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

Low Growth Hormone Levels in Short-Stature Children with Pituitary Hyperplasia Secondary to Primary Hypothyroidism

Objective. The follow-up of GH levels in short-stature children with pituitary hyperplasia secondary to primary hypothyroidism (PPH) is reported in a few cases. We aimed to observe changes in GH secretion in short-stature children with PPH. Methods. A total of 11 short-stature children with PPH accompanied by low GH levels were included. They received levothyroxine therapy after diagnosis. Their thyroid hormones, IGF-1, PRL, and pituitary height were measured at baseline and 3 months after therapy. GH stimulation tests were performed at baseline and after regression of thyroid hormones and pituitary. Results. At baseline, they had decreased GH peak and FT3 and FT4 levels and elevated TSH levels. Decreased IGF-1 levels were found in seven children. Elevated PRL levels and positive thyroid antibodies were found in 10 children. The mean pituitary height was 14.3±3.8 mm. After 3 months, FT3, FT4, and IGF-1 levels were significantly increased (all p<0.01), and values of TSH, PRL, and pituitary height were significantly decreased (all p<0.001). After 6 months, pituitary hyperplasia completely regressed. GH levels returned to normal in nine children and were still low in two children. Conclusion. GH secretion can be resolved in most short-stature children with PPH

A comparative analysis of delay propagation on departure and arrival flights for a chinese case study

In recent years, flight delay costs the air transportation industry millions of dollars and has become a systematic problem. Understanding the behavior of flight delay is thus critical. This paper focuses on how flight delay is affected by operation-, time-, and weather-related factors. Different econometric models are developed to analyze departure and arrival delay. The results show that compared to departure delay, arrival delay is more likely to be affected by previous delays and the buffer effect. Block buffer presents a reduction effect seven times greater than turnaround buffer in terms of flight delays. Departure flights suffer more delays from convective weather than arrival flights. Convective weather at the destination airport for flight delay has a greater impact than at the original airport. In addition, sensitivity analysis of flight delays from an aircraft utilization perspective is conducted. We find that the effect of delay propagation on flight delay differs by aircraft utilization. This impact on departure delay is greater than the impact on arrival delay. In general, specific to the order of flights, the previous delay increases the impact on flight on-time performance as a flight flies a later leg. Buffer time has opposite effects on departure and arrival delay, with the order increasing. A decrease in buffer time with the order increasing, however, still has a greater reduction effect on departure delay than arrival delay. Specific to the number of flights operated by an aircraft, the more flights an aircraft flies in a day, the more the on-time performance of those flights will suffer from the previous delay and buffer time generally

Collision risk-capacity tradeoff analysis of an en-route corridor model

AbstractFlow corridors are a new class of trajectory-based airspace which derives from the next generation air transportation system concept of operations. Reducing the airspace complexity and increasing the capacity are the main purposes of the en-route corridor. This paper analyzes the collision risk-capacity tradeoff using a combined discrete–continuous simulation method. A basic two-dimensional en-route flow corridor with performance rules is designed as the operational environment. A second-order system is established by combining the point mass model and the proportional derivative controller together to simulate the self-separation operations of the aircrafts in the corridor and the operation performance parameters from the User Manual for the Base of Aircraft Data are used in this research in order to improve the reliability. Simulation results indicate that the aircrafts can self-separate from each other efficiently by adjusting their velocities, and rationally setting the values of some variables can improve the rate and stability of the corridor with low risks of loss of separation

How late does your flight depart? A quantile regression approach for a chinese case study

Flight departure delays cost airlines and airports millions of dollars and become a systematic problem. The on-time performance at an airport is connected to and easily affected by delay propagation from previous operations of flights using the airport. In this paper, we employ both Ordinary Least Square (OLS) and quantile regressions to investigate the impact of various influencing factors on flight departure delay. By using historical flight records and weather information, the impacts of delay propagation-related and other factors are quantified to study the correlations between the explanatory and response variables. Three variables, including previous arrival delay, turnaround buffer time, and the first order of a day, are used to examine the propagation effects. We find that aircraft type, flying on a weekday, and being the first flight of a day have significant impacts on short departure delays. Ground buffer is conducive to mitigating delay propagation. For long delays, however, ground buffer cannot work in an efficient way, and the previous arrival effect is more important. Convective weather and aircraft type are the crucial factors in this situation. Interestingly, flying on a weekday suddenly becomes one of the main components under extreme delays. Meanwhile, propagated delay and airport congestion remain significantly impactful on the on-time performance

The Behavior of Error Bounds via Moreau Envelopes

In this paper, we first establish the equivalence of three types of error bounds: uniformized Kurdyka-{\L}ojasiewicz (u-KL) property, uniformized level-set subdifferential error bound (u-LSEB) and uniformized H\"{o}lder error bound (u-HEB) for prox-regular functions. Then we study the behavior of the level-set subdifferential error bound (LSEB) and the local H\"{o}lder error bound (LHEB) which is expressed respectively by Moreau envelopes, under suitable assumptions. Finally, in order to illustrate our main results and to compare them with those of recent references, some examples are also given.Comment: 12 page

Morphing and Sampling Network for Dense Point Cloud Completion

3D point cloud completion, the task of inferring the complete geometric shape from a partial point cloud, has been attracting attention in the community. For acquiring high-fidelity dense point clouds and avoiding uneven distribution, blurred details, or structural loss of existing methods' results, we propose a novel approach to complete the partial point cloud in two stages. Specifically, in the first stage, the approach predicts a complete but coarse-grained point cloud with a collection of parametric surface elements. Then, in the second stage, it merges the coarse-grained prediction with the input point cloud by a novel sampling algorithm. Our method utilizes a joint loss function to guide the distribution of the points. Extensive experiments verify the effectiveness of our method and demonstrate that it outperforms the existing methods in both the Earth Mover's Distance (EMD) and the Chamfer Distance (CD).Comment: 8pages, 7 figures, AAAI202