Exploration of the ordering for a sequential airport ground movement algorithm

Guiding aircraft around the airport's surface while ensuring conflict-free routings is an important problem at airports. Sequential routing and scheduling algorithms can be advantageous for providing fast online solutions for decision support systems to help controllers. However, the effectiveness of such algorithms can depend upon the sequence of consideration of the aircraft, which is often chosen to be first-come-first-served. This research analyses the effects of different heuristics to find better sequences. Results are presented, utilising real data from Zurich Airport. These show that sophisticated heuristics can substantially improve the solution with comparatively little additional computational time. Furthermore, one approach aims to modify relatively few existing routes as it progresses, in order to minimise the workload of the controllers in communicating changes in an online environment

Enhancing decision support systems for airport ground movement

With the expected continued increases in air transportation, the mitigation of the consequent delays and environmental effects is becoming more and more important, requiring increasingly sophisticated approaches for airside airport operations. The ground movement problem forms the link between other airside problems at an airport, such as arrival sequencing, departure sequencing, gate/stand allocation and stand holding. The purpose of this thesis is to contribute to airport ground movement research through obtaining a better understanding of the problem and producing new models and algorithms for three sub-problems. Firstly, many stakeholders at an airport can benefit from more accurate taxi time predictions. This thesis focuses upon this aim by analysing the important factors affecting taxi times for arrivals and departures and by comparing different regression models to analyse which one performs the best for this particular task. It was found that incorporating the information of the airport layout could significantly improve the accuracy and that a TSK fuzzy rule-based system outperformed other approaches. Secondly, a fast and flexible decision support system is introduced which can help ground controllers in an airport tower to make better routing and scheduling decisions and can also absorb as much of the waiting time as possible for departures at the gate/stand, to reduce the fuel burn and environmental impact. The results show potential maximum savings in total taxi time of about 30.3%, compared to the actual performance at the airport. Thirdly, a new research direction is explored which analyses the trade-off between taxi time and fuel consumption during taxiing. A sophisticated new model is presented to make such an analysis possible. Furthermore, this research provides the basis for integrating the ground movement problem with other airport operations. Datasets from Zurich Airport, Stockholm-Arlanda Airport, London Heathrow Airport and Hartsfield-Jackson Atlanta International Airport were utilised to test these sub-problems

Enhancing decision support systems for airport ground movement

With the expected continued increases in air transportation, the mitigation of the consequent delays and environmental effects is becoming more and more important, requiring increasingly sophisticated approaches for airside airport operations. The ground movement problem forms the link between other airside problems at an airport, such as arrival sequencing, departure sequencing, gate/stand allocation and stand holding. The purpose of this thesis is to contribute to airport ground movement research through obtaining a better understanding of the problem and producing new models and algorithms for three sub-problems. Firstly, many stakeholders at an airport can benefit from more accurate taxi time predictions. This thesis focuses upon this aim by analysing the important factors affecting taxi times for arrivals and departures and by comparing different regression models to analyse which one performs the best for this particular task. It was found that incorporating the information of the airport layout could significantly improve the accuracy and that a TSK fuzzy rule-based system outperformed other approaches. Secondly, a fast and flexible decision support system is introduced which can help ground controllers in an airport tower to make better routing and scheduling decisions and can also absorb as much of the waiting time as possible for departures at the gate/stand, to reduce the fuel burn and environmental impact. The results show potential maximum savings in total taxi time of about 30.3%, compared to the actual performance at the airport. Thirdly, a new research direction is explored which analyses the trade-off between taxi time and fuel consumption during taxiing. A sophisticated new model is presented to make such an analysis possible. Furthermore, this research provides the basis for integrating the ground movement problem with other airport operations. Datasets from Zurich Airport, Stockholm-Arlanda Airport, London Heathrow Airport and Hartsfield-Jackson Atlanta International Airport were utilised to test these sub-problems

Exploration of the ordering for a sequential airport ground movement algorithm

Guiding aircraft around the airport's surface while ensuring conflict-free routings is an important problem at airports. Sequential routing and scheduling algorithms can be advantageous for providing fast online solutions for decision support systems to help controllers. However, the effectiveness of such algorithms can depend upon the sequence of consideration of the aircraft, which is often chosen to be first-come-first-served. This research analyses the effects of different heuristics to find better sequences. Results are presented, utilising real data from Zurich Airport. These show that sophisticated heuristics can substantially improve the solution with comparatively little additional computational time. Furthermore, one approach aims to modify relatively few existing routes as it progresses, in order to minimise the workload of the controllers in communicating changes in an online environment

Towards a more realistic, cost effective and greener ground movement through active routing: a multi-objective shortest path approach

Based on the multi-objective optimal speed profile generation framework for unimpeded taxiing aircraft presented in the precursor paper, this paper deals with how to seamlessly integrate such optimal speed profiles into a holistic decision making framework. The availability of a set of non-dominated unimpeded speed profiles for each taxiway segment with respect to conflicting objectives can significantly change the current airport ground movement research. More specifically, the routing and scheduling function that was previously based on distance, emphasizing time efficiency, could now be based on richer information embedded within speed profiles, such as the taxiing times along segments, the corresponding fuel consumption, and the associated economic implications. The economic implications are exploited over a day of operation to take into account cost differences between busier and quieter times of the airport. Therefore, the most cost-effective and tailored decision can be made, respecting the environmental impact. Preliminary results based on the proposed approach are promising and show a 9%–50% reduction in time and fuel respectively for two international airports, viz. Zurich and Manchester Airports. The study also suggests that, if the average power setting during the acceleration phase could be lifted from the level suggested by the International Civil Aviation Organization (ICAO), ground operations may achieve the best of both worlds, simultaneously improving both time and fuel efficiency. Now might be the time to move away from the conventional distance based routing and scheduling to a more comprehensive framework, capturing the multi-facetted needs of all stakeholders involved in airport ground operations

The trade-off between taxi time and fuel consumption in airport ground movement

Environmental impact is a very important agenda item in many sectors nowadays, which the air transportation sector is also trying to reduce as much as possible. One area which has remained relatively unexplored in this context is the ground movement problem for aircraft on the airport’s surface. Aircraft have to be routed from a gate to a runway and vice versa and it is still unknown whether fuel burn and environmental impact reductions will best result from purely minimising the taxi times or whether it is also important to avoid multiple acceleration phases. This paper presents a newly developed multi-objective approach for analysing the trade-off between taxi time and fuel consumption during taxiing. The approach consists of a combination of a graph-based routing algorithm and a population adaptive immune algorithm to discover different speed profiles of aircraft. Analysis with data from a European hub airport has highlighted the impressive performance of the new approach. Furthermore, it is shown that the trade-off between taxi time and fuel consumption is very sensitive to the fuel-related objective function which is used

Heuristic search for the coupled runway sequencing and taxiway routing problem

This paper presents the first local search heuristic for the coupled runway sequencing (arrival & departure) and taxiway routing problems, based on the receding horizon (RH) scheme that takes into account the dynamic nature of the problem. As test case, we use Manchester Airport, the third busiest airport in the UK. From the ground movement perspective, the airport layout requires that departing aircraft taxi across the arrivals runway. This makes it impossible to separate arrival from departure sequencing in practice. Operationally, interactions between aircraft on the taxiways could prevent aircraft from taking off from, or landing on, runways during the slots assigned to them by an algorithm optimizing runway use alone. We thus consider the interactions between arrival and departure aircraft on the airport surface. Compared to sequentially optimized solutions, the results obtained with our approach indicate a significant decrease in the taxiway routing delay, with generally no loss in performance in terms of the sequencing delay for a regular day of operations. Another benefit of such a simultaneous optimization approach is the possibility of holding aircraft at the stands for longer, without the engines running. This significantly reduces the fuel burn, as well as bottlenecks and traffic congestion during peak hours that are often the cause of flight delays due to the limited amount of airport surface space available. Given that the maximum computing time per horizon is around 95 s, real-time operation might be practical with increased computing power

Efficacy of Anti-Inflammatory Therapy in a Model of Acute Seizures and in a Population of Pediatric Drug Resistant Epileptics

Targeting pro-inflammatory events to reduce seizures is gaining momentum. Experimentally, antagonism of inflammatory processes and of blood-brain barrier (BBB) damage has been demonstrated to be beneficial in reducing status epilepticus (SE). Clinically, a role of inflammation in the pathophysiology of drug resistant epilepsies is suspected. However, the use anti-inflammatory drug such as glucocorticosteroids (GCs) is limited to selected pediatric epileptic syndromes and spasms. Lack of animal data may be one of the reasons for the limited use of GCs in epilepsy. We evaluated the effect of the CG dexamethasone in reducing the onset and the severity of pilocarpine SE in rats. We assessed BBB integrity by measuring serum S100β and Evans Blue brain extravasation. Electrophysiological monitoring and hematologic measurements (WBCs and IL-1β) were performed. We reviewed the effect of add on dexamethasone treatment on a population of pediatric patients affected by drug resistant epilepsy. We excluded subjects affected by West, Landau-Kleffner or Lennox-Gastaut syndromes and Rasmussen encephalitis, known to respond to GCs or adrenocorticotropic hormone (ACTH). The effect of two additional GCs, methylprednisolone and hydrocortisone, was also reviewed in this population. When dexamethasone treatment preceded exposure to the convulsive agent pilocarpine, the number of rats developing status epilepticus (SE) was reduced. When SE developed, the time-to-onset was significantly delayed compared to pilocarpine alone and mortality associated with pilocarpine-SE was abolished. Dexamethasone significantly protected the BBB from damage. The clinical study included pediatric drug resistant epileptic subjects receiving add on GC treatments. Decreased seizure frequency (≥50%) or interruption of status epilepticus was observed in the majority of the subjects, regardless of the underlying pathology. Our experimental results point to a seizure-reducing effect of dexamethasone. The mechanism encompasses improvement of BBB integrity. Our results also suggest that add on GCs could be of efficacy in controlling pediatric drug resistant seizures

Exploration of the ordering for a sequential airport ground movement algorithm

Guiding aircraft around the airport's surface while ensuring conflict-free routings is an important problem at airports. Sequential routing and scheduling algorithms can be advantageous for providing fast online solutions for decision support systems to help controllers. However, the effectiveness of such algorithms can depend upon the sequence of consideration of the aircraft, which is often chosen to be first-come-first-served. This research analyses the effects of different heuristics to find better sequences. Results are presented, utilising real data from Zurich Airport. These show that sophisticated heuristics can substantially improve the solution with comparatively little additional computational time. Furthermore, one approach aims to modify relatively few existing routes as it progresses, in order to minimise the workload of the controllers in communicating changes in an online environment

Enhancing decision support systems for airport ground movement

With the expected continued increases in air transportation, the mitigation of the consequent delays and environmental effects is becoming more and more important, requiring increasingly sophisticated approaches for airside airport operations. The ground movement problem forms the link between other airside problems at an airport, such as arrival sequencing, departure sequencing, gate/stand allocation and stand holding. The purpose of this thesis is to contribute to airport ground movement research through obtaining a better understanding of the problem and producing new models and algorithms for three sub-problems. Firstly, many stakeholders at an airport can benefit from more accurate taxi time predictions. This thesis focuses upon this aim by analysing the important factors affecting taxi times for arrivals and departures and by comparing different regression models to analyse which one performs the best for this particular task. It was found that incorporating the information of the airport layout could significantly improve the accuracy and that a TSK fuzzy rule-based system outperformed other approaches. Secondly, a fast and flexible decision support system is introduced which can help ground controllers in an airport tower to make better routing and scheduling decisions and can also absorb as much of the waiting time as possible for departures at the gate/stand, to reduce the fuel burn and environmental impact. The results show potential maximum savings in total taxi time of about 30.3%, compared to the actual performance at the airport. Thirdly, a new research direction is explored which analyses the trade-off between taxi time and fuel consumption during taxiing. A sophisticated new model is presented to make such an analysis possible. Furthermore, this research provides the basis for integrating the ground movement problem with other airport operations. Datasets from Zurich Airport, Stockholm-Arlanda Airport, London Heathrow Airport and Hartsfield-Jackson Atlanta International Airport were utilised to test these sub-problems.EThOS - Electronic Theses Online ServiceGBUnited Kingdo