Arrival Management Research Articles

Validating Flow-Based Arrival Management for En Route Airspace: Human-In-The-Loop Simulation Experiment with ESCAPE Light Simulator

The advancement of Arrival MANager (AMAN) is crucial for addressing the increasing complexity and demand of modern airspace. This study evaluates the operational feasibility and effectiveness of an innovative AMAN designed for en route airspace, the so-called En Route AMAN. The En Route AMAN functions as a controller support system, facilitating the sharing of information between en route air traffic controllers (ATCos), approach controllers (current AMAN), and airport controllers (Departure Managers) in airports with multiple runways. The En Route AMAN aims to support upstream ATCos by sequencing and spacing of incoming streams via speed control and runway assignment, thereby enhancing overall air traffic efficiency. Human-In-The-Loop simulations involving rated ATCos are performed under scenarios that replicate real-world traffic and weather conditions. These simulations focus on upstream airspace to assess the impact of En Route AMAN on delay mitigation and ATCos’ performance. Unlike previous studies that solely relied on theoretical models and fast-time simulation for operational feasibility evaluation, this approach incorporates ATCos’ real-time decision-making, situational awareness, and task management, addressing critical operationalization challenges. The results demonstrated that the En Route AMAN could reduce the average flight duration by up to 25.6 s and decrease the total number of ATCo instructions by up to 20% during peak traffic volume. These findings support that the En Route AMAN is both operationally viable and effective in mitigating arrival delays, highlighting the importance of Human-In-The-Loop for practical validation.

Efficient Bulk Arrival Management in Multi-Service Retrail Queues with Orbital search Leveraging Rabbit MQ

Efficient Bulk Arrival Management in Multi-Service Retrail Queues with Orbital search Leveraging Rabbit MQ

An analysis of the influence of preslaughter management factors on welfare and meat quality outcomes in fed beef cattle in the United States.

During the preslaughter phase, cattle are transported from their place of origin to a slaughter facility, experiencing transportation, lairage, environmental factors, and novel environments. Although research exists that has focused how the preslaughter phase impacts cattle welfare and meat quality, some significant preslaughter management factors and subsequent welfare and meat quality outcomes have not been thoroughly explored. The objective of this study was to assess the effects of preslaughter management factors on welfare and meat quality outcomes in fed beef cattle in the United States. Transportation factors, environmental characteristics, lairage factors, cattle characteristics, and several meat quality variables were collected from 5 federally inspected commercial processing facilities in the United States. After excluding slaughter lots that included <75% complete datasets, a total of 619 slaughter lots representing 84,508 head of cattle were used for further analysis. Predictor variables of interest included processing plant, cattle breed, sex class, operation shift at the plant, distance traveled to the plant, truck waiting time to unload at the plant, lairage duration and space allowance, temperature humidity index, and windspeed. Outcome variables of interest included cattle mobility, carcass bruising, dark cutting (DC), quality grades, and hot carcass weights. Logistic and linear regressions were used to analyze the associations between the predictor and outcome variables of interest. Increased distance traveled and truck waiting time were associated with higher odds of mobility impairment (P = 0.0009 and P = 0.007, respectively), with each 10 km increase in distance traveled having an odds ratio (OR) of 1.001 (95% confidence interval [CI]: 1.000 to 1.001) and each 1-min increase in waiting time having an OR of 1.003 (CI: 1.001 to 1.004). Conversely, a 10-km increase in distance traveled decreased the odds of carcass bruising (OR: 0.997, CI: 0.996 to 0.998; P < 0.0001). Longer lairage was associated with increased odds of DC (P = 0.0415), with each 60-min increase in duration having an OR of 1.034 (CI: 1.001 to 1.068). The results demonstrate the importance of truck arrival management (i.e., scheduling, prioritizing unloading) on mobility. Focusing on lairage management (i.e., density and time) may provide some opportunities to improve meat quality.

PERANCANGAN SISTEM INFORMASI TAMBAT LABUH KAPAL DI PELABUHAN PERIKANAN NUSANTARA KARANGANTU

The purpose of this study is to make it easier to access data and make reports needed by those who need it. The method used in this study is the waterfall model, which begins with research on the current system, design, coding, and maintenance of archive management systems so that archive management information and archive management reports can run quickly, precisely and accurately. The results obtained from this study are regarding the design of a mooring information system that is integrated with a database to support the process of managing ship arrivals and departures easily, quickly, and accurately. In making a ship's arrival and departure certificate, it can be documented into a database, so that it can make it easier if you want to report ship arrival and departure data. The conclusion that can be drawn from this information system is that archive management can be well documented because it is equipped with a database, storage has become a single unit, can reduce redundancy or duplicate data, can display required mooring management information so that it can facilitate officers in making arrival management reports. and ship departure.

Application of Severe Weather Nowcasting to Case Studies in Air Traffic Management

Effective and time-efficient aircraft assistance and guidance in severe weather environments remains a challenge for air traffic control. Air navigation service providers around the globe could greatly benefit from specific and adapted meteorological information for the controller position, helping to reduce the increased workload induced by adverse weather. The present work proposes a radar-based nowcasting algorithm providing compact meteorological information on convective weather near airports for introduction into the algorithms intended to assist in air-traffic management. The use of vertically integrated liquid density enables extremely rapid identification and short-term prediction of convective regions that should not be traversed by aircraft, which is an essential requirement for use in tactical controller support systems. The proposed tracking and nowcasting method facilitates the anticipation of the meteorological situation around an airport. Nowcasts of centroid locations of various approaching thunderstorms were compared with corresponding radar data, and centroid distances between nowcasted and observed storms were computed. The results were analyzed with Method for the Object-Based Evaluation from the Model Evaluation tools software (MET-10.0.1, Developmental Testbed Center, Boulder, CO, US) and later integrated into an assistance arrival manager software, showing the potential of this approach for automatic air traffic assistance in adverse weather scenarios.

Enabling Green Approaches by FMS-AMAN Coordination

Growing political pressure and widespread social concerns about climate change are triggering a paradigm shift in the aviation sector. Projects with the target of reducing aviation’s CO2 emissions and their impact on climate change are being launched to improve currently used procedures. In this paper, a new coordination process between aircraft flight management systems (FMSs) and an arrival manager (AMAN) was investigated to enable fuel-efficient and more sustainable approaches. This coordination posed two major challenges. Firstly, current capacity-centred AMANs’ planning processes are not optimised towards fuel-efficient trajectories. To investigate the benefit of negotiated trajectories with fixed target times for waypoints and thresholds, the terminal manoeuvring area was redesigned for an independent parallel runway system. Secondly, the FMS-AMAN negotiation process plan the trajectories based on time, whereas air traffic controllers guide traffic based on distance. Three tactical assisting tools were implemented in an air traffic controller’s working position to enable a smooth transition from distance-based to time-based coordination and guidance. The whole concept was implemented and tested in real-time human-in-the-loop studies at DLR’s Air Traffic Validation Center. Results showed that the new airspace design and concept was feasible, and a reduction in flown distance was measured.

A dynamic control method for extended arrival management using enroute speed adjustment and route change strategy

The continuous growth of air traffic leads to congestion in the surrounding area of airport. The optimization of the air traffic in this area requires the improvement of management strategies, especially for the arrival air traffic. SESAR has proposed the concept of Extended-Arrival MANagement (E-AMAN), which aims to plan the arrival streams from an earlier stage in order to achieve delay absorption and earlier planning in the en-route phases of flights. Based on this concept, we address a dynamic/on-line air traffic control problem to provide control decisions for flights in order to achieve safety and efficiency during arrival. The dynamic feature is realized by periodically updating the flight information for aircraft trajectory predictions. Sub-problems corresponding to each information update are established. The objective of this problem is to minimize the weighted sum of route congestion and the conflict resolution workload in the enroute segment, and the number of conflicts in the TMA (Terminal Maneuvering Area). A dynamic weight assignment approach is applied for ensuring that as an aircraft get closer to the TMA, its weight for TMA metrics increases accordingly. A case study based on the arrival traffic of the Paris Charles de Gaulle (CDG) airport is investigated by using a meta-heuristic simulated annealing algorithm combined with the rolling horizon approach. Final results are analyzed in terms of the reduction of concerned safety issues, final control decision distribution, and the time transferred through enroute decision change.

Innovative Integration of Severe Weather Forecasts into an Extended Arrival Manager

In the H2020 project “Satellite-borne and INsitu Observations to Predict The Initiation of Convection for ATM” (SINOPTICA), an air traffic controller support system was extended to organize approaching traffic even under severe weather conditions. During project runtime, traffic days with extreme weather events in the Po Valley were analyzed, an arrival manager was extended with a module for 4D diversion trajectory calculation, two display variants for severe weather conditions in an air traffic controller primary display were developed, and the airport Milano Malpensa was modelled for an air traffic simulation. On the meteorological side, three new forecasting techniques were developed to better nowcast weather events affecting tactical air traffic operations and used to automatically organize arrival traffic. Additionally, short-range weather forecasts with high spatial resolution were elaborated using radar-based nowcasting and a numerical weather prediction model with data assimilation. This nowcast information was integrated into the extended arrival manager for the sequencing and guiding of approaching aircraft even in adverse weather situations. The combination of fast and reliable weather nowcasts with a guidance support system enables severe weather diversion coordination in combination with a visualization of its dynamics on traffic situation displays.

Effectiveness of Aircraft Inter-Arrival Control in Upstream Traffic Flow via a Combined Tandem Fluid Queue Model and Integer Programming Approach

Conventionally, several studies indicated that controlling aircraft arrival time in the enroute airspace mitigates arrival aircraft congestion in the terminal airspace. Further research is required to clarify how to leverage this idea to design an air traffic management system, a so-called Extended Arrival MANager (E-AMAN), to reduce the arrival traffic flow while assisting air traffic controllers and boosting their effectiveness quantitatively. Under these circumstances, this research proposed aircraft inter-arrival time control within the en-route airspace and clarified its effectiveness in reducing arrival delay based on mathematical modeling and simulation evaluations. In this paper, we developed the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G_t/GI/s_t</i> + <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">GI</i> tandem fluid model to analyze the time-varying delay time of flights in both en-route and terminal airspace and demonstrated the effect of inter-arrival time control in the upstream arrival traffic flow in the en-route airspace, combining the model with the nonlinear integer programming problem. The calculation results for 3,074 aircraft over 21 days, arriving at Tokyo International Airport between 17:00 and 22:00, show the possibility for the control to reduce the mean and maximum delay time for flights by 18.8% (5.0 s) and 16.5% (37.6 s) on average within the en-route airspace. Moreover, fast-time simulation by AirTOP is conducted to validate the control, revealing the scope to reduce mean and maximum delay times in the terminal airspace by 11.5% (36.5 s) and 19.2% (148.8 s) on average.

Rule Design for Interpretable En Route Arrival Management via Runway-Flow and Inter-Aircraft Control

Rule Design for Interpretable En Route Arrival Management via Runway-Flow and Inter-Aircraft Control

연속강하운용을 이용한 궤적 기반의 항공기 도착 관리 효과 분석 연구

In this study, we propose trajectory-based arrival management using CDO (Continuos Descent Operations). The operational procedures with TBO (Trajectory-Based Operations) concept were established to allow aircraft and ground system to share the trajectories with each other in real time. The proposed operational concept was validated in the air traffic control simulation environment, which consists of controller working position, pseudo pilot system, air traffic generation system, and controllers’ decision support system for arrival management using CDO. Simulation results compared with actual flight data indicate that proposed concept could improve the efficiency of traffic flow management in terms of total descending time and fuel consumption. And it was confirmed that if there is a system that can share and utilize the synchronized trajectory, it can be helpful to control arrival aircraft and apply CDO concept.

Controlling Aircraft Inter-Arrival Time to Reduce Arrival Traffic Delay via a Queue-Based Integer Programming Approach

Despite the importance of controlling the inter-arrival times of flights to propose strategies for efficient arrival management by the Arrival Manager (AMAN), the specific guidelines of such adjustments and their effect on reducing delays have not been explicitly considered. Accordingly, this paper proposes a novel approach, which integrates the Gt/GI/st+GI time-varying fluid model and nonlinear integer programming to flatten the arrival rate at terminal gates. This, in turn, is achieved by minimizing the variance in inter-arrival times by penalizing any excessive change in arrival time, considering operational constraints. The results for Tokyo International Airport show potential to significantly reduce arrival traffic delays by minimizing said variance. This study may also spawn subsequent work, which builds a queuing network comprising upstream and terminal airspace and demonstrates the scope to reduce delays in the terminal airspace by controlling inter-arrival times at the upstream airspace.

Two-stage stochastic programming models for the extended aircraft arrival management problem with multiple pre-scheduling points

Extended aircraft arrival management under uncertainty has been previously studied in the literature using two-stage stochastic optimization in the case of a single initial approach fix (IAF) and a single runway. In this paper, we propose an extension taking into account: (i) multiple IAFs feeding the landing runway, (ii) aircraft having different initial flight status (at-departure-gate or airborne) when making first-stage decisions, and (iii) a time-deviation cost function to minimize that is based on reference values depending on aircraft type and flight phase. Two problem variants are modeled according to the degree of freedom on IAF assignment to aircraft. In the first variant, IAFs are to be assigned to aircraft, as a first-stage decision. In the second variant, IAF assignment is fixed and considered as a problem input. Numerical results on realistic instances from Paris Charles-de-Gaulle airport confirm the benefit of taking into account uncertainty through two-stage stochastic programming, and through re-assignment of IAFs.

Optimising truck arrival management and number of service gates at container terminals

Purpose Truck appointment systems have been applied in critical container ports in the United States due to their potential to improve handling operations. This paper aims to develop a truck appointment system to optimise the total cost experiencing at the entrance of container terminals by managing truck arrivals and the number of service gates satisfying a given level of service. Design/methodology/approach The approximation of Mt/G/nt queuing model is applied and integrated into a cost optimisation model to identify (1) the number of arrival trucks allowed at each time slot and (2) the number of service gates operating at each time slot that ensure the average waiting time is less than a designated time threshold. The optimisation model is solved by the Genetic Algorithm and tested with a case study. Its effectiveness is identified by comparing the model's outcomes with observed data and other recent studies. Findings The results indicate that the developed truck appointment system can provide more than threefold and twofold reductions of the total cost experiencing at the terminal entrance compared to the actual data and results from previous research, respectively. Originality/value The proposed approach provides applicably coordinated truck plans and operating service gates efficiently to decrease congestion, emission and expenses.

Identifying Operational Benefits of the Arrival Management System – A KPI-Based Experimental Method by Evaluating Radar Trajectories

The arrival management (AMAN) system is a decision support tool for air traffic controllers to establish and maintain the landing sequence for arrival aircraft. The original intention of designing the AMAN system is to improve the efficiency of air traffic management (ATM), but few studies are investigating the operational benefits of this system based on key performance indicators (KPIs) and evaluating actual data in a real-time environment. The main purpose of this paper is to propose a KPI based transferable comparative analysis method for identifying the operational benefits of the AMAN through radar trajectories. Firstly, six KPIs are established from a joint study of the mainstream ATM performance frameworks worldwide. Secondly, appropriate evaluation technique approaches are determined according to the characteristics of each KPI. Finally, a Chinese metropolitan airport is taken for the case study, and three periods are defined to form data samples with high similarity for comparative experiments. The results validate the feasibility of the proposed method and find comprehensive performance improvements in arrival operations under the effects of the AMAN system.

Automated sequencing and merging with dynamic aircraft arrival routes and speed management for continuous descent operations

In this paper, we present a novel methodology to manage arrival traffic in terminal airspace. We define two areas around the airport, aiming to efficiently schedule incoming traffic. A four-dimensional (4D) trajectory negotiation/synchronization process between the air traffic control officer (ATCO) and the aircraft is performed in the pre-sequencing area, while the aircraft are still in the en-route phase of flight. On the other hand, in the dynamic-trajectories area, the ATCO, with the help of a ground support tool, generates dynamic arrival routes that automatically adapt to the current traffic demand. These arrival routes allow the aircraft to fly neutral continuous descent operations (CDOs, descents with idle thrust and no speed-brakes usage) and to ensure a separation throughout the arrival procedure. We choose a mixed-integer-programming approach to generate the arrival routes, while we formulate and solve an optimal control problem to generate a set of candidate CDOs per aircraft. Results show that, with a sufficient look-ahead time, it is possible to assign a required time of arrival (RTA) within each aircraft-arrival time window that would allow to efficiently schedule traffic even in the most challenging and dense scenarios. Besides improving efficiency of current operations in terminal airspace, the methodology presented in this paper could become a technical enabler towards an extended arrival manager (E-AMAN) with extended capabilities and, ultimately, to a fully deployed trajectory based operations (TBO) environment.

Research on disruption management of urgent arrival in job shop with deteriorating effect

A disruption management method based on cumulative prospect theory is proposed for the urgent with deteriorating effect arrival in flexible job shop scheduling problem (FJSP). First, the mathematical model of problem is established with minimizing the completion time of urgent order, minimizing the total process time of the system and minimizing the total cost as the target. Then, the cumulative prospect theory equation of the urgent arrival in job shop scheduling process is induced designed. Based on the selected model, an optimized multi-phase quantum particle swarm algorithm (MQPSO) is proposed for selecting processing route. Finally, using Solomon example simulation and company Z riveting shop example as the study object, the performance of the proposed method is analyzed. It is compared with the current common rescheduling methods, and the results verify that the method proposed in this paper not only meets the goal of the optimized objects, but improves the practical requirements for the stability of production and processing system during urgent arrival. Lastly, the optimized multiphase quantum particle swarm algorithm is used to solve disruption management of urgent arrival problem. Through instance analysis and comparison, the effectiveness and efficiency of urgent arrival disruption management method with deteriorating effect are verified.

Benefits Derived from Arrival Management and Wake Turbulence Re-Categorization in China

Air traffic administration requires evidence when promoting new technology or a new concept of operation. Therefore, when decision support tools are applied, it is necessary to analyze the costs and benefits quantitatively. This paper focuses on the evaluation of Key Performance Indicators (KPIs) correlated with the improvement of arrival operations after the implementation of the Arrival Management (AMAN) system and Wake Turbulence Re-categorization in China (RECAT-CN). Firstly, we give an overview of the implementation of the AMAN system and RECAT in China. Secondly, the KPIs related to the arrival operation are established according to the characteristics of AMAN and RECAT-CN, based on the existing KPI systems in the field of Air Traffic Management (ATM). The proposed KPIs are: airport acceptance rate; final approach interval; flight time within the terminal area (TMA); and taxi-in time. Thirdly, arrival operation within the TMA around Guangzhou International Airport is used as an example to carry out the quantitative analysis. The region and time range were defined for the performance comparison, and external factors were also examined. Finally, using descriptive and inferential statistics, the proposed KPIs’ comparison results are presented and visualized. Such results indicate a significant improvement in arrival operation with the AMAN system and RECAT-CN at Guangzhou International Airport.

Network-wide assessment of ATM mechanisms using an agent-based model

This paper presents results from the SESAR ER3 Domino project. Three mechanisms are assessed at the ECAC-wide level: 4D trajectory adjustments (a combination of actively waiting for connecting passengers and dynamic cost indexing), flight prioritisation (enabling ATFM slot swapping at arrival regulations), and flight arrival coordination (where flights are sequenced in extended arrival managers based on an advanced cost-driven optimisation). Classical and new metrics, designed to capture network effects, are used to analyse the results of a micro-level agent-based model. A scenario with congestion at three hubs is used to assess the 4D trajectory adjustment and the flight prioritisation mechanisms. Two different scopes for the extended arrival manager are modelled to analyse the impact of the flight arrival coordination mechanism. Results show that the 4D trajectory adjustments mechanism succeeds in reducing costs and delays for connecting passengers. A trade-off between the interests of the airlines in reducing costs and those of non-connecting passengers emerges, although passengers benefit overall from the mechanism. Flight prioritisation is found to have no significant effects at the network level, as it is applied to a small number of flights. Advanced flight arrival coordination, as implemented, increases delays and costs in the system. The arrival manager optimises the arrival sequence of all flights within its scope but does not consider flight uncertainties, thus leading to sub-optimal actions.

Effects of departure manager and arrival manager systems on airport capacity

At an international level, interest in airport capacity has been growing in the last few years because its maximisation ensures best performance of infrastructure. Infrastructure, procedure and human factor constraints, however, should be considered to ensure a safe and regular flow of the flights. The paper presents the values of airport capacity obtained from two methodologies: the Advisory Circular AC 150/5060-5 and the Air Traffic Optimisation (AirTOp) fast time simulator (FTS). Two scenarios have been analysed: the ‘Baseline’ scenario (ie the current procedural and infrastructural airport layout) and the ‘What if ’ scenario (ie the current layout managed with Departure MANager and Arrival MANager systems). The simpler approach of the Federal Aviation Administration (FAA) advisory circular (AC) cannot model both the complex layout of the three-runway airport and the effects of planning tools. Its potential is limited to fast and preliminary analyses. Therefore, under knotty geometrical and procedural conditions, the use of aircraft delay simulation models or (FTS) models is the only tool that meets the needs of airport-management bodies. In particular, the current traffic volume of the examined airport is far from its Baseline capacity (−30 per cent) and is 40 per cent lower than the ‘What-if ’ capacity. The obtained results refer to the specific layout examined, but the pursued approach could be implemented at different airports.