Journal of Air Transportation
Total articles ≅ 124
Latest articles in this journal
Published: 11 November 2022
Journal of Air Transportation pp 1-10; https://doi.org/10.2514/1.d0298
Advanced air mobility operations are expected to significantly increase the demand for limited airspace resources. Two key features distinguish advanced air mobility operations from commercial avia...
Published: 27 October 2022
Journal of Air Transportation pp 1-17; https://doi.org/10.2514/1.d0255
Neural network approximations have become attractive to compress data for automation and autonomy algorithms for use on storage-limited and processing-limited aerospace hardware. However, unless th...
Published: 19 September 2022
Journal of Air Transportation pp 1-10; https://doi.org/10.2514/1.d0313
This paper proposes a new optimization scheme using neural networks for runway balancing to minimize departure and arrival aircraft delay. The delay prediction for runway balancing optimization is obtained by a neural network, only without any additional simulations. Developing an accurate simulation model under an uncertain environment is difficult, but the proposed neural network model can estimate the average delay without modeling uncertainty explicitly. In this paper, the effectiveness of the proposed method is validated through numerical simulations. First, simulations are used to generate the data, which are then used to train the neural network. Next, the runway balancing problem is solved via simulated annealing using the delay predicted by the neural network. The simulation result shows that the proposed approach outperforms the simulation-based method under an uncertainty environment. Therefore, the neural network is shown to accurately estimate the delay under the uncertainty environment, which makes the proposed neural-network-based method applicable to objective function calculations for optimization.
Published: 22 August 2022
Journal of Air Transportation pp 1-7; https://doi.org/10.2514/1.d0292
This was exploratory-in-nature follow-on research. The previous efforts focused on the operational impact of using a head-up display with localizer guidance in lieu of centerline lights for takeoff...
Published: 29 July 2022
Journal of Air Transportation pp 1-16; https://doi.org/10.2514/1.d0295
The forecasted increase in unmanned aerial vehicle (UAV) traffic in lower airspace raises concerns for maintaining the safety and efficiency of flight operations near towered airports. Regulatory bodies envision a collaborative interface between UAV traffic management and air traffic management to allow for coordinated operations of both systems. This study identifies the main challenges that such an environment poses for tower control. To address these challenges, an initial design for a collaborative tower control display is introduced. Remote human-in-the-loop simulations with professional air traffic controllers confirmed the usefulness of several interface elements (in particular, UAV priority and routing indications), as well as the utilization of a grid of geofences to dynamically segregate UAVs from manned aircraft. Surprisingly, the control strategy for geofence activation was similar to that of managing manned aircraft from a tower control perspective. Participants also mentioned that they would like more control over UAV traffic than initially expected. Performance could be improved by increasing predictability of UAV routing, adding conflict detection support as well as providing more authority over individual UAV locomotion supported by a tailored geofence structure. Further work is needed to investigate controller behavior in an environment that also requires control over manned traffic.
Published: 29 July 2022
Journal of Air Transportation pp 1-12; https://doi.org/10.2514/1.d0278
Urban air mobility (UAM) is a new mode of intracity transportation that promises to free commuters of ground congestion by providing air-taxi services within dense metropolitan environments. The in...
Published: 21 July 2022
Journal of Air Transportation pp 1-17; https://doi.org/10.2514/1.d0286
Loss of control in flight is the primary fatal accident category in general aviation. Forty-six fixed-wing United Kingdom accidents from 2018 and 2019 were analyzed to identify precursors, human factors, and possible reasons for unsuccessful recovery. Most of the events were nonfatal (82.6%), and most occurred during low-altitude flight phases: particularly, landings and go-arounds. Pilots under the age of 40 and over the age of 75 were disproportionately more likely to experience loss of control in flight. It was mostly precipitated by ineffective recovery from an upset, inadequate energy management, abnormal/inadvertent control inputs or maneuvers, or improper procedures. Insufficient height above the ground was a factor in most unsuccessful recoveries, followed by limited pilot capability. Fatal accidents were much more likely to be unrecoverable due to a hazardous mental or physical state or incorrect recognition of the situation. Decision- and skill-based human errors contributed to most events; more than half of the cases involved both errors. Fatal accidents were more complex in terms of preflight and latent human errors. These results informed a new definition of loss of control in flight for general aviation combined with a conceptual framework to inform future intervention strategies.
Published: 11 July 2022
Journal of Air Transportation pp 1-12; https://doi.org/10.2514/1.d0275
In this work, we project the idea of aerial passenger transport in the near future: on-demand urban air mobility (UAM) for the greater Munich area in the year 2030. We propose a simulation framewor...
Published: 6 July 2022
Journal of Air Transportation pp 1-11; https://doi.org/10.2514/1.d0308
Reviews of general aviation weather training curricula indicate gaps in how students experience different weather patterns and learn to correlate weather knowledge in weather-related situations. Au...
Published: 1 July 2022
Journal of Air Transportation, Volume 30, pp 91-101; https://doi.org/10.2514/1.d0306
With the rapid growth of global traffic flow, the flight anomalies caused by convective weather are becoming worse. More efficient traffic control measures can be implemented to improve airspace’s effective utilization and reduce the resulting ground and air waiting times if reroute optimization during cruise under convective weather can be realized before taking off. Based on vertical integrated liquid water, echo top, and flight altitude, this paper establishes a three-dimensional deviation probability distribution and defines a method of segment availability and capacity in convective weather. The optimization algorithms named Floyd, Rapidly-exploring Random Tree Star (RRT*), and informed-Rapidly-exploring Random Tree Star (Informed-RRT*) are used to minimize reroute distances. The deviation probability distribution is established based on 6146 historical flights under convective weather from 11 to 20 August 2018 in some upper area control centers under the administration of central and southern air traffic management bureaus. The Floyd and informed-RRT* algorithms are compared for reroute optimization for several flights in a given scenario. Based on the time to compute optimized reroutes and the quality of the reroute results, the Floyd algorithm is shown to provide the best rerouting optimization.