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To explore the airspace structure and safety performance of unmanned aerial vehicle (UAV) system based on spatial digital twins (DTs), the study introduces DTs technology, and combines convolutional neural network (CNN) algorithm with UAV autonomous network. The DTs system of UAV is constructed by using wireless communication technology, and its security performance is simulated. The results show that in the analysis of the system packet loss rate, it is found that with the increase of the acquisition points, the amount of transmitted data only increases slightly, but the packet loss rate does not change significantly. In the analysis of the network performance of the unmanned aircraft system, it is found that the node energy-based weighted clustering algorithm (EWCA) can be used to increase the life of the overall network and enhance its availability by rationally controlling the number of nodes and the number of switching between clusters. As the number of nodes increases, the minimum survival time of each clustering algorithm decreases linearly. When the number of nodes is less than 600, the growth rate of cluster head is higher; When the number of nodes is more than 600, the curve growth is relatively smooth. In the analysis of the probability of network safety interruption, it is found that using the model constructed, when the energy acquisition coefficient is close to 0.5, the energy conversion efficiency is higher, the signal-to-noise ratio is larger. Also, when the number of intermediate nodes is increased to 10, the UAV has the best network safety performance. Therefore, through the research, it is found that the UAV DTs system constructed can significantly improve the safety performance of the UAV during its airspace flight. It can provide experimental references for the widespread application of the UAV in the later period. [ABSTRACT FROM AUTHOR]

Unmanned aircraft systems (UAS) generally use Global Navigation Satellite System (GNSS) measurements to estimate their state (position and orientation) for outdoor navigation. However, in urban environments, GNSS pseudorange measurements contain biases due to multipath effects and signal blockages by nearby buildings. For safe navigation in such environments, it is beneficial to predict the state uncertainty while accounting for the effect of measurement biases. Reachability analysis is a commonly used tool to predict the state uncertainty of a system. However, existing works do not account for the effect of measurement biases on state estimation, which consequently affects the predicted state uncertainty. Additionally, majority of the existing literature focuses on linear systems, whereas the dynamics of widely used practical systems are better captured by non-linear models. Thus, in this paper we present a non-linear stochastic reachability analysis to predict bounds on the state uncertainty while accounting for measurement biases. We derive the analysis for a fixed-wing UAS navigating using ranging measurements. In order to evaluate our predicted bounds for GNSS-based navigation, we simulate a 3D urban environment and the pseudorange biases due to multipath effects. We validate the predicted bounds for multiple trajectories in the simulated environment. Finally, we demonstrate the applicability of our predicted bounds towards ensuring safe UAS navigation in a shared airspace. [ABSTRACT FROM AUTHOR]

The introduction of ADS-B, a satellite-based aircraft tracking technology, and the increasing installation of ADS-B receiver stations around the globe eases the tracking of aircraft, compared with traditional solutions using secondary radar. Given the large scale of ADS-B implementation and the high frequency of data collection, storing and managing ADS-B induced data has become increasingly difficult: The worldwide ADS-B data easily aggregates to several hundreds of terabyte per year, depending on the spatial coverage and temporal resolution. Standard data management solutions do not work well for ADS-B data, since they either require a large uncompressed index structure or cannot be queried efficiently. In this paper, we propose a novel compressed index structure for managing ADS-B data, called ADS-BI. The essential building blocks are spatio-temporal reference partitioning, reordering, and compression. On top of the partitioned, compressed representation, metadata is stored effectively, and exploited during query answering for typical ATM related task such as trajectory adherence evaluation, as well as complexity and safety metrics assessment by only accessing parts of the compressed data as necessary. Our novel index structure is evaluated on worldwide ADS-B data for a week in November 2016. For comparison, we implemented ten standard compression/indexing methods. The experiments reveal that none of these traditional methods can target the sweet spot between a small storage and efficient query answering. Our novel technique provides fast query answering at smallest storage costs. This paper contributes toward efficient handling of the increasing amount of traffic data in air traffic management, and eventually, toward more efficient and safer air transportation. [ABSTRACT FROM AUTHOR]

This paper presents a study on short-term cooperative conflict detection and resolution (CDR) of unmanned aerial vehicles (UAVs). A two-layered CDR mechanism is proposed, which aims at guaranteeing safe separation, minimizing the overall cost of UAVs, and improving computational efficiency. In the first layer, the information from the environment is processed. In the second layer, conflicts among UAVs are resolved by applying the local centralized optimization method, with consideration given to the dynamic constraints of UAVs. This paper studies the safe separation constraints of pairwise conflicts in virtue of a geometry-based method. A heading change and speed change mixed conflict resolution approach is applied. To meet with the online planning requirements, the vectorized stochastic parallel gradient descent-based method is proposed to find the local optimal heading change solutions. The linear safe separation constraints on speeds are derived. A periodicity feature-based method is used to depart the feasible sub-regions for each pairwise conflict. A mixed integer linear programming model is established to find the optimal speed change solutions. The experiments results show that the proposed heading change algorithm could greatly reduce the summation of additional flight distances of UAVs, and influences on air traffic, compared with other short-term algorithms; the computational efficiency of this algorithm satisfies the online planning requirement. Comparing with the existing algorithm, our speed change algorithm reduces the number of feasible sub-regions to $2^{n_{c} }$ times lower, where $n_{c}$ is the number of pairwise conflict, and therefore, it reduces computation time dramatically. [ABSTRACT FROM AUTHOR]

Strategic air traffic management (SATM) problem, one of the critical tasks in air traffic operations, faces new challenges as the increased concerns on environmental impact and operation efficiency of the air transportation, and the system uncertainty increases due to the time-varying interference, such as the convective weather. To effectively address these challenges, we propose the formulation and solution of a generalized 4-D SATM problem for an air traffic system with convective weather uncertainty. The proposed SATM problem formulation is computationally tractable and the schedule results can realize the avoidance of the convective weather with more than a tolerable risk probability. We provide a solution approach to tackle this problem with complex mathematical basics and illustrate the capabilities of the proposed mixed integer solution approach on the real regional air traffic system operated by the China civil aviation administration. Numerical results demonstrate the effectiveness of the proposed solution approach. [ABSTRACT FROM AUTHOR]

This paper discusses a unique formulation for the en-route flight planning problem in a constrained airspace with the objective to minimize costs incurred from earliness, lateness, and fuel-consumption, and to ensure flight safety. Mid-air conflict and collision avoidance, and also minimum separation distance between aircraft and speed-dependent fuel-consumption-rate, are explicitly formulated. A 3D mesh network consisting of waypoints is used to provide alternative routing options for aircraft. The formulation of fuel-consumption-rate as a function of speed as part of the air-traffic planning (ATP) problem is unique in the literature. Moreover, this paper is the first attempt to model the mid-air conflict and collision avoidance as part of the ATP problem. In order to demonstrate the capabilities of the mathematical model, test instances were generated and solved by three different solution strategies. The proposed centralized solution strategy can optimally solve small size instances, similar to the air-traffic around airports to help air-traffic control authorities to manage arrival and departure sequences. Larger networks that include several airports can be solved by the proposed two sequential solution strategies (decentralized and hybrid solution strategies) to help air-traffic planning authorities to manage air-traffic safely and more economically. [ABSTRACT FROM AUTHOR]

Airspace capacity is limited primarily by the saturation of air traffic controller’s capacity, whose workload increases as air traffic complexity increases. Workload can be reduced through task automation by advanced controller tools. Automation and the development of novel controller tools is therefore one of the key aspects of future concepts of operations in European and American air traffic management systems. Implementation of trajectory-based operations (TBOs) has been proposed as a way to reduce workload, but few studies have examined how TBO affects air traffic complexity. This paper compares air traffic complexity experienced by ten air traffic controllers in a real-time simulation environment involving conventional operations and TBO. Analysis of subjective complexity scores collected in real time showed that TBO significantly reduced complexity when at least 70% of aircraft were flying according to TBO and when the airspace was occupied simultaneously by more than 15 aircraft. Subjective complexity scores were tested for correlation with 20 commonly used complexity indicators, and six indicators were used to generate a predictive linear model that performed well in conventional operations but less well under TBO. Therefore, we defined and experimentally validated two of seven novel TBO-specific complexity indicators. A second correlation model combining these two novel indicators with four already in use generated much better predictions of complexity than the first model. [ABSTRACT FROM PUBLISHER]

More than a dozen wireless technologies are used by air traffic communication systems during different flight phases. From a conceptual perspective, all of them are insecure, as security was never part of their design. Recent contributions from academic and hacking communities have exploited this inherent vulnerability to demonstrate attacks on some of these technologies. However, not all of these contributions have resonated widely within aviation circles. At the same time, the security community lacks certain aviation domain knowledge, preventing aviation authorities from giving credence to their findings. In this survey, we aim to reconcile the view of the security community and the perspective of aviation professionals concerning the safety of air traffic communication technologies. To achieve this, we first provide a systematization of the applications of wireless technologies upon which civil aviation relies. Based on these applications, we comprehensively analyze vulnerabilities and existing attacks. We further survey the existing research on countermeasures and categorize it into approaches that are applicable in the short term and research of secure new technologies deployable in the long term. Since not all of the required aviation knowledge is codified in academic publications, we additionally examine the existing aviation standards and survey 242 international aviation experts. Besides their domain knowledge, we also analyze the awareness of members of the aviation community concerning the security of wireless systems and collect their expert opinions on the potential impact of concrete attack scenarios using these technologies. [ABSTRACT FROM PUBLISHER]

The majority of reported near-midair collisions that involve a general aviation aircraft occur in the vicinity of nontowered airports. A prior work has investigated the feasibility of creating an automated air traffic control system for these nontowered airports using solutions to a partially observable Markov decision process. Validating such system will require an accurate model of aircraft behavior in the traffic pattern. This paper evaluates the different approaches for deriving traffic pattern models from recorded radar data. The first approach is based on prior trajectory clustering work, where turning points in trajectories are identified and clustered. This method performs well on simulated data, but due to its reliance on noisy heading rates, it has difficulty with real-world data. The second approach uses Bayesian inference techniques to learn the parameters of the traffic pattern model, where a hidden semi-Markov model with a hierarchical Dirichlet process as a prior is investigated. Inference in this model is made computationally tractable using Markov chain Monte Carlo methods. The turning point and Bayesian models are compared with each other using different $f$- divergence measures, and the latter is found to better represent the observed data. [ABSTRACT FROM PUBLISHER]

This paper studies the problem of aircraft midair conflict resolution, which is a key technology to enable the coordinated and decentralized air traffic control envisioned in the Next Generation Air Transportation System (NextGen). The method proposed in this paper is based on stochastic optimal control, which is able to incorporate uncertainties in both aircraft and wind dynamics. The proposed numerical algorithm uses a Markov chain (MC) to approximate the continuous-time aircraft and wind dynamics, then the optimal control law is derived based on the MC. The proposed algorithm is able to resolve the conflicts between aircraft and moving convective weather regions. For conflict resolution between pairs of aircraft, a decomposition technique is proposed to reduce the computational complexity of the numerical algorithm. Simulations show that the proposed algorithm provides robustness against uncertainties in the system and is suitable for real applications. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]