Airport taxi planning: Lagrangian decomposition

The airport taxi planning (TP) module is a decision tool intended to guide airport surface management operations. TP is defined by a flow network optimization model that represents flight ground movements and improves aircraft taxiing routes and schedules during periods of aircraft congestion. TP is not intended to operate as a stand‐alone tool for airport operations management: on the contrary, it must be used in conjunction with existing departing and arriving traffic tools and overseen by the taxi planner of the airport, also known as the aircraft ground controller. TP must be flexible in order to accommodate changing inputs while maintaining consistent routes and schedules already delivered from past executions. Within this dynamic environment, the execution time of TP may not exceed a few minutes. Classic methods for solving binary multi‐commodity flow networks with side constraints are not efficient enough; therefore, a Lagrangian decomposition methodology has been adapted to solve it. We demonstrate TP Lagrangian decomposition using actual data from the Madrid‐Barajas Airport. Copyright © 2011 John Wiley & Sons, Ltd.     

A Heuristic Algorithm for the Allocation of Airport Runway System Capacity

Abstract

This paper develops a heuristic algorithm for the allocation of airport runway capacity to minimise the cost of arrival and departure aircraft/flight delays. The algorithm is developed as a potential alternative to optimisation models based on linear and integer programming. The algorithm is based on heuristic (‘greedy’) criteria that closely reflect the ‘rules of thumb’ used by air traffic controllers. Using inputs such as arrival and departure demand, airport runway system capacity envelopes and cost of aircraft/flight delays, the main output minimises the cost of arrival and departure delays as well as the corresponding interdependent airport runway system arrival and departure capacity allocation. The algorithm is applied to traffic scenarios at three busy US airports. The results are used to validate the performance of the proposed heuristic algorithm against results from selected benchmarking optimisation models.     

Research review of air traffic management

As air transport demand keeps growing more quickly than system capacity, efficient and effective management of system capacity becomes essential to the operation of the future global air traffic system. Although research in the past two decades has made significant progress in relevant research fields, e.g. air traffic flow management and airport capacity modelling, research loopholes in air traffic management still exist and links between different research areas are required to enhance the system performance of air traffic management. Hence, the objective of this paper is to review systematically current research in the literature about the issue of air traffic management to prioritize productive research areas. Papers about air traffic management are discussed and categorized into two levels: system and airport. The system level of air transport research includes two main topics: air traffic flow management and airspace research. On the airport level, research topics are: airport capacity, airport facility utilization, aircraft operations in the airport terminal manoeuvring area as well as aircraft ground operations research. Potential research interests to focus on in the future are the integration between airspace capacity and airport capacity, the establishment of airport information systems to use airport capacity better, and the improvement in flight schedule planning to improve the reliability of schedule implementation.     

Slot misuse phenomena in capacity-constrained airports with seasonal demand: the Greek experience

Abstract

Airport slot misuse disturbs the efficient and continuous operation of capacity-constrained airports, leading to congestion and delay problems. Deviations from the coordinated schedule in regional airport systems that feature seasonal demand and delays in certain peak periods are studied in this article. The Greek airport system is considered as a case study. Deviations are quantified by computing the difference between scheduled and actual aircraft arrival times as well as the hourly slot capacity utilization ratio. Two collective indicators for airport benchmarking are proposed. An in-depth analysis of slot allocation deviations and the delays they cause is carried out for a representative sample of airports that are classified according to the proposed indicators. A brief discussion on potential measures to mitigate slot misuse is also presented.     

Comparing aircraft noise pollution and cost-risk effects of inland and offshore airports: The case of Dalian International Airport,Dalian, China

China’s Dalian International Airport is taken to compare the aircraft noise pollution and the cost-risk effects of the expanded an existing inland and a proposed offshore airport. The findings show that the aircraft noise pollution of the offshore airport is much less than that of the expanded inland airport; the land-use cost, noise reduction charges and other risks of the offshore airport are also much less; the creation of the offshore airport may be more favorable to the city’s development.     

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.     

Demonstration of reduced airport congestion through pushback rate control

Airport surface congestion results in significant increases in taxi times, fuel burn and emissions at major airports. This paper describes the field tests of a congestion control strategy at Boston Logan International Airport. The approach determines a suggested rate to meter pushbacks from the gate, in order to prevent the airport surface from entering congested states and to reduce the time that flights spend with engines on while taxiing to the runway. The field trials demonstrated that significant benefits were achievable through such a strategy: during eight four-hour tests conducted during August and September 2010, fuel use was reduced by an estimated 12,250–14,500 kg (4000–4700 US gallons), while aircraft gate pushback times were increased by an average of only 4.4 min for the 247 flights that were held at the gate.     

Using supplemental aircraft noise information to assist airport neighbours understand aircraft noise

This paper deals with the value of supplemental aircraft noise information in the form of combining aircraft movement numbers and noise levels to assist airport neighbours in understanding airport noise. To analyse the socio-spatial interaction of annoyance with, and interference by, aircraft noise, an alternative is recommended, namely the number of noise events above selected noise levels so that laypeople can better understand the extent of noise. The research is based on a questionnaire survey of households affected by aircraft noise around OR Tambo International Airport near Johannesburg. The results indicate that levels of annoyance and disturbance across a number of normal household activities are positively related to the number of noise events recorded, irrespective of noise levels above 60 dB.     

Estimation of airport noise impacts on public health. A case study of İzmir Adnan Menderes Airport

The air transport industry is showing rapid growth in line with the call for meeting the requirements of a rising population. Noise mapping is more useful than surveys and measurements to estimate the effects of noise on public health. In this paper, noise levels for the day, evening and night time slices around İzmir Adnan Menderes Airport were calculated by use of the SoundPLAN 7.2 software according to the European Noise Directive, and the “ECAC Doc. 29-Interim” method was applied for the computation of the aircraft noise. Air traffic data of year 2012, technical information about the airport and geographical data including the layers of elevation, residential buildings, auxiliary buildings, hospitals and schools were used as the main inputs for the model developed in the study. The model was found to perform well for the areas closer to the airport. The results of the study suggested that the area at the north side of the airport, where the city center of İzmir is located, is more affected than other areas. The threshold value of 55 dB(A) was found to be exceeded in 0.3% of the land area covered by İzmir City center during the time slice “day”. The results showed that about 2% of the resident population was exposed to noise levels of 55 dB(A) or higher during day-time in İzmir. In addition, it was understood that the number of people who are potentially exposed to high noise levels and threatened by several illness such as hypertension and sleep disturbances is significant in the surrounding area of the airport. It is thought to be important for airport operators to manage the airport capacity based on the flight schedules in order to control the noise exposure level around the airport.     

Apron capacity at hub airports—the impact of wave‐system structure

At hub airports, dominant airlines/alliance coordinate their flights in time with the aim of increasing the number (and quality) of connections, thus producing a wave‐system in traffic schedules. This paper addresses the impact of concentrating aircraft into waves on airport apron capacity. Existing models for apron capacity estimation are based on the number of stands, stand occupancy time, and demand structure, differing between representative groups of aircraft served at an airport. Criteria for aircraft grouping are aircraft type and/or airline and/or type of service (domestic, international, etc.). Modified deterministic analytical models proposed in this paper also take into account the wave‐system parameters, as well as runway capacity. They include the impact of these parameters on the number of flights in wave, stand occupancy time, and consequently apron capacity. Numerical examples illustrate the difference between apron capacity for an origin–destination airport and a hub airport, under the same conditions; utilization of the theoretical apron capacity at a hub airport, given the wave‐system structure; and utilization of the apron capacity at a hub airport when point‐to‐point traffic is allowed to use idle stands. Furthermore, the influence of different assignment strategies for aircraft stands in the case of hub airports is also discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

Level of service analysis for airport baggage claim with a case study of the Calgary International Airport

This work presents a methodology to evaluate the level of service (LOS) of an airport baggage claim. A psychometric scaling technique is employed to obtain quantitative data from qualitative data (user responses as a function of five rating categories). Regression analysis is applied to obtain a statistically valid relationship between user responses and observed operational indicators. The proposed model is developed from a case study of the West Jet baggage claim area at the Calgary International Airport – Canada, where 62 passengers have been observed and interviewed. The collected data allowed the proposal of standards, which indicate tolerable limits as a function of various LOS ranges (A–E). The results are useful for managers and designers on assessing the LOS offered in a terminal, but also during the planning and design stages of an airport. Copyright © 2010 John Wiley & Sons, Ltd.     

Life cycle assessment of heated apron pavement system operations

Heated pavement systems (HPS) offer an attractive alternative to the cumbersome process of removing ice and snow from airport pavements using traditional snow removal systems. Although snow and ice removing efficiency and economic benefits of HPS have been assessed by previous studies, their environmental impact is not well known. Airport facilities offering public or private services need to evaluate the energy consumption and global warming potential of different types of snow and ice removal systems. Energy usage and emissions from the operations of hydronic heated pavement system using geothermal energy (HHPS-G), hydronic HPS using natural gas furnace (HHPS-NG), electrically heated pavement system (EHPS), and traditional snow and ice removal system (TSRS) are estimated and compared in this study using a hybrid life cycle assessment (LCA). Based on the system models assessed in this study, HPS application in the apron area seems to be a viable option from an energy or environmental perspective to achieve ice/snow free pavement surfaces without using mechanical or chemical methods. TSRS methods typically require more energy and they produce more greenhouse gas (GHG) emissions compared to HPS during the operation phase, under the conditions and assumptions considered in this study. Also, HPS operations require less energy and have less GHG emissions during a snow event with a smaller snowfall rate and a larger snow duration.     

Ground delay program planning under uncertainty in airport capacity

Abstract

This paper presents an algorithm for assigning flight departure delays under probabilistic airport capacity. The algorithm dynamically adapts to weather forecasts by revising, if necessary, departure delays. The proposed algorithm leverages state-of-the-art optimization techniques that have appeared in recent literature. As a case study, the algorithm is applied to assigning departure delays to flights scheduled to arrive at San Francisco International Airport in the presence of uncertainty in the fog clearance time. The cumulative distribution function of fog clearance time was estimated from historical data. Using daily weather forecasts to update the probabilities of fog clearance times resulted in improvement of the algorithm's performance. Experimental results also indicate that if the proposed algorithm is applied to assign ground delays to flights inbound at San Francisco International airport, overall delays could be reduced up to 25% compared to current level.     

An online speed profile generation approach for efficient airport ground movement

The precise guidance and control of taxiing aircraft based on four-dimensional trajectories (4DTs) has been recognised as a promising means to ensure safe and efficient airport ground movement in the context of ever growing air traffic demand. In this paper, a systematic approach for online speed profile generation is proposed. The aim is to generate fuel-efficient speed profiles respecting the timing constraints imposed by routing and scheduling, which ensures conflict-free movement of aircraft in the planning stage. The problem is first formulated as a nonlinear optimisation model, which uses a more flexible edge-based speed profile definition. A decomposed solution approach (following the framework of matheuristic) is then proposed to generate feasible speed profiles in real time. The decomposed solution approach reduces the nonlinear optimisation model into three tractable constituent problems. The control point arrival time allocation problem is solved using linear programming. The control point speed allocation problem is solved using particle swarm optimisation. And the complete speed profile between control points is determined using enumeration. Finally, improved speed profiles are generated through further optimisation upon the feasible speed profiles. The effectiveness and advantages of the proposed approach are validated using datasets of real-world airports.     

Accuracy of reinforcement learning algorithms for predicting aircraft taxi-out times: A case-study of Tampa Bay departures

Taxi-out delay is a significant portion of the block time of a flight. Uncertainty in taxi-out times reduces predictability of arrival times at the destination. This in turn results in inefficient use of airline resources such as aircraft, crew, and ground personnel. Taxi-out time prediction is also a first step in enabling schedule modifications that would help mitigate congestion and reduce emissions. The dynamically changing operation at the airport makes it difficult to accurately predict taxi-out time. In this paper we investigate the accuracy of taxi out time prediction using a nonparametric reinforcement learning (RL) based method, set in the probabilistic framework of stochastic dynamic programming. A case-study of Tampa International Airport (TPA) shows that on an average, with 93.7% probability, on any given day, our predicted mean taxi-out time for any given quarter, matches the actual mean taxi-out time for the same quarter with a standard error of 1.5 min. Also, for individual flights, the taxi-out time of 81% of them were predicted accurately within a standard error of 2 min. The predictions were done 15 min before gate departure. Gate OUT, wheels OFF, wheels ON, and gate IN (OOOI) data available in the Aviation System Performance Metric (ASPM) database maintained by the Federal Aviation Administration (FAA) was used to model and analyze the problem. The prediction accuracy is high even without the use of detailed track data.     

Noise pollution associated with the operation of the Dar es Salaam International Airport

The operation of airports results in environmental impacts associated with high levels of noises and vibrations. These may have severe negative effects to both workers and surrounding residents and their properties. Here we look at the noise impacts associated with the operation of the Dar es Salaam International Airport (DIA) in Tanzania. Field measurements were carried out to determine noise levels at various positions at the airport during aircraft landing and take-off. The surrounding residents' perceptions on the noises were also investigated using semi-structured interviews. Workers on the apron (marshellers), house keepers, security workers, and mechanics are exposed to noise levels that could affect their health. The noise levels in the surrounding settlements of Kipawa and Kiwalani were higher than the WHO recommended limits and causing annoyance to residents. The use of appropriate ear protectors by the workers was found to reduce the noises to harmless levels. Periodical audiometric tests of the workers will help to monitor the noise impacts. Enforcement of appropriate environmental regulations on the airliners can also reduce noise pollution at the airport.     

Optimal assignment for check-in counters based on passenger arrival behaviour at an airport

Establishing how to utilize check-in counters at airport passenger terminals efficiently is a major concern facing airport operators and airlines. Inadequate terminal capacity and the inefficient utilization of facilities such as check-in counters are major factors causing congestion and delays at airport passenger terminals. However, such delays and congestion can be reduced by increasing the efficiency of check-in counter operations, based on an understanding of passengers' airport access behaviour. This paper presents an assignment model for check-in counter operations, based on passengers' airport arrival patterns. In setting up the model, passenger surveys are used to determine when passengers arrive at the airport terminals relative to their flight departure times. The model then uses passenger arrival distribution patterns to calculate the most appropriate number of check-in counters and the duration of time that each counter should be operated. This assignment model has been applied at the Seoul Gimpo International Airport in Korea. The model provides not only a practical system for the efficient operations of time-to-time check-in counter assignments, but also a valuable means of developing effective longer-term solutions to the problem of passenger terminal congestion and delays. It also offers airlines a means of operating check-in counters with greater cost effectiveness, thus leading to enhanced customer service.     

Eco-efficiency management program (EEMP)—a model for road fleet operation

Fuel consumption has always been a matter of economic concern in road fleet management, giving rise to many initiatives aimed at fostering more efficient energy use. The increasingly awareness of environmental problems now requires these programs to include environmental aspects. A structured Eco-efficiency Management Program (EEMP) is proposed for road fleet operation, taking into account the traditional approach that strives to minimise fuel consumption as well as wider economic and environmental aspects. The EEMP has its potential evaluated in a case study undertaken for INFRAERO, Brazilian’s airport authority, on the operation of its road fleet supporting aircraft ground operations at Rio de Janeiro International Airport. The paper looks at EEMP’s implementation by identifying the program’s phases, its participants and their competencies, eco-efficiency indicators, and performance targets.     

The economics of airport noise: How to manage markets for noise licenses

This paper discusses various issues in the implementation of a local market for aircraft noise licenses to solve the noise externalities harming the residents located near airports. The design of such markets is affected by aircraft heterogeneity, wind contingencies, peak times, runways capacity constraints, hub strategies, and airport planning is discussed.