The effects of pushback delays on airport ground movement

With the constant increase in air traffic, airports are facing capacity problems. Optimisation methods for specific airport processes are starting to be increasingly utilised by many large airports. However, many processes do happen in parallel, and maximising the potential benefits will require a more complex optimisation model, which can consider multiple processes simultaneously and take into account the detailed complexities of the processes where necessary, rather than using more abstract models. This paper focuses on one of these complexities, which is usually ignored in ground movement planning; showing the importance of the pushback process in the routing process. It investigates whether taking the pushback process into consideration can result in the prediction of delays that would otherwise pass unnoticed. Having an accurate model for the pushback process is important for this and identifying all of the delays that may occur can lead to more accurate and realistic models that can then be used in the decision making process for ground movement operations. After testing two different routing methods with a more detailed pushback process, we found that many of the delays are not predicted if the pushback process is not explicitly modelled. Having a more precise model, with accurate movements of aircraft is very important for any integrated model and will allow ground movement models to be of use in more reliable integrated decision making systems at airports. Minimising these delays can help airports increase their capacity and become more environmentally friendly

The effects of pushback delays on airport ground movement

With the constant increase in air traffic, airports are facing capacity problems. Optimisation methods for specific airport processes are starting to be increasingly utilised by many large airports. However, many processes do happen in parallel, and maximising the potential benefits will require a more complex optimisation model, which can consider multiple processes simultaneously and take into account the detailed complexities of the processes where necessary, rather than using more abstract models. This paper focuses on one of these complexities, which is usually ignored in ground movement planning; showing the importance of the pushback process in the routing process. It investigates whether taking the pushback process into consideration can result in the prediction of delays that would otherwise pass unnoticed. Having an accurate model for the pushback process is important for this and identifying all of the delays that may occur can lead to more accurate and realistic models that can then be used in the decision making process for ground movement operations. After testing two different routing methods with a more detailed pushback process, we found that many of the delays are not predicted if the pushback process is not explicitly modelled. Having a more precise model, with accurate movements of aircraft is very important for any integrated model and will allow ground movement models to be of use in more reliable integrated decision making systems at airports. Minimising these delays can help airports increase their capacity and become more environmentally friendly

The effects of pushback delays on airport ground movement

With the constant increase in air traffic, airports are facing capacity problems. Optimisation methods for specific airport processes are starting to be increasingly utilised by many large airports. However, many processes do happen in parallel, and maximising the potential benefits will require a more complex optimisation model, which can consider multiple processes simultaneously and take into account the detailed complexities of the processes where necessary, rather than using more abstract models. This paper focuses on one of these complexities, which is usually ignored in ground movement planning; showing the importance of the pushback process in the routing process. It investigates whether taking the pushback process into consideration can result in the prediction of delays that would otherwise pass unnoticed. Having an accurate model for the pushback process is important for this and identifying all of the delays that may occur can lead to more accurate and realistic models that can then be used in the decision making process for ground movement operations. After testing two different routing methods with a more detailed pushback process, we found that many of the delays are not predicted if the pushback process is not explicitly modelled. Having a more precise model, with accurate movements of aircraft is very important for any integrated model and will allow ground movement models to be of use in more reliable integrated decision making systems at airports. Minimising these delays can help airports increase their capacity and become more environmentally friendly

Towards a more realistic, cost effective and greener ground movement through active routing: part 1 - optimal speed profile generation

Among all airport operations, aircraft ground movement plays a key role in improving overall airport capacity as it links other airport operations. Moreover, ever increasing air traffic, rising costs and tighter environmental targets create a pressure to minimise fuel burn on the ground. However, current routing functions envisioned in Advanced Surface Movement, Guidance and Control Systems (A-SMGCS) almost exclusively consider the most time efficient solution and apply a conservative separation to ensure conflict free surface movement, sometimes with additional buffer times to absorb small deviations from the taxi times. Such an overly constrained routing approach may result in either a too tight planning for some aircraft so that fuel efficiency is compromised due to multiple acceleration phases, or performance could be further improved by reducing the separation and buffer times. In light of this, Part 1 and 2 of this paper present a new Active Routing framework with the aim of providing a more realistic, cost effective and environmental friendly surface movement, targeting some of the busiest international hub airports. Part 1 of this paper focuses on optimal speed profile generation using a physics based aircraft movement model. Two approaches based respectively on the Base of Aircraft Data (BADA) and the International Civil Aviation Organization (ICAO) engine emissions database have been employed to model fuel consumption. These models are then embedded within a mutli-objective optimization framework to capture the essence of different speed profiles in a Pareto optimal sense. The proposed approach represents the first attempt to systematically address speed profiles with competing objectives. Results reveal an apparent trade-off between fuel burn and taxi times irrespective of fuel consumption modelling approaches. This will have a profound impact on the routing and scheduling, and open the door for the new concept of Active Routing discussed in Part 2 of this paper

Two-stage combinatorial optimization framework for air traffic flow management under constrained capacity

Air traffic flow management is a critical component of air transport operations because at some point in time, often very frequently, one of more of the critical resources in the air transportation network has significantly reduced capacity, resulting in congestion and delay for airlines and other entities and individuals who use the network. Typically, these “bottlenecks” are noticed at a given airport or terminal area, but they also occur in en route airspace. The two-stage combinatorial optimization framework for air traffic flow management under constrained capacity that is presented in this thesis, represents a important step towards the full consideration of the combinatorial nature of air traffic flow management decision that is often ignored or dealt with via priority-based schemes. It also illustrates the similarities between two traffic flow management problems that heretofore were considered to be quite distinct. The runway systems at major airports are highly constrained resources. From the perspective of arrivals, unnecessary delays and emissions may occur during peak periods when one or more runways at an airport are in great demand while other runways at the same airport are operating under their capacity. The primary cause of this imbalance in runway utilization is that the traffic flow into and out of the terminal areas is asymmetric (as a result of airline scheduling practices), and arrivals are typically assigned to the runway nearest the fix through which they enter the terminal areas. From the perspective of departures, delays and emissions occur because arrivals take precedence over departures with regard to the utilization of runways (despite the absence of binding safety constraints), and because arrival trajectories often include level segments that ensure “procedural separation” from arriving traffic while planes are not allowed to climb unrestricted along the most direct path to their destination. Similar to the runway systems, the terminal radar approach control facilities (TRACON) boundary fixes are also constrained resources of the terminal airspace. Because some arrival traffic from different airports merges at an arrival fix, a queue for the terminal areas generally starts to form at the arrival fix, which are caused by delays due to heavy arriving traffic streams. The arrivals must then absorb these delays by path stretching and adjusting their speed, resulting in unplanned fuel consumption. However, these delays are often not distributed evenly. As a result, some arrival fixes experience severe delays while, similar to the runway systems, the other arrival fixes might experience no delays at all. The goal of this thesis is to develop a combined optimization approach for terminal airspace flow management that assigns a TRACON boundary fix and a runway to each flight while minimizing the required fuel burn and emissions. The approach lessens the severity of terminal capacity shortage caused by and imbalance of traffic demand by shunting flights from current positions to alternate runways. This is done by considering every possible path combination. To attempt to solve the congestion of the terminal airspace at both runways and arrival fixes, this research focuses on two sequential optimizations. The fix assignments are dealt with by considering, simultaneously, the capacity constraints of fixes and runways as well as the fuel consumption and emissions of each flight. The research also develops runway assignments with runway scheduling such that the total emissions produced in the terminal area and on the airport surface are minimized. The two-stage sequential framework is also extended to en route airspace. When en route airspace loses its capacity for any reason, e.g. severe weather condition, air traffic controllers and flight operators plan flight schedules together based on the given capacity limit, thereby maximizing en route throughput and minimizing flight operators' costs. However, the current methods have limitations due to the lacks of consideration of the combinatorial nature of air traffic flow management decision. One of the initial attempts to overcome these limitations is the Collaborative Trajectory Options Program (CTOP), which will be initiated soon by the Federal Aviation Administration (FAA). The developed two-stage combinatorial optimization framework fits this CTOP perfectly from the flight operator's perspective. The first stage is used to find an optimal slot allocation for flights under satisfying the ration by schedule (RBS) algorithm of the FAA. To solve the formulated first stage problem efficiently, two different solution methodologies, a heuristic algorithm and a modified branch and bound algorithm, are presented. Then, flights are assigned to the resulting optimized slots in the second stage so as to minimize the flight operator's costs.Ph.D

Simulation und Optimierung von Flugzeug-Groundverkehr mit Hilfe von Zellularautomatenmodellen am Beispiel des Flughafens Düsseldorf

In der heutigen Zeit ist ein Leben ohne Flugzeuge nicht mehr vorstellbar. In den Urlaub oder zu einem dienstlichen Termin zu fliegen, ist weit verbreitet. Sogar das Fliegen als Hobby in kleinen Privatflugzeugen ist nicht mehr außergewöhnlich und bereichert unser Leben. Die Kehrseite dieser Entwicklung ist der wachsende Flugverkehr, der mittlerweile die am stärksten wachsende Personentransportart geworden ist. In Deutschland liegt die Wachstumsrate für Flugverkehr über 2,3 % pro Jahr. Die Wachstumsrate für motorisierten Individualverkehr liegt hingegen bei 0,2 %, für Eisenbahnverkehr bei 0,3 % und für den öffentlichen Personenverkehr bei -0,1 %. Dieser starke Zuwachs im Luftverkehr verursacht Probleme hinsichtlich der vorhandenen Kapazitäten an allen internationalen Flughäfen in Deutschland. Der Flughafen Düsseldorf ist bezüglich der Flugbewegungen der drittgrößte Flughafen in Deutschland. Er wurde 1927 eröffnet und besteht aus 2 parallelen Pisten, einer zu den Pisten parallel verlaufenden Rollbahn, einem Passagierterminal und drei Vorfeldern (ein Vorfeld grenzt direkt an das Terminal). Am Flughafen Düsseldorf gab es im Jahr 2016 217.500 Flugbewegungen mit 23,5 Millionen Passagieren. Die Kapazitätsgrenze des Flughafens liegt bei 24 Millionen Passagieren und ist 2017 erstmals überschritten worden. Aufgrund des beschränkten Platzes im Umfeld des Flughafens ist eine weitere räumliche Ausdehnung nicht möglich. Optimierungen an der Infrastruktur des Flughafens selbst sind aus politischen Gründen sehr schwer zu realisieren. 1965 wurde ein Vergleich zwischen dem Flughafen und den umliegenden Städten geschlossen, um die Lärmbelastung durch Limitierung der Flugbewegungen nicht weiter zu erhöhen. Über 50 Jahre später ist diese Grenze nun erreicht und ein Ausbau des Flughafens wäre vonnöten. Der Vergleich ist aber noch immer gültig und verhindert notwendige Erweiterungen. Alternativ wird versucht, Verbesserungen der Situation durch eine effizientere Nutzung der vorhandenen Infrastruktur, z.B. durch Optimierung der Rollwege, zu erzielen. Hierbei können Simulationen helfen, um eventuelle Fehlplanungen schon während der Konzeptionsphase zu erkennen und zu verhindern. In dieser Arbeit wird ein neues Simulationsmodell, das CAMAT-Modell (Cellular Automaton Model for Airport Traffic) vorgestellt. Es kann die Dynamik aller Flugzeuge und die Interaktionen der Flugzeuge untereinander simulieren. Das Modell wird durch Realdaten aus verschiedenen Quellen kalibriert. So werden Daten genutzt, die durch Beobachtungen am Flughafen Düsseldorf entstanden sind. Ferner werden Daten der Flugsicherung, vor allem Daten hinsichtlich der Gate- und Rollwegezuweisungen, und viele undokumentierte Informationen, die auf der Erfahrung der Fluglotsen beruhen, genutzt. Zuletzt werden diese Daten durch Daten von Flightradar24, wie die tatsächlichen Ankunfts- und Abflugzeiten ergänzt. Ein Vergleich zwischen Realdaten und den Ergebnissen der Simulation zeigt die Genauigkeit des entwickelten Modells. Im zweiten Teil dieser Arbeit wird das entwickelte Modell verwendet, um die Folgen für die Rollzeiten bei verschiedenen Szenarien, wie neuen Rollwegen, das Ergänzen von Rollbahnen oder Bauarbeiten auf Rollbahnen, am Flughafen Düsseldorf zu simulieren. Für jedes Szenario werden die Änderungen hinsichtlich der Rollzeiten der Flugzeuge berechnet und deren Auswirkungen auf den Kerosinverbrauch erläutert. Diese Arbeit schließt mit einem Ausblick auf mögliche Erweiterungen des Simulationsmodells, welche die Idee der Optimierung des Flugbetriebs durch den Flughafen Düsseldorf, aber auch durch die rollenden Flugzeuge selbst, weiterverfolgen.Nowadays a world without people flying in airplanes is hard to imagine. Going on vacation or on a business trip by plane has become quite common and even flying just for fun in small private planes is no longer unusual and enriches our lives. This development’s downside is the increasing growth of airplane traffic, being the most increasing mode of transportation. In Germany the expected growth rate for airplane traffic is over 2.3 % per year in contrast to 0.2 % for motorized private transport, 0.3 % for railway transport and -0.1 % for public transport. This increase creates problems on all international airports in Germany because of their limited capacity. The airport of Duesseldorf is the third largest airport in Germany with regard to airplane movement. It was opened in 1927 and consists of two parallel runways, one parallel taxiway, one passenger terminal and three aprons (one close to the terminal). The airport handled 217,500 airplane movements in 2016 with 23.5 million passengers. The capacity limit of 24 million passengers was reached in 2017 for the first time. Due to the limited space around the airport further expansion is not possible. Furthermore optimizations on the airport’s infrastructure are hard to realize due to political reasons. The airport reached a settlement with all nearby towns in 1965 for reducing noise pollution by limiting airplane movement. Over 50 years later this limit is reached; however the settlement is still valid and impedes necessary expansions. In addition to airport expansion, improvements of airport surface operations are necessary to handle the increasing number of airplanes. Therefore simulations are helpful to evaluate suggestions and to avoid poor planning in advance. In this work a new simulation model, the CAMAT-Model (Cellular Automaton Model for Airport Traffic), is developed. It simulates all airplanes in a microscopic way and considers the interactions between them. The model is adjusted by real-world data from a range of sources. First, real-world data is used, collected through visual observation at the airport of Duesseldorf. Second, data of Air-Traffic Control (ATC) is put on use, meaning data about gates used by the airplanes and undocumented tower agents’ experience about taxiing routes. Third, the usage of additional data collected by flightradar24, such as actual departure and arrival times, is helpful. A comparison between real-word data and simulated data is presented to prove the accuracy of the model. Some examples for the utilization of the simulation model are given in the second part of this work, including simulations of new taxiing routes for airplane traffic at the airport of Duesseldorf in case of construction work as well as in case of possible future extensions. For each scenario changes in taxiing time are calculated to evaluate the effects on taxiing times in general and on fuel consumption. This work concludes with some outlooks on future work pursuing the main ideas for optimization of airplane taxiing, containing ideas for improvement by the airport as well as improvements for airplanes to reduce their taxiing times themselves

A life-cycle flexibility framework for designing, evaluating and managing "complex" real options : case studies in urban transportation and aircraft systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology, Management, and Policy Program, 2007.Includes bibliographical references.Designing a flexible system with real options is a method for managing uncertainty. This research introduces the concept of "complex" real options, which are composed of interconnected echnological, organizational and process components. "Complex" real options differ from the "standard" real options described in the literature in the option life-cycle activities of design, evaluation and management. To address the challenges posed by "complex" real options, the Life-Cycle Flexibility (LCF) Framework was created. The framework addresses issues along the entire life-cycle of an option, in both technical and social system dimensions. Two case studies were considered in this research to better understand "complex" real options and test the LCF Framework: 1) a large blended wing body aircraft in a commercial aircraft manufacturing enterprise and, 2) Intelligent Transportation System (ITS) capabilities in an urban region with multiple public and private stakeholders. For the case studies, both a quantitative and qualitative analysis was completed. System dynamics and traffic demand models were used to quantitatively evaluate flexibility for each case study. Forty interviews with practitioners were conducted to better understand the practical challenges associated with flexible systems.(cont.) This research found that there are significant differences between "standard" and "complex" real options. In the design phase, enterprise architecture issues must be considered either as a precursor or simultaneously with the design of the option. In the evaluation stage, option valuation techniques more sophisticated than those found in the real options literature were needed to value the "complex" real options. In the management stage, political considerations were of great importance as political opposition could prevent option exercise from occurring. Without the LCF framework, existing processes for evaluating real options are not adequate for taking into account the interacting technical, organizational and process components of 'complex" real options. In summary, this research provides new insights into the design, evaluation and management of "complex" real options.by Joshua Bryan McConnell.Ph.D