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As part of a project to identify and rank choke points in the National Airspace System (NAS), we engaged with 18 aviation industry stakeholders—Federal Aviation Administration, airline, and airport representatives—to understand their point of view regarding current choke points and their causes. We organized and participated in stakeholder meetings, telephone interviews, and two workshops. Through this process, we identified 66 individual NAS choke points, which we then ranked based on the number of times each choke point was mentioned by the 18 stakeholders. The top-ranked choke points were primarily the large hub airports; they contribute the largest share of NAS congestion. We solicited feedback from the NAS stakeholders on the causes of choke points at 12 airports that we believe have the most severe and the largest share of NAS choke points; the causes at those 12 airports are likely to be similar to those at airports considered less severe choke points. We categorized the cited causes as airport surface constraints, departure constraints, arrival constraints, or airspace issues.

This paper presents a search algorithm based framework to calibrate origin-destination (O-D) market specific airline ticket demands and prices for the Air Transportation System (ATS). This framework is used for calibrating an agent based model of the air ticket buy-sell process - Airline Evolutionary Simulation (Airline EVOS) -that has fidelity of detail that accounts for airline and consumer behaviors and the interdependencies they share between themselves and the NAS. More specificially, this algorithm simultaneous calibrates demand and airfares for each O-D market, to within specified threshold of a pre-specified target value. The proposed algorithm is illustrated with market data targets provided by the Transportation System Analysis Model (TSAM) and Airline Origin and Destination Survey (DB1B). Although we specify these models and datasources for this calibration exercise, the methods described in this paper are applicable to calibrating any low-level model of the ATS to some other demand forecast model-based data. We argue that using a calibration algorithm such as the one we present here to synchronize ATS models with specialized forecast demand models, is a powerful tool for establishing credible baseline conditions in experiments analyzing the effects of proposed policy changes to the ATS.

An emerging vision of high-speed, on-demand mobility includes small aircraft that are as accessible to the broad population as cars. Broad accessibility dictates that such vehicles be safe and easy to use, including significantly reduced operator training, relative to current small aircraft. Very high levels of automation present a potential approach to enabling these goals, however unless emerging automation can largely obviate the need for human involvement beyond providing high-level goals (such as desired origin, destination, and time of departure), human-automation interaction will remain a key challenge. What are the safety levels and functions required for automated pilotage and how close are we to achieving them? In this overview, we assess likely safety goals and requirements for on-demand mobility aircraft and then examine the state of the art in transportation automation that could help meet them. Looking at intercity rail, cars, and aircraft we survey operational safety functions that automation currently supports, how completely it performs these functions, and how it supports tasks shared with human operators. We conclude with a brief discussion of likely gaps between the state of the art and the needs of on-demand mobility.

As part of ongoing research, the National Aeronautics and Space Administration (NASA) and LMI developed a research framework to assist policymakers in identifying impacts on the U.S. air transportation system (ATS) of potential policies and technology related to the implementation of the Next Generation Air Transportation System (NextGen). This framework, called the Air Transportation System Evolutionary Simulation (ATS-EVOS), integrates multiple models into a single process flow to best simulate responses by U.S. commercial airlines and other ATS stakeholders to NextGen-related policies, and in turn, how those responses impact the ATS. Development of this framework required NASA and LMI to create an agent-based model of airline and passenger behavior. This Airline Evolutionary Simulation (AIRLINE-EVOS) models airline decisions about tactical airfare and schedule adjustments, and strategic decisions related to fleet assignments, market prices, and equipage. AIRLINE-EVOS models its own heterogeneous population of passenger agents that interact with airlines; this interaction allows the model to simulate the cycle of action-reaction as airlines compete with each other and engage passengers. We validated a baseline configuration of AIRLINE-EVOS against Airline Origin and Destination Survey (DB1B) data and subject matter expert opinion, and we verified the ATS-EVOS framework and agent behavior logic through scenario-based experiments. These experiments demonstrated AIRLINE-EVOS's capabilities in responding to an input price shock in fuel prices, and to equipage challenges in a series of analyses based on potential incentive policies for best equipped best served, optimal-wind routing, and traffic management initiative exemption concepts..

NASA created the Environmentally Responsible Aviation (ERA) Project to explore and document the feasibility, benefits and technical risk of vehicle concepts and enabling technologies that will reduce the impact of aviation on the environment, and to advance the technology readiness level of key technologies for mid-term implementation. Over the course of the project, ERA has studied and developed dozens of technologies to make aircraft fly more fuel-efficiently, with less noise and emissions than ever before. Some of these technologies are entering the fleet as incremental improvements to the latest airframes; others require further development. To track and understand future impacts of the program on noise, fuel, emissions, and other areas of interest, ERA has been developing a range of tools to measure projected technology impacts. Part of this latest effort focused on evaluating the safety impacts of ERA N+2 technologies and designs projected into the next generation air transportation system. Beginning with an assumption of basic aircraft airworthiness, we identified needed standards development efforts and the impact of differentiated N+2 aircraft flight performance on future air traffic management operations.

Mosaic ATM The objective of this research effort was to analyze the costs and benefits of NASA’s candidate air traffic management (ATM) concepts and technologies (C&Ts) supporting a near-term vision of Trajectory Based Operations (TBO). We assessed each C&T separately, not collectively. We created benefit mechanisms flow diagrams for each selected TBO C&T from operational tests, field evaluations, and controller-in-the-loop simulation evaluations. Next we created detailed models to evaluate the benefits of each concept throughout the National Airspace System (NAS). Concurrently, we analyzed the costs of each C&T by comparing analogous programs, particularly other NASA research and development concepts that became Federal Aviation Administration (FAA) ATM solutions. Our results show national payoff periods that ranged from less than 1 year to 50 years or more for the weather-related concepts.

We have conducted an initial life -cycle cost/benefit assessment of NASA’s Distributed Air/Ground Traffic Management (DAG -TM). We estimated the benefit -to -cost ratio and net present value for each of three concept elements: En Route Free Maneuvering, En Route Trajectory Negoti ation, and Terminal Arrival Self -Spacing . Although many conservative assumptions were used, our results show that each concept element has a benefit -to -cost ratio significantly greater than unity. We found that if airspace users equip only newly purchased aircraft with the required avionics – thereby avoiding retrofitting existing aircraft – costs decrease dramatically as compared to if both new and existing aircraft are equipped in order to reach a target equipage percentage for the entire fleet. It is e vident that the two en route concept elements provide effective potential solutions for the en route congestion problem anticipated in the future while the terminal area concept element offers a compelling potential solution to reducing in -trail spacing, p articularly when instrument landing approaches are required. HE National Aeronautics and Space Administration (NASA) is conducting far -term research into a proposed concept for gate -to -gate national airspace system (NAS) operations called Di stributed Air/Ground Traffic Management (DAG -TM). DAG -TM is based on distributed decision making between flight deck crews, air traffic service providers (ATSP) and aeronautical operational control (AOC) personnel. The goal of DAG -TM is to increase system capacity/throughput, enable user preferences, and provide greater flexibility and efficiency, while meeting air traffic management (ATM) requirements and maintaining system safety and user accessibility to the NAS. DAG -TM will be accomplished with a huma n-centered operational paradigm enabled by procedural and technological innovations. These innovations include automation aids, information sharing and Communication, Navigation, and Surveillance (CNS) / ATM technologies. The total DAG -TM concept is inte nded to address all user classes (commercial carriers, general aviation, etc.) with an emphasis towards ensuring access to airspace resources for the entire user community. The full scope of DAG -TM is embodied in 15 Concept Elements (CEs) that define the concept across all flight phases (pre -flight planning, departure, cruise and arrival) and operational domains in the