Generation Air Traffic Management Research Articles

Aircraft Trajectory Prediction using LSTM Neural Network with Embedded Convolutional Layer

The development of convective weather avoidance algorithm is crucial for aviation operations and it is also a key objective of the next generation air traffic management system. This paper proposes a novel network architecture that embeds convolutional layers into long short-time memory (LSTM) cells to predict the trajectory, based on the convective weather condition along the flight plan before the aircraft takeoff. The data used in the experiments are history flight track data, the last on-file flight plan, and the time-dependent convective weather map. The history flight data are taken from NASA Sherlock database and the weather data used in this paper is the Echo Top (ET) convective weather product from Corridor Integrated Weather System (CIWS). The experiment is conducted using three months history data over the period from Nov 1, 2018 through Feb 5, 2019 with the flights from John F. Kennedy International Airport (JFK) to Los Angeles International Airport (LAX) but the methodology can be applied to the flights between any arbitrary two airports. Interpolation is performed on flight plans and real history tracks to fix the fold number of LSTM cell and also reduce computation complexity. The training loss is defined as the standard Mean Squared Error (MSE) of the predicted tracks and the real history tracks. Adam optimizer is used for backpropagation. Learning from the real historical flight data, the out-of-sample test shows that 47.0\% of the predicted flight tracks are able to reduce the deviation compared to the last on-file flight plan. The overall variance is reduced by 12.3\%.

A Novel Multi-Criteria Preamble Detection Algorithm for ADS-B Signals

Satellite-based automatic dependent surveillance broadcast (ADS-B) is of great importance in the next generation air traffic management system. However, there are two major challenges: interference and low signal to noise ratio (SNR). The interference can be mitigated by various separation algorithms. In this paper, we are committed to improving the detection performance for the ADS-B signals with downlink format field equal to 17 at low SNRs. At the moment, commercial receivers work well with sufficient SNRs but may not function properly in the case of the low SNRs. To this end, based on the characteristics of the ADS-B signal frame format, we propose a novel multi-criteria preamble detection algorithm. The proposed algorithm is a constant false alarm rate (CFAR) detection algorithm, and the determination of threshold is independent of noise power. We make a detailed theoretical analysis of each criterion, and develop the analytic expression of the detection probability. All the theoretical results are validated by the Monte Carlo simulations. The simulation shows that the proposed algorithm has an excellent probability of detection when the SNR is low, which is suitable for the satellite-based ADS-B application.

Sequential collaborative detection strategy on ADS-B data attack

Automatic Dependent Surveillance - Broadcast (ADS-B) surveillance is regarded as the core technology in the next generation air traffic management. Due to the absence of consideration on security, ADS-B data is faced with various challenges on integrity and authentication, especially for ADS-B data attack with high concealment. In this paper, common attack pattern models are analyzed. In terms of sequential ADS-B data, detection methods are designed according to flight and ground station capabilities, which integrate several detection methods, including flight plan validation, single node data detection and group data detection, to generate comprehensive attack probability as reference for judgment on data attack. To improve the positive detection ratio, ground to ground, ground to air and air to air collaborative detections are proposed to enhance each single node detection ability. Experiments conducted on real ADS-B data illustrated that the sequential collaborative detection strategy was efficient on effectiveness and accuracy, especially for random deviation injection attack, constant deviation injection attack and DoS attack.

Optimal Aircraft Trajectories to Minimize the Radiative Impact of Contrails and CO 2

The rapid growth of air traffic in the Asia Pacific region in the last decade has brought about the need for more sustainable modes of flight. A key initiative is the development of a Next Generation Air Traffic Management (NG-ATM) system which allows aircraft to fly optimal trajectories. Besides fuel- and time-related costs, other considerations for optimal routing include emissions, noise and contrails. Multi-Objective Trajectory Optimisation (MOTO) allows the generation of optimal trajectories with regards to these objectives, with dynamic weights depending on the phase of flight. Contrails are a major contributor to aviation's total Radiative Forcing (RF), being more significant than that of CO2. In particular, when formed in areas of low temperature and high relative humidity, contrails are known to persist for hours, spreading and eventually transitioning into cirrus clouds. Contrails trap heat by reflecting the long-wave infra-red radiation emitted by the earth back to its surface, producing positive RF. However, the albedo of contrails also reflects the incoming shortwave radiation from the sun, resulting in a negative component of RF. The impact of contrails, quantified by its associated RF, is thus not merely a function of environmental parameters but also a function of time. In this paper, a MOTO algorithm is used to generate optimal trajectories that minimize the radiative impact of contrails and CO2, while minimizing flight time and fuel burn. A case study of a transcontinental flight from Paris to Beijing is presented to demonstrate the feasibility of such an algorithm in providing strategic and tactical trajectory optimization capabilities.

Next Generation Flight Management System for Real-Time Trajectory Based Operations

This paper presents the concept of operations, architecture and trajectory optimisation algorithms of a Next Generation Flight Management System (NG-FMS). The NG-FMS is developed for Four Dimensional (4D) Intent Based Operations (IBO) in the next generation Communications, Navigation, Surveillance and Air Traffic Management system (CNS+A) context. The NG-FMS, primarily responsible for the aircraft navigation and guidance task, acts as a key enabler for achieving higher level of operational efficiency and mitigating environmental impacts both in manned and unmanned aircraft applications. The NG-FMS is interoperable with the future ground based 4DT Planning, Negotiation and Validation (4-PNV) systems, enabling automated Trajectory/Intent Based Operations (TBO/IBO). After the NG-FMS architecture is presented, the key mathematical models describing the trajectory generation and optimisation modes are introduced. A detailed error analysis is performed and the uncertainties affecting the nominal trajectories are studied to obtain the total NG-FMS error budgets. These are compared with the Required Navigation Performance (RNP) values for the various operational flight tasks considered.

Realities and challenges of nextgen air traffic management: the case of ADS-B

Air traffic is continuously increasing worldwide, with both manned and unmanned aircraft looking to coexist in the same airspace in the future. Next generation air traffic management systems are crucial in successfully handling this growth and improving the safety of billions of future passengers. The Automatic Dependent Surveillance Broadcast (ADS-B) system is a core part of this future. Unlike traditional radar systems, this technology empowers aircraft to automatically broadcast their locations and intents, providing enhanced situational awareness. This article discusses important issues with the current state of ADS-B as it is being rolled out. We report from our OpenSky sensor network in Central Europe, which is able to capture about 30 percent of the European commercial air traffic. We analyze the 1090 MHz communication channel to understand the current state and its behavior under the increasing traffic load. Furthermore, the article considers important security challenges faced by ADS-B. Our insights are intended to help identify open research issues, furthering new interest and developments in this field.

Time-based collision risk models for air traffic management systems

A finite supply of airspace and limited opportunities for expansion of physical infrastructure has led aviation authorities worldwide to commit substantial resources toward the development of new initiatives to accommodate rising demand in the global airspace system. The European Union is developing the Single European Sky , while a parallel program in the USA, the Next Generation Air Traffic Management System, or NextGen , is introducing systems and procedures that promise safer operations, increased efficiency, and environmental sustainability. This paper serves to present two enabling steps toward achievement of those objectives. The first is the establishment of a metric to express the time-based performance of aircraft operating in trajectory-based operations environments. The second is a pair of stochastic models that provide a method by which the collision risk between these aircraft may be determined. Application is then demonstrated for the purpose of illustrating how future capacity requirements may be managed while maintaining an adequate margin of safety. The paper concludes by providing insight into the nature of required time performance that will be necessary to support forecasted levels of air traffic.

An Efficient Broadcast Authentication Scheme with Batch Verification for ADS-B Messages

As a cornerstone of the next generation air traffic management (ATM), automatic dependent surveillance-broadcast (ADS-B) system can provide continual broadcast of aircraft position, identity, velocity and other messages over unencrypted data links to generate a common situational awareness picture for ATM. However, since ADS-B messages are unauthenticated, it is easy to insert fake aircrafts into the system via spoofing or insertion of false messages. Unfortunately, the authentication for ADS-B messages has not yet been well studied. In this paper, we propose an efficient broadcast authentication scheme with batch verification for ADS-B messages which employs an identity-based signature (IBS). Security analysis indicates that our scheme can achieve integrity and authenticity of ADS-B messages, batch verification, and resilience to key leakage. Performance evaluation demonstrates that our scheme is computationally efficient for the typical avionics devices with limited resources, and it has low communication overhead well suitable for low-bandwidth ADS-B data link.

System Wide Information Management Architecture Designing

As an important technical support platform of the next generation air traffic management concepts, Civil Aviation Wide Information Management System is responsible for providing various types of interactive information to relative business departments. This paper took SOA approach to analyze and design the function architecture of SWIM. And focused on the different technical approaches and deploying integration levels, it analyzed two kinds of SWIM technical architecture selections. This paper is funded by the National Science and Technology Supporting Program Civil Aviation Wide Information Management Technology and Platform (No. 2011BAH24B07) Project.

An Efficient Subcarrier Allocation Method for AeroMACS-Based Communication Systems

The work presented here deals with an IEEE 802.16e-based system for airport surface communications, named AeroMACS. Such a system has been proposed as a possible solution to satisfy the growing demand of new communication services and needs of next generation air traffic management (ATM) systems. By focusing on a specific airport environment, a resource allocation algorithm is proposed that allows the communication system capacity to be increased by exploiting the tap correlation related to each user communication channel. Optimal resource allocation using tap correlation has been previously shown to have a significant gain with respect to different alternatives, but also suffers from severe computational complexity. In order to relax this drawback, a novel suboptimal method is proposed that allows the implementation complexity to be lowered and the derivation of channel parameters to be made affordable, in particular in the case of fast varying propagation conditions or high estimation latency. The performance of the proposed algorithm is validated by comparisons with those achieved by the optimal approach and alternative solutions under different application conditions and users speed values. The final result shown here is a significant performance improvement for the proposed algorithm with respect to standard alternatives.

Exploring team sensemaking in air traffic control (ATC): insights from a field study in low visibility operations

Sensemaking helps teams coordinate their efforts to understand and anticipate events in uncertain situations. While it is recognized that breakdowns in team sensemaking can lead to incidents, next generation air traffic management (ATM) projects have not paid serious attention to this research topic. This article presents findings from an exploratory field study of team sensemaking in air traffic control for low visibility operations. The study uses the critical decision method and the data/frame model of sensemaking (Klein et al. in Expertise out of context: proceedings of the 6th international conference on naturalistic decision making. Erlbaum, Mahwah, 2007) as a theoretical basis for examining Tower and Approach operations that will be transformed by next generation ATM projects. The findings concern the elicitation of explanatory frameworks for making sense of low visibility operations, the identification of domain-specific strategies that shape sensemaking and the presentation of emergent requirements for team sensemaking. Implications are made for embedding operational experience into future ATM systems to improve collaborative decision making.

Fault Tree Analysis for Safety/Security Verification in Aviation Software

The Next Generation Air Traffic Management system (NextGen) is a blueprint of the future National Airspace System. Supporting NextGen is a nation-wide Aviation Simulation Network (ASN), which allows integration of a variety of real-time simulations to facilitate development and validation of the NextGen software by simulating a wide range of operational scenarios. The ASN system is an environment, including both simulated and human-in-the-loop real-life components (pilots and air traffic controllers). Real Time Distributed Simulation (RTDS) developed at Embry Riddle Aeronautical University, a suite of applications providing low and medium fidelity en-route simulation capabilities, is one of the simulations contributing to the ASN. To support the interconnectivity with the ASN, we designed and implemented a dedicated gateway acting as an intermediary, providing logic for two-way communication and transfer messages between RTDS and ASN and storage for the exchanged data. It has been necessary to develop and analyze safety/security requirements for the gateway software based on analysis of system assets, hazards, threats and attacks related to ultimate real-life future implementation. Due to the nature of the system, the focus was placed on communication security and the related safety of the impacted aircraft in the simulation scenario. To support development of safety/security requirements, a well-established fault tree analysis technique was used. This fault tree model-based analysis, supported by a commercial tool, was a foundation to propose mitigations assuring the gateway system safety and security.

Complexity analysis of the Next Gen Air Traffic Management System: trajectory based operations

According to Federal Aviation Administration traffic predictions currently our Air Traffic Management (ATM) system is operating at 150 percent capacity; forecasting that within the next two decades, the traffic with increase to a staggering 250 percent [17]. This will require a major redesign of our system. Today's ATM system is complex. It is designed to safely, economically, and efficiently provide air traffic services through the cost-effective provision of facilities and seamless services in collaboration with multiple agents however, contrary the vision, the system is loosely integrated and is suffering tremendously from antiquated equipment and saturated airways. The new Next Generation (Next Gen) ATM system is designed to transform the current system into an agile, robust and responsive set of operations that are designed to safely manage the growing needs of the projected increasingly complex, diverse set of air transportation system users and massive projected worldwide traffic rates. This new revolutionary technology-centric system is dynamically complex and is much more sophisticated than it's soon to be predecessor. ATM system failures could yield large scale catastrophic consequences as it is a safety critical system. This work will attempt to describe complexity and the complex nature of the NextGen ATM system and Trajectory Based Operational. Complex human factors interactions within Next Gen will be analyzed using a proposed dual experimental approach designed to identify hazards, gaps and elicit emergent hazards that would not be visible if conducted in isolation. Suggestions will be made along with a proposal for future human factors research in the TBO safety critical Next Gen environment.

Toward Air Traffic Complexity Assessment in New Generation Air Traffic Management Systems

The characterization of complex air traffic situations is an important issue in air traffic management (ATM). Within the current ground-based ATM system, complexity metrics have been introduced with the goal of evaluating the difficulty experienced by air traffic controllers in guaranteeing the appropriate aircraft separation in a sector. The rapid increase in air travel demand calls for new generation ATM systems that can safely and efficiently handle higher levels of traffic. To this purpose, part of the responsibility for separation maintenance will be delegated to the aircraft, and trajectory management functions will be further automated and distributed. The evolution toward an autonomous aircraft framework envisages new tasks where assessing complexity may be valuable and requires a whole new perspective in the definition of suitable complexity metrics. This paper presents a critical analysis of the existing approaches for modeling and predicting air traffic complexity, examining their portability to autonomous ATM systems. Possible applications and related requirements will be discussed.

Automation for task analysis of next generation air traffic management systems

The increasing span of control of Air Traffic Control enterprise automation (e.g. Flight Schedule Monitor, Departure Flow Management), along with lean-processes and pay-for-performance business models, has placed increased emphasis on operator training time and error rates. There are two traditional approaches to the design of human–computer interaction (HCI) to minimize training time and reduce error rates: (1) experimental user testing provides the most accurate assessment of training time and error rates, but occurs too late in the development cycle and is cost prohibitive, (2) manual review methods (e.g. cognitive walkthrough) can be used earlier in the development cycle, but suffer from poor accuracy and poor inter-rater reliability. Recent development of “affordable” human performance models provide the basis for the automation of task analysis and HCI design to obtain low cost, accurate, estimates of training time and error rates early in the development cycle. This paper describes a usability/HCI analysis tool that this intended for use by design engineers in the course of their software engineering duties. The tool computes estimates of trials-to-mastery (i.e. time to competence for training) and the probability of failure-to-complete for each task. The HCI required to complete a task on the automation under development is entered into the web-based tool via a form. Assessments of the salience of visual cues to prompt operator actions for the proposed design are used to compute training time and error rates. The web-based tool enables designers in multiple locations to review and contribute to the design. An example analysis is provided along with a discussion of the limitations of the tool and directions for future research.