Generation Air Transportation System Research Articles

Projecting the economic burden of health impacts of aircraft noise: a case study of Baltimore Washington International Thurgood Marshall Airport.

While the Next Generation Air Transportation System (NextGen) in the United States optimizes flight patterns, it has led to the unintended consequence of increasing aircraft noise exposure in some communities near airports. Despite the evidence that chronic exposure to high noise levels produces detrimental health effects, potential adverse health consequences due to increased noise in the affected communities have not been adequately considered in aviation policy discussions. We assessed the long-term health and associated economic burden of increased aircraft noise caused by NextGen near the Baltimore-Washington Thurgood Marshall International (BWI) airport in Maryland. A probabilistic Markov model projected the incremental health and associated economic burden over 30, 20, and 10 years, comparing post-NextGen noise exposure levels to pre-NextGen levels. Health outcomes included cardiovascular disease (CVD), anxiety disorders, noise annoyance, and low birth weight (LBW). Noise exposure was categorized into four levels (<55 dB DNL, 55-60 dB DNL, 60-65 dB DNL, >65 dB DNL). A Monte Carlo simulation with 2000 iterations was run to obtain incremental burden estimates and uncertainty intervals. One-way sensitivity analyses for noise effect parameters were conducted. Increased aircraft noise exposure was estimated to produce (discounted) incremental mortality costs of $362 million, morbidity costs of $336 million, and losses of 15,326 Quality-Adjusted Life Years (QALYs) over the next 30 years. Sensitivity analyses revealed the greatest uncertainty for CVD outcomes. NextGen is a system that can increase the operational efficiency of airports by optimizing flight patterns. While operational efficiency is beneficial in many ways, changes in flight patterns and volume can also produce noise pollution, a major public health concern that should be considered in policy decision-making. This study quantifies the long-term health and economic implications of increased aircraft noise exposure following the implementation of NextGen in communities near the Baltimore-Washington International Airport. Our findings underscore the importance of considering public health consequences of noise pollution.

A method to mitigate cyber exploits on automatic dependent surveillance-broadcast (ADS-B) data transmissions

PurposeAutomatic dependent surveillance-broadcast (ADS-B) is the foundational technology of the next generation air transportation system defined by Federal Aviation Authority and is one of the most precise ways for tracking aircraft position. ADS-B is intended to provide greater situational awareness to the pilots by displaying the traffic information like aircraft ID, altitude, speed and other critical parameters on the Cockpit Display of Traffic Information displays in the cockpit. Unfortunately, due to the initial proposed nature of ADS-B protocol, it is neither encrypted nor has any other innate security mechanisms, which makes it an easy target for malicious attacks. The system is vulnerable to various active and passive attacks like message ingestion, message deletion, eavesdropping, jamming, etc., which has become an area of concern for the aviation industry. The purpose of this study is to propose a method based on modified advanced encryption standard (AES) algorithm to secure the ADS=B messages and increase the integrity of ADS-B data transmissions.Design/methodology/approachThough there are various cryptographic and non-cryptographic methods proposed to secure ADS-B data transmissions, it is evident that most of these systems have limitations in terms of cost, implementation or feasibility. The new proposed method implements AES encryption techniques on the ADS-B data on the sender side and correlated decryption mechanism at the receiver end. The system is designed based on the flight schedule data available from any flight planning systems and implementing the AES algorithm on the ADS-B data from each aircraft in the flight schedule.FindingsThe suitable hardware was developed using Raspberry pi, ESP32 and Ra-02. Several runs were done to verify the original message, transmitted data and received data. During transmission, encryption algorithm was being developed, which has got very high secured transmission, and during the reception, the data was secured. Field test was conducted to validate the transmission and quality. Several trials were done to validate the transmission process. The authors have successfully shown that the ADS-B data can be encrypted using AES algorithm. The authors are successful in transmitting and receiving the ADS-B data packet using the discussed hardware and software methodology. One major advantage of using the proposed solution is that the information received is encrypted, and the receiver ADS-B system can decrypt the messages on the receiving end. This clearly proves that when the data is received by an unknown receiver, the messages cannot be decrypted, as the receiver is not capable of decrypting the AES-authenticated messages transmitted by the authenticated source. Also, AES encryption is highly unlikely to be decrypted if the encryption key and the associated decryption key are not known.Research limitations/implicationsImplementation of the developed solution in actual onboard avionics systems is not within the scope of this research. Hence, assessing in the real-time distances is not covered.Social implicationsThe authors propose to extend this as a software solution to the onboard avionics systems by considering the required architectural changes. This solution can also bring in positive results for unmanned air vehicles in addition to the commercial aircrafts. Enhancement of security to the key operational and navigation data elements is going to be invaluable for future air traffic management and saving lives of people.Originality/valueThe proposed solution has been practically implemented by developing the hardware and software as part of this research. This has been clearly brought out in the paper. The implementation has been tested using the actual ADS-B data/messages received from using the ADS-B receiver. The solution works perfectly, and this brings immense value to the aircraft-to-aircraft and aircraft-to-ground communications, specifically while using ADS-B data for communicating the position information. With the proposed architecture and minor software updates to the onboard avionics, this solution can enhance safety of flights.

A Radio Frequency Fingerprinting-Based Aircraft Identification Method Using ADS-B Transmissions

The automatic dependent surveillance broadcast (ADS-B) system is one of the key components of the next generation air transportation system (NextGen). ADS-B messages are transmitted in unencrypted plain text. This, however, causes significant security vulnerabilities, leaving the system open to various types of wireless attacks. In particular, the attacks can be intensified by simple hardware, like a software-defined radio (SDR). In order to provide high security against such attacks, radio frequency fingerprinting (RFF) approaches offer reasonable solutions. In this study, an RFF method is proposed for aircraft identification based on ADS-B transmissions. Initially, 3480 ADS-B samples were collected by an SDR from eight aircrafts. The power spectral density (PSD) features were then extracted from the filtered and normalized samples. Furthermore, the support vector machine (SVM) with three kernels (linear, polynomial, and radial basis function) was used to identify the aircraft. Moreover, the classification accuracy was demonstrated via varying channel signal-to-noise ratio (SNR) levels (10–30 dB). With a minimum accuracy of 92% achieved at lower SNR levels (10 dB), the proposed method based on SVM with a polynomial kernel offers an acceptable performance. The promising performance achieved with even a small dataset also suggests that the proposed method is implementable in real-world applications.

The effect of adopting the Next Generation Air Transportation System (NextGen) on air travel performance

The US Federal Aviation Administration (FAA) has implemented a large-scale multi-year infrastructure program called the Next Generation Air Transportation System (NextGen) to improve air transportation efficiency. To assess its efficacy, we estimate how NextGen projects completed between 2014 and 2017 affected air travel time and delays using an event study approach. We find sizable time savings in air travel time and delays from implementing NextGen. The time savings are more substantial for flights that experience unexpected shocks, such as poor weather and prior delays. In contrast, while NextGen seemed to close the performance gap between the hub and non-hub carriers generated by market power, the effect was short-lived and quickly reversed. Although we also find some small social benefits from carbon emission reductions, we cannot rule out that aggregate carbon emissions may have increased due to a rebound effect.

FUTURE AIR TRANSPORTATION RAMIFICATION: URBAN AIR MOBILITY (UAM) CONCEPT: URBAN AIR MOBILITY

Urban Air Mobility (UAM) is a new concept offered for solving urban transportation system problems, contributing to reducing traffic congestion, atmospheric pollution and mobility around metropolitan areas which is progressively an evolved aviation market. Facing the evolved dynamics in the airspace and on the ground, developed new technologies are able to withstand against destroy transportation infrastructures of the big cities, making it necessary to develop UAM services in the megapolises and regional transportation sector. Based on new technologies and modern business approaches, applying the next generation aviation infrastructure makes it capable of setting up a novel air traffic within the urban environment. This case study aims to explore the urban air transport advantages, particularly adoption of UAM, which might be an alternative next generation air transportation system. Referring to the collected operational data and design performances of the UAM, in this paper, we will try to describe a multi approach studying differences between traditional aviation transportation and UAM operation. The first step of the study consists of defining an airspace classification for UAM mission and use of applicable requirements for air navigation service providers and second part of the study describes performing UAM infrastructure and design of vertiports necessary for vertical take-off and landing (VTOL) vehicles. Detailed design specification is not included in this study but limited characteristics are indicated according to the VTOL manufacturer that are obtained from the test results. As far as VTOL vehicles have not started their mission yet, the UAM operators are at the stage of development to set up their future operation. The expected trend provides justifiable assumptions of the necessity of establishing the new transportation ramification within the aviation industry, upon transforming existing business activities and regulations.

Re-entry predictions of space debris for collision avoidance with air traffic

The need for a safe and efficient integration of space vehicle operations into air traffic system to minimize the risk of impacts of spacecraft and aircraft and to sustain a steady air traffic is evident. This work provides a strategy toward more efficient management of uncontrolled re-entries by combining uncertainty propagation analysis with the FAA’s ConOps in the framework of the FAA’s Next Generation Air Transportation System (NextGen). The paper considers the scenario where a spacecraft re-entry is completely uncontrolled. During such re-entry, predictions are very difficult and are affected by various sources of uncertainty. Then the resulting position distribution throughout airspace boundaries is analysed and the impact on air traffic is estimated by defining protected airspace areas. The impact of the size of the protected area on the air traffic control is analysed and strategies for re-routing of air traffic are proposed. To verify the proposed results, the re-entry of the core stage of the CZ-5B R/B launcher is simulated.

The Effect of Adopting the Next Generation Air Transportation System on Air Travel Performance

The Effect of Adopting the Next Generation Air Transportation System on Air Travel Performance

Situation Awareness Decision Support System for Air Traffic Management Using Ontological Reasoning

Air traffic management (ATM) is a vital service in air transportation provided by air traffic controllers (ATCs). Air traffic controllers and aircraft pilots are required to make increasingly difficult airspace decisions based on an ever-increasing number of information inputs, such as weather, flights, airspace, and reports. Additionally, proliferation of unmanned aerial systems raises concerns about safety and security (including cybersecurity) that challenge future airspace control. Additionally, ATM decision making requires dynamic situational awareness provided by mental cognitive faculties of airspace personnel. This paper presents a situation awareness (SAW) decision support system ATM reasoner (SAWDAR) approach to support decisional processes in ATM. The SAWDAR approach is based on artificial cognition implemented by means of knowledge representation (ontologies) and semantic reasoning. The ontological SAWDAR approach incorporates uncertainty considerations by including metrics for the veracity of surveillance systems, such as radars and automatic dependent surveillance-broadcast. By using the ontological SAW, experimental results demonstrate enhanced decision performance on airspace situations in a scenario, where an airplane is about to take off in the presence of potential hazardous drones flying around. The results demonstrate that the ontological SAWDAR approach can autonomously and dynamically support stakeholders (ATCs and pilots) to decide whether or not to allow aircraft takeoff. Concluding remarks and future research directions of avionics analytics ontology are also presented toward Next Generation Air Transportation System flight management.

Performance-Based Navigation Flight Path Analysis Using Fast-Time Simulation

The growing demand for air transportation has led to an increase in worldwide air traffic inefficiency due to capacity constraints. The impacts associated with this situation can be reduced through operational changes. To better handle the problem, the Single European Sky ATM Research (SESAR) and the Next Generation Air Transportation System (NextGen) program suggest Performance-Based Navigation (PBN) as a solution. The Area Navigation (RNAV) and Required Navigation Performance (RNP) approaches belong to the group of PBN procedures. These procedures allow for a more efficient use of airspace by reducing route distances, fuel consumption and perceived aircraft noise. This article quantifies the benefits of PBN systems for two indicator parameters—fuel burn and flight time—and compares PBN systems to conventional instrument navigation procedures. The case studies use five airports in Brazil. The results of this analysis show that the benefits of the PBN approach vary with aircraft type and individual route characteristics.

Tracking of Aircrafts Using Software Defined Radio (SDR) With An Antenna

Automatic Dependent Surveillance-Broadcast (ADS-B) is one in all the favoured technologies employed in air traffic surveillance. The ADS- B uses a band of 1090 MHz. ADS-B is attended with the prevailing radar-based technologies to locate aircraft. The Next Generation Air Transportation System (NGATS) conflicts can be detected and resolved by the coexistence of radar systems and ADS-B. Here we tend to track the aircraft using Software Defined Radio, hence the complexness and the value of ADS-B system implementation is drastically reduced. SDR can receive multiple numbers of aircraft information like altitude, latitude, longitude, speed, and direction in real-time and displayed by using an appropriate antenna. The usage of SDR maximizes the coverage of data with accuracy and may accomplish timely.

Uncertainty quantification and reduction in aircraft trajectory prediction using Bayesian-Entropy information fusion

Eliminating accidents while maintaining the integrity of the National Airspace System is one of the central objectives of the Next Generation Air Transportation System. This paper presents a Bayesian framework for accurate trajectory and accident prediction in National Airspace System using a high-fidelity trajectory simulation platform. Various uncertainties in aircraft trajectory prediction due to pilot behavior and weather effects are included as random variables in the simulations. Bayesian-Entropy method fuses available observation data (e.g., positioning system) with existing physical constraints (e.g. runway location) to update these simulation parameters. The posterior distributions of parameters are used to predict the probability of an adverse incident and time-remaining to incident. The proposed Bayesian updating scheme offers a flexible and rigorous way for adverse incident diagnostics and prognostics in current and future Air Traffic Management. Two realistic examples are given to show that it is possible to derive advance warning using the proposed methodology. The approach integrates data from a simulation model, with real-time traffic data streams and available physical constraints, using the Bayesian-Entropy information fusion methodology. This advance warning will allow the pilots/controllers to take actions to mitigate adverse incident in the National Airspace System.

The Next Generation Air Transportation System of the United States: Vision, Accomplishments, and Future Directions

Abstract To address concerns about anticipated increases in air traffic, leverage the capabilities of new technologies to enhance service, and accommodate new classes of airspace users, the U.S. Federal Aviation Administration and its partners embarked on a modernization effort known as the Next Generation Air Transportation System, or NextGen. NextGen encompasses a wide-range of improvements in communications, navigation, surveillance, and Air Traffic Management (ATM) automation systems. NextGen also includes many procedural improvements to leverage new technologies and advances in the science of ATM. This article describes the vision for NextGen, discusses the planning framework (including the business case for the investments), enumerates the major implementations to date, and describes the implementation challenges. Finally, the article discusses the future direction of NextGen.

How Air Traffic Control Intervention Effects Altitude Deviations on Optimized Profile Descent Arrivals

U.S. National Airspace System modernization began with the publication of the Next Generation Air Transportation System Integrated Plan (NextGen) in 2004 to accommodate forecast air travel demand increases in the United States. This framework proposed an integrated approach to safety, environmental sustainability, reduced fuel burn, and increased airspace and airport capacity by using automated capabilities. One of these capabilities, the Optimized Profile Descent (OPD) is an automated procedure created to link the en route phase of flight with the terminal area within the context of NextGen goals. This type of automated procedure was developed during the NextGen short phase (2004-2012) for both air traffic control and aircraft, but they continue to be used in a non-integrated manner. It is the confluence of incompatible automated and manual air traffic management techniques that produce a favorable location for an altitude deviation. The purpose of this study is to determine the effect of air traffic control intervention on altitude deviations reported during optimized profile descent arrival procedures in the U.S. National Airspace System from January 1, 2012 to January 1, 2018. Examination of aviation safety reports from this time period showed that air traffic control intervention did effect altitude deviations, specifically in the areas of aircrew error, communication error, and equipment malfunction or limitation. This analysis also demonstrated the failure of the altitude deviation rate to return to normal historic levels after the introduction of NextGen procedures, making altitude deviation a leading safety indicator for the U.S. National Airspace System.

Lower cost departures for airlines: Optimal policies under departure metering

Departure metering is an airport surface management procedure that limits the number of aircraft in the runway queue by holding aircraft either at a predesigned metering area or at gates. Field tests of the procedure have shown significant fuel savings, implying that the procedure can play an important role in the Next Generation Air Transportation System being implemented in the U.S. In this paper we study optimal departure operations at airports in the context of departure metering. More specifically, we develop a stochastic dynamic programming framework for tactical management of pushback operations at gates and for determining the optimal number of aircraft to be directed to the runway queue from the metering areas. We introduce four easy-to-implement departure metering policies, and perform comparative analyses between these practical policies and the numerical-optimization based policies. In addition, from a strategic perspective, we identify optimal capacities for metering areas to be used as part of departure metering implementations. Overall, we find that the annual fuel and operating savings for airlines could be around $1.7 million if our proposed policies are implemented at the Detroit Metropolitan Wayne County Airport. Such policies can also be adapted by other airports to improve the overall efficiency of surface traffic management and departure operations.

Implementation of Automatic Aircraft Tracking with RTL-SDR

To improve the efficiency, safety, and capacity of air space system, an Automatic Dependent Surveillance-Broadcast (ADS-B) is one of the popular technologies used in air traffic surveillance. The ADS-B uses 1090 MHz band. ADS-B is complemented by existing radar-based technologies to locate aircraft. The coexistence of radar systems and ADS-B is a key system to detect and resolve conflicts in the Next Generation Air Transportation System (NGATS). But, the major disadvantage of ADS-B is its implementation complexity and increase in cost without user-friendly. This paper focuses to reduce the complexity and cost of ADS-B system implementation in MATLAB with the help of Software Defined Radio (SDR). SDR is user-friendly and easy to handle aircraft information without increasing the cost. The ADS-B system implemented with SDR can receive the multiple numbers of aircraft information such as altitude, latitude, longitude, speed, and direction in real-time. Usage of SDR maximizes the information coverage with reliability and can achieve timely communication in Air Traffic Control (ATC) networks.

Context-Driven Autonomy for Enhanced System Resilience in Emergent Operating Environments

As higher degrees of operational autonomy are sought in engineered systems, resilient command and control (C2) capabilities are essential for mitigating performance degradation and disruptions. Autonomous C2 systems typically excel in performance optimization and failure-prevention within known or anticipated environments, but can exhibit poor efficacy given a lack of preemptive knowledge of needs and environments. This paper presents a context-driven decision engine for resilient C2 of engineered systems in emergent operating environments. The solution integrates diagnostic and prognostic heuristics to 1) assess system state of health (SoH) based on operational availability; 2) establish situational awareness; and 3) drive C2 decisions based on scenario-specific constraints and priorities. The solution is applied to an air traffic management problem for autonomous aircraft operations based on a Federal Aviation Administration Next Generation Air Transportation System (NextGen) concept. Agent-based modeling and Monte Carlo simulation are used to evaluate the incident rate ( λ ) and mission reliability ( $R_{M}$ ) of the proposed context-based solution against rule-based and utility-based C2 solutions, including the Radio Technical Commission for Aeronautics DO-185B standard and Dynamic A-star Lite (D* Lite) algorithm. Paired t -tests are used to compare approaches based on λ and $R_{M}$ given identical test cases. Results suggest that the proposed context-based solution can concurrently enhance threat avoidance and adaptation capabilities in emergent environments, whereas unilaterally optimized performance is observed via the rule-based and utility-based C2 solutions.

Multiple Model Method for Aircraft Conflict Detection and Resolution in Intent and Weather Uncertainty

This paper presents a novel multiple model (MM) method for aircraft conflict detection and resolution (CDR) in intent and weather uncertainty for the next generation air transportation system. It is based on probabilistic MM aircraft trajectory prediction. Conflict detection is performed through the use of predicted probability of conflict (PC). An improved algorithm for estimating PC is proposed and compared with a commonly used method. Conflict resolution (CR) is formulated as a stochastic model predictive control (MPC) problem subject to a constraint on the predicted PC to guarantee safety of the optimized CR trajectories. The cost function to be minimized is tailored to the CR problem and includes the cost of performing evasive maneuvers as well as the average cost incurred by extra travel distance to the destination due to the maneuvers. An efficient algorithm for finding the optimal path (maneuver sequence), with respect to the maneuver cost, is proposed and extended to an overall CDR optimization algorithm for the total cost, in order to produce optimized conflict-free CR trajectories. The proposed search algorithm is essentially a generalization of an optimal list Viterbi algorithm (for unconstrained minimization through a trellis) to the constrained case of our MPC-based CDR problem. The capability and computational efficiency of the proposed MM-CDR method (including PC prediction, optimal search, and overall CDR) are evaluated via comprehensive simulation of a large variety of unmanned aerial vehicle “sense-and-avoid” encounter scenarios, and are compared with existing methods in the literature.

Impact of multi-criteria optimized trajectories on European airline efficiency, safety and airspace demand

Today the European airspace is facing multiple capacity constraints which are regulating demand during busy traffic periods of the day. These capacity limits cause inefficiencies in flight and airport ground handling. Current market forecasts predict an annual growth in passenger air traffic demand between 4.5 percent and 4.8 percent. This growth will be realized by an increasing number of aircraft movements reflected in an expected annual growth of jet airplanes by 3.3 percent with a negative impact on airspace capacity. To better manage the rare airspace capacity, the Single European Sky ATM Research (SESAR) and the Next Generation Air Transportation System (NextGen) program suggest free route airspaces, a Performance Based Navigation (PBN) and harmonized airspace structures as efficient concepts of improvement in air traffic efficiency. Beside today's minimum fuel and time objectives, a growing public awareness of the anthropogenic environmental impact necessitates further functions for flight planning and execution. Additionally, today's high safety standards must not be negatively influenced by the introduction of free route airspaces. In this paper, we present a trajectory calculation model capable of exploiting a 4D free route optimization potential while considering the divergent targets of safety, efficiency and environmental compatibility. In particular, the environmental effects of condensation trails depending on the time of the day are carefully considered. To further estimate the impact of free routes on airspace demand and on safety issues, the model is implemented in the simulation environment TOMATO, and the European flight intentions have been optimized for an entire day based on departure airports, arrival airports and original departure times July 2016. The resulting trajectories are evaluated against the number, location and duration of separation infringements. Despite constantly changing air speeds and cruising altitudes induced by the optimization target functions, the number and duration of separation infringements could be reduced by 30% due to optimized lateral and vertical trajectories. The results of this case study show a high potential for an increased airspace capacity under free routing conditions. Furthermore, fuel burn (20%) and airline direct operational costs (40%) could be significantly reduced.

Evaluation of head-worn and head-up displays for use in enhanced flight vision system operations

Research, development, test, and evaluation of flight deck interface technologies is being conducted by NASA to proactively identify, develop, and mature tools, methods, and technologies for improving aviation safety of new and legacy vehicles operating in the Next Generation Air Transportation System (NextGen). One specific area of research was the use of small head-worn displays (HWDs) to serve as a possible equivalent to a head-up display (HUD) for commercial aircraft. A simulation experiment was conducted to evaluate if the HWD can provide an equivalent level of performance to a HUD. Airline flight crews conducted simulated approach and landing operations during low visibility operations. The results showed that there were no statistical differences in flight crews’ performance in terms of flight technical error suggesting that the HWD may serve as an equivalent display to the HUD. Further, the HWD may have several advantages over a HUD making its adoption an attractive alternative for commercial flight deck implementation. Technical hurdles remain to be overcome for complete display equivalence including, most notably, the end-to-end latency of the HWD system. The results and conclusions taken from the results of the high fidelity simulation experiment are described and offer future research directions.

Surrounding traffic complexity analysis for efficient and stable conflict resolution

The constant increase in air traffic demand increases a probability of the separation minima infringements in certain areas as a consequence of increased traffic density. The Annual Safety Report 2016 reports that in recent years the number of infringements, measured per million flight hours, had been increased at a lower rate (Eurocontrol, 2018). However, this level of infringements still generates a continuous pressure on the air traffic control (ATC) system and seeks for more control resources ready to tactically solve potential conflicts, while increasing at the same time the operational costs. Considering present air traffic management (ATM) trade-off criteria: increased airspace capacity and traffic efficiency but reducing the cost while preserving safety, new services must be designed to distribute the separation management ATC task loads among other actors. Based on the Single European Sky Air Traffic Management Research and Next Generation Air Transportation System initiatives, this paper proposes an innovative separation management service to shift the completely centralized tactical ATC interventions to more efficient decentralized tactical operations relying on an advanced surrounding traffic analysis tool, to preserve the safety indicators while considering the operational efficiency. A developed methodology for the proposed service is an application-oriented, trying to respond to characteristics and requirements of the current operational environment. The paper further analysis the traffic complexity taking into consideration the so-called domino effect, i.e. a number of the surrounding aircraft causally involved in the separation management service by the means of identification of the spatiotemporal interdependencies between them and the conflicting aircraft. This complexity is driven by the interdependencies structure and expressed as a time-criticality in quantifying the total number of the system solutions, that varies over time as the aircraft are approaching to each other. The results from two randomly selected ecosystem scenarios, extracted from a simulated traffic, illustrate different avoidance capacities for a given look-ahead time and the system solutions counts, that in discrete moments reach zero value.