9,226 research outputs found
Empirical exploration of air traffic and human dynamics in terminal airspaces
Air traffic is widely known as a complex, task-critical techno-social system,
with numerous interactions between airspace, procedures, aircraft and air
traffic controllers. In order to develop and deploy high-level operational
concepts and automation systems scientifically and effectively, it is essential
to conduct an in-depth investigation on the intrinsic traffic-human dynamics
and characteristics, which is not widely seen in the literature. To fill this
gap, we propose a multi-layer network to model and analyze air traffic systems.
A Route-based Airspace Network (RAN) and Flight Trajectory Network (FTN)
encapsulate critical physical and operational characteristics; an Integrated
Flow-Driven Network (IFDN) and Interrelated Conflict-Communication Network
(ICCN) are formulated to represent air traffic flow transmissions and
intervention from air traffic controllers, respectively. Furthermore, a set of
analytical metrics including network variables, complex network attributes,
controllers' cognitive complexity, and chaotic metrics are introduced and
applied in a case study of Guangzhou terminal airspace. Empirical results show
the existence of fundamental diagram and macroscopic fundamental diagram at the
route, sector and terminal levels. Moreover, the dynamics and underlying
mechanisms of "ATCOs-flow" interactions are revealed and interpreted by
adaptive meta-cognition strategies based on network analysis of the ICCN.
Finally, at the system level, chaos is identified in conflict system and human
behavioral system when traffic switch to the semi-stable or congested phase.
This study offers analytical tools for understanding the complex human-flow
interactions at potentially a broad range of air traffic systems, and underpins
future developments and automation of intelligent air traffic management
systems.Comment: 30 pages, 28 figures, currently under revie
Multilevel semantic analysis and problem-solving in the flight domain
A computer based cockpit system which is capable of assisting the pilot in such important tasks as monitoring, diagnosis, and trend analysis was developed. The system is properly organized and is endowed with a knowledge base so that it enhances the pilot's control over the aircraft while simultaneously reducing his workload
Towards Flight Trials for an Autonomous UAV Emergency Landing using Machine Vision
This paper presents the evolution and status of a number of research programs focussed on developing an automated fixed wing UAV landing system. Results obtained in each of the three main areas of research as vision-based site identification, path and trajectory planning and multi-criteria decision making are presented. The results obtained provide a baseline for further refinements and constitute the starting point for the implementation of a prototype system ready for flight testing
Aircraft Trajectory Planning Under Uncertainty by Light Propagation
AbstractIn the SESAR framework (Single European Sky ATM Research), the need to increase the air traffic capacity motivated the 4D (space + time) aircraft trajectory planning. This paper deals with an important Air Traffic Management (ATM) problem that consists in generating sets of 4D conflict-free trajectories (the tactical planning problem). The Light Propagation Algorithm (LPA) was introduced in [1] to deal with this problem. LPA has recently been shown to manage successfully a full day of traffic over the French airspace, removing all conflicts while satisfying ATM constraints.In this paper, we adapt the LPA to take into account uncertainties in trajectory prediction. We introduce and test a new algorithm called u/LPA (LPA under uncertainty) on the same day of traffic. For some situations, uncertainties reduce so much the search space that the standard algorithm cannot guarantee conflict free situation. As a consequence, one must include some time constraints for few trajectories (so-called RTA points: Real Time of Arrival constraints) in order to remove the remaining conflicts. The goal of RTA points is to impose an aircraft to be at a specified position at some given time. This results into a new optimization formulation of the tactical trajectory planning problem involving the decision as to where/when RTA points should be imposed. In order to solve this new problem, here we are content with a simple heuristic that yields encouraging results
Autonomous flight and remote site landing guidance research for helicopters
Automated low-altitude flight and landing in remote areas within a civilian environment are investigated, where initial cost, ongoing maintenance costs, and system productivity are important considerations. An approach has been taken which has: (1) utilized those technologies developed for military applications which are directly transferable to a civilian mission; (2) exploited and developed technology areas where new methods or concepts are required; and (3) undertaken research with the potential to lead to innovative methods or concepts required to achieve a manual and fully automatic remote area low-altitude and landing capability. The project has resulted in a definition of system operational concept that includes a sensor subsystem, a sensor fusion/feature extraction capability, and a guidance and control law concept. These subsystem concepts have been developed to sufficient depth to enable further exploration within the NASA simulation environment, and to support programs leading to the flight test
Flexible Stereo: Constrained, Non-rigid, Wide-baseline Stereo Vision for Fixed-wing Aerial Platforms
This paper proposes a computationally efficient method to estimate the
time-varying relative pose between two visual-inertial sensor rigs mounted on
the flexible wings of a fixed-wing unmanned aerial vehicle (UAV). The estimated
relative poses are used to generate highly accurate depth maps in real-time and
can be employed for obstacle avoidance in low-altitude flights or landing
maneuvers. The approach is structured as follows: Initially, a wing model is
identified by fitting a probability density function to measured deviations
from the nominal relative baseline transformation. At run-time, the prior
knowledge about the wing model is fused in an Extended Kalman filter~(EKF)
together with relative pose measurements obtained from solving a relative
perspective N-point problem (PNP), and the linear accelerations and angular
velocities measured by the two inertial measurement units (IMU) which are
rigidly attached to the cameras. Results obtained from extensive synthetic
experiments demonstrate that our proposed framework is able to estimate highly
accurate baseline transformations and depth maps.Comment: Accepted for publication in IEEE International Conference on Robotics
and Automation (ICRA), 2018, Brisban
Aeronautical Engineering: A continuing bibliography, supplement 120
This bibliography contains abstracts for 297 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1980
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