Method for evaluating the landing aircraft sequence under disturbed conditions with the use of Petri nets

2016 ◽  
Vol 120 (1227) ◽  
pp. 819-844 ◽  
Author(s):  
J. Skorupski ◽  
A. Florowski
Keyword(s):  
Petri Nets ◽  
Traffic Management ◽  
Control Strategies ◽  
Air Traffic ◽  
Control Algorithms ◽  
Air Traffic Controller ◽  
Airport Capacity ◽  
Evaluation Scores ◽  
Random Disturbances ◽  
Different Characteristics

ABSTRACTOne of the important tasks that air traffic management services are faced with today is the task of maximising airport capacity. This can be achieved at the tactical level through proper organisation of air traffic around an airport. In recent years, many methods and algorithms for scheduling aircraft landings have been developed; they take into account various optimisation goals. The aim of this paper was to create a method that would allow one to evaluate landing aircraft sequences resulting from these control algorithms, especially in the presence of random disturbances. This method involves modelling the landing aircraft sequence by using Petri nets. The model and the computer tool that have been developed make it possible to take into account different kinds of disturbances and examine the effectiveness of various control strategies under these conditions. This paper presents two experiments that test disturbances with different characteristics and of different intensities. It has been shown that small but more frequent disturbances lead to the worsening of evaluation scores for a given sequence to a lesser extent than rare but larger disturbances. This is particularly important for control algorithms in which the focus is on high aircraft density. If the type of particular disturbances is properly assessed, then it will be possible to assist the decision-maker (air traffic controller) by providing him/her with quantitative evaluations of possible solutions.

scholarly journals Modeling and Robustness Study of Railway Transport Networks Using P-Timed Petri Nets

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Anis Mhalla ◽  
Mohanned Gaied
Keyword(s):  
Petri Nets ◽  
Traffic Management ◽  
Control Strategies ◽  
Discrete Event ◽  
Transport Systems ◽  
Population Mobility ◽  
Railway Transport ◽  
Transport Networks ◽  
Modeling And Analysis ◽  
Increasing Demand

The importance of public transport systems continues to grow. These systems must respond to an increasing demand for population mobility and traffic disturbances. Rail transport networks can be considered as Discrete Event Systems (DES) with time constraints. The time factor is a critical parameter, since it includes dates to be respected in order to avoid overlaps, delays, and collisions between trains. P-time Petri Nets have been recognized as powerful modeling and analysis tools for railway transport systems. Temporal disturbances in these systems include railway infrastructure, traffic management, and disturbances (weather, obstacles on the tracks, malice, social movement, etc.). The developments presented in this paper are devoted to the modeling and the study of the robustness of the railway transport systems in order to evaluate the stability and the efficiency of these networks. In this study two robust control strategies towards time disturbances are presented. The first one consists of compensating the disturbance as soon as it is observed in order to avoid constraints violation. The second one allows generating, by the control, a temporal lag identical to the disturbance in order to avoid the death of marks on the levels of synchronization transitions of the P-time Petri net model.

scholarly journals Weather Impact on Airport Performance

Aerospace ◽  
2018 ◽  
Vol 5 (4) ◽  
pp. 109 ◽  
Author(s):  
Michael Schultz ◽  
Sandro Lorenz ◽  
Reinhard Schmitz ◽  
Luis Delgado
Keyword(s):  
Traffic Management ◽  
Probability Distributions ◽  
Weather Conditions ◽  
Air Traffic ◽  
Weather Data ◽  
Data Set ◽  
Airport Capacity ◽  
Weather Events ◽  
The Individual ◽  
The Impact

Weather events have a significant impact on airport performance and cause delayed operations if the airport capacity is constrained. We provide quantification of the individual airport performance with regards to an aggregated weather-performance metric. Specific weather phenomena are categorized by the air traffic management airport performance weather algorithm, which aims to quantify weather conditions at airports based on aviation routine meteorological reports. Our results are computed from a data set of 20.5 million European flights of 2013 and local weather data. A methodology is presented to evaluate the impact of weather events on the airport performance and to select the appropriate threshold for significant weather conditions. To provide an efficient method to capture the impact of weather, we modelled departing and arrival delays with probability distributions, which depend on airport size and meteorological impacts. These derived airport performance scores could be used in comprehensive air traffic network simulations to evaluate the network impact caused by weather induced local performance deterioration.

Dynamically Coloured Petri Nets for Air Traffic Management Safety Purposes

1997 ◽  
Vol 30 (8) ◽  
pp. 169-174 ◽  
Author(s):  
M.H.C. Everdij ◽  
H.A.P. Blom ◽  
M.B. Klompstra
Keyword(s):  
Petri Nets ◽  
Traffic Management ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Coloured Petri Nets

Effects of Air Traffic Congestion Delays under Several Flow-Management Policies

1996 ◽  
Vol 1517 (1) ◽  
pp. 29-36 ◽  
Author(s):  
Gregory D. Glockner
Keyword(s):  
Optimization Model ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Air Traffic ◽  
Practical Implementation ◽  
Model Framework ◽  
Flow Management ◽  
Traffic Demand ◽  
Airport Capacity ◽  
Facility Construction

Air traffic delays occur when demand for airports or airspace exceeds available capacity. Consequently, these delay effects can be lessened by increasing capacity or by modifying the air traffic demand. Increasing capacity is an important solution, but it is a long-range option involving major changes such as facility construction, fundamental procedural changes, and improvements in navigational equipment. For short-term decision making a tactical-optimization model can suggest alternative flight plans to reduce delays. However, a tactical-optimization model is extremely complex because of the uncertainty in airport-capacity forecasts, which primarily depend on weather. A practical implementation of a tactical-optimization model must therefore make approximations so that a solution may be computed quickly and be of good quality. A practical model framework for the congestion-delay problem is given; this model framework is a generalization of several other flow-management models. Congested situations are simulated, to compare the practical performance of this model to other air traffic management tactics.

scholarly journals Heading Toward Trusted ATCO-AI Systems: A Literature Review

2021 ◽  
Author(s):  
Jimmy Y. Zhong
Keyword(s):  
Artificial Intelligence ◽  
Traffic Management ◽  
Human Performance ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Air Traffic Controller ◽  
Current Review ◽  
Explainable Ai ◽  
Emerging Issues ◽  
Shed Light

The current review addresses emerging issues that arise from the creation of safe, beneficial, and trusted artificial intelligence–air traffic controller (AI-ATCO) systems for air traffic management (ATM). These issues concern trust between the human user and automated or AI tools of interest, resilience, safety, and transparency. To tackle these issues, we advocate the development of practical AI ATCO teaming frameworks by bringing together concepts and theories from neuroscience and explainable AI (XAI). By pooling together knowledge from both ATCO and AI perspectives, we seek to establish confidence in AI-enabled technologies for ATCOs. In this review, we present an overview of the extant studies that shed light on the research and development of trusted human-AI systems, and discuss the prospects of extending such works to building better trusted ATCO-AI systems. This paper contains three sections elucidating trust-related human performance, AI and explainable AI (XAI), and human-AI teaming.

scholarly journals Air Traffic Management during Rare Events Such as a Pandemic: Paris Charles de Gaulle Case Study

Aerospace ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 155
Author(s):  
Paolo Scala ◽  
Miguel Mujica Mota ◽  
Daniel Delahaye
Keyword(s):  
Traffic Management ◽  
Rare Events ◽  
Negative Impact ◽  
Public Information ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Aviation Industry ◽  
Charles De Gaulle ◽  
Airport Capacity ◽  
De Gaulle

Paris Charles de Gaulle Airport was the second European airport in terms of traffic in 2019, having transported 76.2 million passengers. Its large infrastructures include four runways, a large taxiway network, and 298 aircraft parking stands (131 contact) among three terminals. With the current pandemic in place, the European air traffic network has declined by −65% flights when compared with 2019 traffic (pre-COVID-19), having a severe negative impact on the aviation industry. More and more often taxiways and runways are used as parking spaces for aircraft as consequence of the drastic decrease in air traffic. Furthermore, due to safety reasons, passenger terminals at many airports have been partially closed. In this work we want to study the effect of the reduction in the physical facilities at airports on airspace and airport capacity, especially in the Terminal Manoeuvring Area (TMA) airspace, and in the airport ground side. We have developed a methodology that considers rare events such as the current pandemic, and evaluates reduced access to airport facilities, considers air traffic management restrictions and evaluates the capacity of airport ground side and airspace. We built scenarios based on real public information on the current use of the airport facilities of Paris Charles de Gaulle Airport and conducted different experiments based on current and hypothetical traffic recovery scenarios. An already known optimization metaheuristic was implemented for optimizing the traffic with the aim of avoiding airspace conflicts and avoiding capacity overloads on the ground side. The results show that the main bottleneck of the system is the terminal capacity, as it starts to become congested even at low traffic (35% of 2019 traffic). When the traffic starts to increase, a ground delay strategy is effective for mitigating airspace conflicts; however, it reveals the need for additional runways.

Information Manager for Determining Data Presentation Preferences in Future Enroute Air Traffic Management

1998 ◽  
Vol 42 (1) ◽  
pp. 47-51
Author(s):  
Jacqueline A. Duley ◽  
Scott M. Galster ◽  
Raja Parasuraman
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Information Needs ◽  
New Technologies ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Air Traffic Controller ◽  
Adaptive Automation ◽  
Presentation Frequency ◽  
Traffic Manager

One proposed vision of the future National Airspace System (NAS) involves a change in philosophy from that of air traffic control to one of air traffic management, i.e. Free Flight. In order to accommodate this philosophy change, new technologies will be implemented to assist the air traffic manager (today's air traffic controller) in decision making. When enhancing the system we must also consider the interface between the air traffic manager and this new system and its corresponding new philosophy. To better determine the design of such an interface we must first understand the information needs of the air traffic manager. The present study investigated the information requirements of 58 enroute air traffic controllers. The controllers provided their preferences in presentation frequency as well as the importance of the information to be displayed. The results reveal the potential for adaptive automation as a form of information management.

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