The difficulty of managing airspace is reflected in the complexity of forecasting its evolution. This paper presents a new neural network framework for managing images for which pixels are matrices with application to air traffic complexity map prediction. By modelling air traffic with a linear dynamical system, air traffic maps can be defined as images whose pixels are matrices. By computing intermediate steps, these air traffic maps are defined as images whose pixels are symmetric positive definite matrices. Then, we implement a convolution neural network with a specific data preprocessing step, new convolution, max-pooling, and flatten layers suitable to such images. The new convolution, max-pooling and flatten layers are capable of processing images coming from the data preprocessing step.

抄録全体を表示

To improve the prediction accuracy of traffic flow in terminal area, a traffic flow prediction model based on dif-ferent weather scenarios (TFPM-DWS) is proposed in this paper. First, a feature set for predicting traffic flow is extracted from terminal data of traffic demand, weather, and flow control strategy. Then, convolutional neural network (CNN) and K-Means++ algorithm are used to get the embedded spatial features and cluster weather avoidance field (WAF) images into some scenarios. Based on different scenarios, TFPM-DWS is constructed by using CNN and Gated Recurrent Unit (GRU). Finally, the proposed model is validated on the historic traffic data of Baiyun Airport. Its weather data is clustered into mild weather scenarios and severe weather scenarios, and the traffic flow characteristics under the two scenarios are analyzed. Further, traffic flow predictions at 1-hour intervals are performed for the traffic flows under different weather scenarios. The comparative experimental results show that the proposed traffic flow prediction model based on different weather scenarios has higher prediction accuracy than other existing traffic flow prediction methods for terminal areas.

抄録全体を表示

The Southwest Airlines scheduling crisis of December 2022 and its consequences have highlighted the importance of robust disruption recovery. To support advancements in schedule recovery, we present RecovAir, an Agent-Based Model that simulates the flow of aircraft, crew, and passengers in an airline’s flight network under departure and arrival rate limits and ad-hoc recovery strategies. By measuring Key Performance Indicators like On-Time Performance, cancellation count, and total delay, RecovAir quantifies simulation outcomes to support comparisons and controlled experiments with recovery parameters. We demonstrate RecovAir’s utility by synthesizing plausible scenarios for both the first day of the 2022 scheduling crisis and a day with zero cancellations in 2024 for Southwest Airlines. Using RecovAir, we simulate these scenarios while varying disruptions, recovery strategies, and a parameter that controls prioritization between delays and cancellations. Our results validate the implementation of RecovAir and show that a fast, greedy algorithm can perform nearly as well as Southwest Airlines’ actions on the first day of the scheduling crisis without initiating any ferry flights (i.e., non-revenue flights to reposition airline crew). We envision RecovAir as a platform on which researchers and airlines can evaluate recovery algorithms holistically and prepare for future disruptions.

抄録全体を表示

Time difference of arrival (TDOA) measurement is a proficient technique for enhancing the security of automatic dependent surveillance―broadcast (ADS-B). The method assesses the credibility of a reported position by measuring its TDOA across receivers, subsequently validating the coherence between the position and TDOA. For testing a spe-cific implementation of the method in research-and-development process, factory acceptance test, and site acceptance test, dedicated testing equipment is necessary. However, such testing equipment have not been discussed in the open literature. Therefore, this paper presents the testing equipment developed by the authors, which is capable of generating ADS-B signals with an adjustable TDOA.

抄録全体を表示

Currently, Automatic Dependent Surveillance-Broadcast (ADS-B) is used as one of the aircraft surveillance systems in Europe, the United States, and other regions. ADS-B messages are transmitted from transponders loaded on aircraft, which include position, altitude, velocity, and other operational information. The implemented information provides positional performance indexes of the Navigation Integrity Category (NIC) and Navigation Accuracy Category-Position (NACp). NIC and NACp values are required to meet operational performance to use ADS-B for aircraft surveillance. We installed an ADS-B receiver near Sendai airport to evaluate quality of ADS-B performance and developed analytical tool for them. This paper discusses our method for processing ADS-B data to estimate quality of ADS-B performance. Using our evaluation concept, statistical results of NIC and NACp are evaluated.

抄録全体を表示

This contribution discusses an architecture of a software defined radio setup and a general measurement principle for a multi-static radar system to be deployable at airport infrastructures. This project is a cooperative study of the Electronic Navigation Research Insititute (ENRI), Japan and the University of Applied Sciences (HTWK) Leipzig, Germany. Initial measurements are done for object localization in anechoic chambers based on the acquistion of a plurality of impulse responses. Particular focus is on the use of open source instruments and software defined radios, the synchronization of which is essential for the measurement of impulse responses.

抄録全体を表示

Terminal airspace trajectory clustering is a significant research topic, providing crucial decision-making support for airspace design, traffic management, and route planning. Currently, an advanced method for flight trajectory clus-tering involves using the latent space of autoencoders. While autoencoders excel in handling low-dimensional, simple data, the high dimensionality, complexity, and noise of terminal area flight trajectories pose challenges for data recon-struction. Therefore, this paper introduces the Deep Autoencoding Gaussian Mixture Model (DAGMM) to establish a new flight trajectory clustering model, aiming to uncover terminal airspace flow patterns. Using departure trajectories in the terminal airspace of Guangzhou Baiyun Airport in China as a case study, the effectiveness of the proposed clustering framework is validated through visualization of various trajectory distributions and the use of the t-SNE method to visualize trajectories in latent space.

抄録全体を表示

Quantitative methods are used alongside qualitative methods in Human-in-the-Loop experiments for operational feasibility evaluation of a novel air traffic control operations. In this study, we developed a complexity index that captures traffic flow characteristics. The developed index is calculated solely from traffic data, with the ability to express temporal and spatial complexity changes and variation in a given experiment. The utility of this metric was examined in a simulation experiment concerning an additional area control tool for Tokyo Haneda arrivals. The results show that the application of an en route arrival manager reduces the average value of the proposed complexity index based on the air traffic control characteristics of the arriving traffic flow by up to 16% and 9% on average. This was cross-confirmed by insights given by typical methods, such as the number of instructions given by controllers and qualitative feedback from controllers. Our proposed new indicators complemented the qualitative and subjective feedback from controllers, and quantified what controllers were unaware of over a wide range and long-term, enabled visual and objective discussions.

抄録全体を表示

This study proposes cognitive team task modeling for an Air Traffic Controller (ATC) team using Communicative NGOMSL and a modified cognitive model. The conversations of 12 professional ATCs during an ATC task simulation with three sectors were transcribed. As the first step of the Communicative NGOMSL method, the Hierarchical Task Analysis (HTA) of ATC is created from the transcriptions, and the communication pattern is figured out by applying a UML sequence diagram. The communicative NGOMSL can be utilized for teamwork analysis by analyzing the grounding process, the ratio of communication time to execution time for each team member to assess the efficiency of communication, and comparing learning time and mental workload among team members to understand the degree of balance in workload and capability. The results show that radar controllers (R) spend a higher execution time ratio than coordinators (C) do, and this difference depends on the sectors and the distribution of flight phases. Team Workload factor and the learning time ratio between roles show a high negative correlation, which means that the smaller the difference in learning time between R and C, the higher the team workload. A modified cognitive model that includes a grounding process is proposed.

抄録全体を表示

The Ionospheric modeling is a required step for the implementation of the Ground Based Augmentation System (GBAS), at low latitude zones this is particularly challenging due to the known ionospheric disturbances and their effects. Previously, single constellation ionospheric modeling using the time-step method has been performed in low latitudes, yet, as constellations grow, the multi-constellations assessment of this modeling including both Medium Earth Orbit (MEO) and Inclined Geosynchronous Orbit (IGSO) satellites is necessary considering the orbital characteristics of IGSO affecting the time-step method. In this study, the time-step method is applied to evaluate the nominal ionospheric conditions in the vicinity of an airport using GPS and BDS MEO constellations, additionally, we evaluate the case when IGSO satellites are included. These tests were based on the use of selected receivers from the National Continuously Operating Reference Stations Data Center (NCDC) of Thailand, which is a robust, multi-stakeholder network of GNSS receivers distributed throughout the kingdom. The results showed that the ionospheric modeling using GPS and BDS MEO agree with each other under nominal conditions, however, when IGSO satellites are to be included, some considerations in the time-step method should be taken due to its orbital characteristics.

抄録全体を表示

Technological progress such as glass cockpit has been introduced, however, it may also produce negative effects such as mismatches between pilots and flight deck systems, leading to human errors. Therefore, it is vital to develop adequate display formats aimed at reducing aviation accidents resulting from pilot errors, while contributing to the appropriate coexistence of pilots and automation systems. From the business viewpoint, it also requires to minimize rework in the late design stage, which poses a significant risk of schedule delays to timely introduce the product into the market. Therefore, methodologies and development processes that can finalize requirements specifications in the early design stages are required. In this study, we propose a display format design analysis method to utilize experiment data in the earliest stage and incorporate it to the V shape development process in addition to the early mockup evaluation methodology for risk-resilient display formats.

抄録全体を表示

Many airspace design concepts for integration of traditional crewed aircraft and new entrants such as drones and advanced air mobility aircraft are based on geo-fencing, i.e. constraining the aircraft flight within a certain operation volume or corridor. Such volumes are designed based on the predicted flight trajectory and a buffer which accounts for flight errors. Once the volumes are determined, the pilots need to control the aircraft within them. This research focuses on the lateral component and proposes a multi-layer volume deviation alert part of a situation awareness tool and based on the current flight position and tests the concept in a flight test using Japan Aerospace Exploration Agency’s experimental helicopter. Prior to the flight test, it was assumed that alerts at 100 m, 200 m and 300 m thresholds will enhance the flight safety without impacting the mission performance, but the results showed that the 100 m alert increases the pilot workload without contributing significantly to the volume conformance. It was demon-strated that the pilot was able to correct the course of the aircraft as soon as the alert was issued, verifying the effec-tiveness of the approach. Pilot feedback was also used to obtain directions for improved volume and alert design. The research confirmed that the multi-layer volume concept can be applied to enhance flight safety without increasing pilot workload, provided the operation volume and alerts are properly designed.

抄録全体を表示

Current air traffic flow management primarily relies on sector-based approaches, where controller workload represents a limiting factor airspace capacity. Moving sectors enable flow-centric traffic concepts and provide a solution for higher capacities. To evaluate effective air traffic concepts, complexity metrics serve as indirect measures of controller workload. This study applies three developed complexity metrics to the Japanese sector-based airspace, which serves as a benchmark for the evaluation of moving sectors. Our results indicate that moving sectors could reduce peak loads by aggregating homogeneous traffic flows. This could lead to increased airspace capacity. The various complexity metrics demonstrate positive correlations and the ability to identify peak loads. Subsequent research will focus on developing and implementing an operational framework for moving sectors, aiming to fully realize their operational advantages. We will develop and apply flow-centric operational concepts, specifically addressing aircraft handovers and interactions between moving sectors. These efforts will validate complexity metrics using human-in-the-loop experiments.

抄録全体を表示

Airport Collaborative Decision Making (A-CDM) is currently implemented to foster collaboration for efficient airport slot allocation. In the ASEAN region, where a central decision-making authority is not available, each airport reserves its autonomy in managing its own airport resources, which leads to different decision-making policies. An effective collaborative airport slot allocation approach needs to demonstrate its ability to collaborate with different slot allocation policies. Reinforcement Learning, a learning-based approach, can make use of interactions between airports to capture the underlying policies of other airports. In this paper, we consider a multi-airport system with different slot allocation policies, consisting of a Reinforcement Learning airport agent interacting with fixed-policy airport agents. We want to validate if the Reinforcement Learning agent can utilize interactions between airports to learn to reallocate slots efficiently under reduced capacity scenarios. We perform validation on the Hong Kong-Singapore-Bangkok hub, with the 2018 OAG data. The performance of the Reinforcement Learning agent is compared with the Nearest Heuristic, which assigns delays based on the nearest available slots. Results show that the Reinforcement Learning agent performs significantly better than the Nearest Heuristic under a heavy-reduced capacity scenario, with a total delay of 84 and 107, respectively. For a medium-reduced capacity scenario, the Reinforcement Learning agent closely resembles the performance of the Nearest Heuristic, with a total delay of 45 and 41, respectively.

抄録全体を表示

Airport security queues often suffer from inefficiencies that result in long wait times and decreased throughput, especially at peak departure time, affecting both passengers and airlines. Thiswork addresses the problem of reassigning passengers to specific time slots for crossing security, aiming to mitigate these inefficiencies. We frame this problem as a Minimum Cost Network Flow (MCNF) problem, enabling us to solve it exactly in polynomial time due to its linear programming structure. Our approach redistributes passenger demand across different time intervals. By optimizing the reassignment of passengers to 𝛿-minute time slots, we achieve significant improvements in throughput and reductions in waiting time. Preliminary results demonstrate the effectiveness of our method in enhancing operational efficiency and passenger satisfaction. The MCNF formulation offers a scalable and adaptable solution, providing long-term benefits for airport security management.

抄録全体を表示

This contribution present first in-situ nearfield measurements of a glide slope antenna array by means of an un-manned aerial vehicle as possible substitution or enhancement of nowadays performed regular flight inspection with aircraft. Presented measurements are part of the NAVANT-NG project, which addresses the aspects of measurement data acquisition with a tethered UAV and postprocessing of the data for obtaining the navigation signal properties in the coverage area according to specifications of the ICAO. Successful nearfield measurements in the vicinity of the navigation system with drones have the potential to substantially contribute to flight inspection procedures both in an economical and a scientific manner. A first assessment of the measurement results shows a successful data acquisition of magnitude and phase, which can be matched to the measurement position recorded by a GPS receiver mounted on the UAV. Finally, predicted glide slope signal results based on the near field measurement data are shown and discussed with respect to possible error contributions.

抄録全体を表示

The limited air-to-ground communication methods and tactical operation approaches of the current Air Traffic Control (ATC) system are difficult to satisfy the requirements of Trajectory-Based Operations (TBO) for effectively coordinating the 4-Dimensional Trajectory (4DT) across various systems and stakeholders. To improve the safety, operating economics, and environmental sustainability, a collaborative operational environment is required to share comprehensive information between aircraft and corresponding Air Traffic Management (ATM) components during all flight phases. This paper identifies the concept of connected aircraft, and clarifies approaches for achieving initial TBO by integrating tactical actions and strategic plannings. Furthermore, based on the live flight experiment, the validation of proposed approach to ensure consistency of 4DT between the aircraft and ground systems is presented. Finally, the lessons learned and requirements for cooperating between current ATC systems and SWIM-enabled systems via the connected aircraft are discussed and analyzed.

抄録全体を表示