTT) Autonomous System (AS) Sub-project was created to assist with the transition into higher levels of autonomy to enable new modes of air transportation, such as UAM. TTT-AS has identified HAT as a key research need to enable UAM while maintaining today’s ultra-safe aviation system safety levels. The latter challenge has been taken up by the NASA System-Wide Safety (SWS) Project, which recognizes that aviation safety, as it evolves, shall require new ways of thinking about safety to include integration of a wide-range of existing and new safety systems and practices, enhanced tools and technologies, increased access to data and data fusion, improved data analysis capabilities, enhanced in-time risk monitoring and detection, hazard prioritization and mitigation, safety assurance decision-support, and in-time integrated system analytics [3].The operational concept of UAM represents a variety of work that has been termed, “work-as-imagined” to characterize the idea that how people think that work is done and how work is actually done are often not the same [4]. To ensure design success and system safety, looking at “work-as-done” provides a comparative approach toward UAM concept and technology design through examination of corresponding analogs found today in aviation (e.g., on-demand operations) and other transportation domains (e.g., port operations). The paper shall discuss various alternative applications with specific focus on airline operation center (AOC) operations, and unmanned aerial system (UAS) command-and-control to inform scaled-versions of FAM and RSC, respectively, and with consideration of the national airspace system contextual environment. The tenets and principles of the HAT field and current NASA research efforts under the TTT-AS sub-project shall also be described. Finally, the SWS sub-project efforts to develop In-Time System-Wide Safety Assurance (ISSA) and In-Time Safety Management Systems (IASMS) are discussed in terms of how “in-time” safety assurance may be conceptualized for the on-demand mobility air taxi “work-as-imagined” operational concept [5]. As part of this effort, concepts from the emerging field of resilience engineering, are being studied. Traditional approaches to aviation safety have focused on what can go wrong and how to prevent it. Another approach to thinking about system safety should reflect not only “avoiding things that go wrong” (protective safety) but also “ensuring that things go right” (productive safety), that enables a system to exhibit the resilient performance [6] necessary for the success of the future aviation system emerging concepts of operations. The paper shall describe efforts focused on how productive safety and resilience may enable a more complete approach to system safety thinking and design of ISSA and IASMS for UAM. Future directions and research needs shall also be discussed.

resilience↗

NASA NTRSDate not supplied

Simulated Evaluation of Strategic Conflict Management Capabilities for Urban Air Mobility Operations

Urban Air Mobility (UAM) is a new air transportation service concept to carry passengers or cargo in metropolitan areas, leveraged by innovative aircraft and automation technologies. NASA has conducted a series of simulations to evaluate the UAM concept of operations and inform the development of airspace procedures and services for UAM operations. The latest set of simulations called “X5” were conducted to test a Provider of Services for UAM (PSU) prototype that NASA developed for UAM flight planning, strategic conflict management support, and data exchange between UAM operators. In these simulations, two strategic conflict management capabilities, Demand-Capacity Balancing (DCB) and Sequencing and Scheduling (S&S), were further investigated. This paper describes the system architecture designed for the X5 simulation activities, the sequence diagram for strategic conflict management, and the simulation environment in the Dallas/Fort Worth urban area. The simulation results based on several system performance metrics for evaluation show that a sequential application of DCB and S&S effectively works to distribute traffic demand and meet sequencing and spacing criteria by assigning ground delays, compared to the DCB only and S&S only cases.

Urban Air Mobility, Strategic Conflict Management,↗

NASA NTRSDate not supplied

Simulated Evaluation of Strategic Conflict Management Capabilities for Urban Air Mobility Operations

Simulation↗

NASA NTRS2014

Throughput Benefit Assessment for Tactical Runway Configuration Management (TRCM)

The System-Oriented Runway Management (SORM) concept is a collection of needed capabilities focused on a more efficient use of runways while considering all of the factors that affect runway use. Tactical Runway Configuration Management (TRCM), one of the SORM capabilities, provides runway configuration and runway usage recommendations, monitoring the active runway configuration for suitability given existing factors, based on a 90 minute planning horizon. This study evaluates the throughput benefits using a representative sample of today's traffic volumes at three airports: Memphis International Airport (MEM), Dallas-Fort Worth International Airport (DFW), and John F. Kennedy International Airport (JFK). Based on this initial assessment, there are statistical throughput benefits for both arrivals and departures at MEM with an average of 4% for arrivals, and 6% for departures. For DFW, there is a statistical benefit for arrivals with an average of 3%. Although there is an average of 1% benefit observed for departures, it is not statistically significant. For JFK, there is a 12% benefit for arrivals, but a 2% penalty for departures. The results obtained are for current traffic volumes and should show greater benefit for increased future demand. This paper also proposes some potential TRCM algorithm improvements for future research. A continued research plan is being worked to implement these improvements and to re-assess the throughput benefit for today and future projected traffic volumes.

Phojanamongkolkij, Nipa↗

NASA NTRS2016

From Rural to Urban Environments: Human/Systems Simulation Research for Low Altitude UAS Traffic Management (UTM)

This paper describes the human/systems simulation research within NASA's UAS (Unmanned Aircraft System) Traffic Management (UTM) project. The paper starts with a short description of the UTM project, then presents the UTM development schedule briefly, before leading into more detailed discussions of the simulation test beds current capabilities, as well as the ongoing and planned human/systems research activities.

unmanned aircraft systems↗

NASA NTRS2018

An Implementation Analysis of Communications, Navigation, and Surveillance (CNS) Technologies for Unmanned Air Systems (UAS)

The aviation industry and government agencies face a rapidly-emerging need for integrating large-scale populations of Unmanned Air Systems (UAS) into the worldwide controlled and uncontrolled airspace. Critical components for integration include the Communications, Navigation, and Surveillance (CNS) technologies necessary for ensuring safe UAS operations. Under NASA program NNA16BD84C, our work on CNS architectural concepts for the safe operation of UAS in controlled and uncontrolled airspace has introduced CNS architectures which must be analyzed in terms of implementation readiness.Controlled airspace operations for UAS are consistent with the needs for manned aviation in the worldwide Air Traffic Management (ATM) service. Uncontrolled airspace operations are consistent with the NASA Unmanned (air) Traffic Management (UTM) concept of operations. Implementation readiness is based on the NASA concept of Technology Readiness Levels (TRLs) ranging from TRL1 (basic principles observed and reported) to TRL9 (actual system flight proven through successful mission operations). In the architecture concepts, we have introduced a number of new CNS architectural elements which need to be correlated with TRL levels. In this paper, we present our implementation analysis for communications networks, communications data links, navigation, and surveillance. Each area has been under active research and development during the course of the current NASA program which has produced studies on UAS CNS Requirements, UAS CNS Architecture for Controlled Airspace and UAS CNS Architecture for Uncontrolled Airspace. We have published our architecture concepts in major UAS-related conferences (including iCNS2017, IEEE Aerospace 2018, and iCNS2018) and will continue to seek additional publication opportunities. We look forward to continuing our work to realize a full integration testing scenario for both controlled and uncontrolled airspace operation.

Unmanned (Air) Traffic Management (UTM) service↗

NASA NTRS2023

Study of Pairwise Deconfliction Metrics to Analyze Air Traffic Complexity in Upper Class E Airspace

Upper Class E Traffic Management (ETM) is envisioned to cooperatively facilitate operations of a diverse set of aerial vehicles, such as high-altitude long-endurance fixed-wing unmanned aircraft (low-speed and high-speed), high-altitude platforms, airships, stratospheric balloons, supersonic unmanned and commercial aircraft, etc., with a wide variety of mission types, performance characteristics, communication, navigation and surveillance capabilities, maneuverability, and on-board avionics in the National Airspace System (NAS) ’above’ 60,000 feet above mean sea level, without an active and direct control from human air traffic controllers. A diverse mixture of aerial vehicle types creates significant challenges in understanding air traffic complexity, which may not correlate strongly with air traffic density. One key step for determining air traffic complexity in upper class E airspace is to first understand pairwise deconfliction metrics such as reachability, reserve area, and reserve flight time for each pair of unique aerial vehicle types under potential conflict. Therefore, pairwise deconfliction metrics are first defined, and analytical equations are derived for conflict resolution using the heading change maneuver. Next, case studies are performed to analyze deconfliction metrics to avoid secondary conflicts in upper class E airspace. The study shows that pairwise deconfliction metrics are functions of maneuverability, performance characteristics, uncertainty in position and velocity, heading angle change, and conflict angle of aerial vehicles. The next step for this research is to build a mathematical model for air traffic complexity using pairwise deconfliction metrics and validate it in an upper Class E simulation environment.

Airspace Complexity↗

NASA NTRSDate not supplied

Study of Pairwise Deconfliction Metrics to Analyze Air Traffic Complexity in Upper Class E Airspace

Airspace Complexity↗

NASA NTRS2013

Precision Departure Release Capability (PDRC) Final Report

After takeoff, aircraft must merge into en route (Center) airspace traffic flows that may be subject to constraints that create localized demand/capacity imbalances. When demand exceeds capacity, Traffic Management Coordinators (TMCs) and Frontline Managers (FLMs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves a Call for Release (CFR) procedure wherein the Tower must call the Center to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool, based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release time is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that improves tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions and departure runway assignments to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept reduces uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs and FLMs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station in Dallas/Fort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations. This paper presents research results from the PDRC research activity. Companion papers present the Concept of Operations and a Technology Description.

tactical departure scheduling↗

NASA NTRS2011

Automated Air Traffic Control Operations with Weather and Time-Constraints: A First Look at (Simulated) Far-Term Control Room Operations

In this paper we discuss results from a recent high fidelity simulation of air traffic control operations with automated separation assurance in the presence of weather and time-constraints. We report findings from a human-in-the-loop study conducted in the Airspace Operations Laboratory (AOL) at the NASA Ames Research Center. During four afternoons in early 2010, fifteen active and recently retired air traffic controllers and supervisors controlled high levels of traffic in a highly automated environment during three-hour long scenarios, For each scenario, twelve air traffic controllers operated eight sector positions in two air traffic control areas and were supervised by three front line managers, Controllers worked one-hour shifts, were relieved by other controllers, took a 3D-minute break, and worked another one-hour shift. On average, twice today's traffic density was simulated with more than 2200 aircraft per traffic scenario. The scenarios were designed to create peaks and valleys in traffic density, growing and decaying convective weather areas, and expose controllers to heavy and light metering conditions. This design enabled an initial look at a broad spectrum of workload, challenge, boredom, and fatigue in an otherwise uncharted territory of future operations. In this paper we report human/system integration aspects, safety and efficiency results as well as airspace throughput, workload, and operational acceptability. We conclude that, with further refinements. air traffic control operations with ground-based automated separation assurance can be an effective and acceptable means to routinely provide very high traffic throughput in the en route airspace.

Prevot, Thomas↗

NASA NTRS2013

SARDA: An Integrated Concept for Airport Surface Operations Management

The Spot and Runway Departure Advisor (SARDA) is an integrated decision support tool for airlines and air traffic control tower enabling surface collaborative decision making (CDM) and departure metering in order to enhance efficiency of surface operations at congested airports. The presentation describes the concept and architecture of the SARDA as a CDM tool, and the results from a human-in-the-loop simulation of the tool conducted in 2012 at the FutureFlight Central, the tower simulation facility. Also, presented is the current activities and future plan for SARDA development. The presentation was given at the meeting with the FAA senior advisor of the Surface Operations Office.

surface collaborative decision making↗

NASA NTRS1991

Multi-Attribute Task Battery - Applications in pilot workload and strategic behavior research

The Multi-Attribute Task (MAT) Battery provides a benchmark set of tasks for use in a wide range of lab studies of operator performance and workload. The battery incorporates tasks analogous to activities that aircraft crewmembers perform in flight, while providing a high degree of experimenter control, performance data on each subtask, and freedom to nonpilot test subjects. Features not found in existing computer based tasks include an auditory communication task (to simulate Air Traffic Control communication), a resource management task permitting many avenues or strategies of maintaining target performance, a scheduling window which gives the operator information about future task demands, and the option of manual or automated control of tasks. Performance data are generated for each subtask. In addition, the task battery may be paused and onscreen workload rating scales presented to the subject. The MAT Battery requires a desktop computer with color graphics. The communication task requires a serial link to a second desktop computer with a voice synthesizer or digitizer card.

Arnegard, Ruth J.↗

NASA NTRS1992

The multi-attribute task battery for human operator workload and strategic behavior research

The Multi-Attribute Task (MAT) Battery provides a benchmark set of tasks for use in a wide range of lab studies of operator performance and workload. The battery incorporates tasks analogous to activities that aircraft crewmembers perform in flight, while providing a high degree of experimenter control, performance data on each subtask, and freedom to use nonpilot test subjects. Features not found in existing computer based tasks include an auditory communication task (to simulate Air Traffic Control communication), a resource management task permitting many avenues or strategies of maintaining target performance, a scheduling window which gives the operator information about future task demands, and the option of manual or automated control of tasks. Performance data are generated for each subtask. In addition, the task battery may be paused and onscreen workload rating scales presented to the subject. The MAT Battery requires a desktop computer with color graphics. The communication task requires a serial link to a second desktop computer with a voice synthesizer or digitizer card.

Comstock, J. Raymond, Jr.↗