Airport capacity increase via the use of braking profiles

Many airports are encountering the problem of insufficient capacity, which is particularly severe in periods of increased traffic. A large number of elements influence airport capacity, but one of the most important is runway occupancy time. This time depends on many factors, including how the landing roll procedure is performed. The procedure usually does not include the objective to minimize the runway occupancy time. This paper presents an analysis which shows that the way of braking during landing roll has an essential impact on runway throughput and thus on airport capacity. For this purpose, the landing roll simulator (named ACPENSIM) was created. It uses Petri nets and is a convenient tool for dynamic analysis of aircraft movement on the runway with given input parameters and a predetermined runway exit. Simulation experiments allowed to create a set of nominal braking profiles that have different objective functions: minimizing the runway occupancy time, minimizing noise, minimizing tire wear, maximizing passenger comfort and maximizing airport capacity as a whole. The experiments show that there is great potential to increase airport capacity by optimizing the braking procedure. It has been shown that by using the proposed braking profiles it is possible to reduce the runway occupancy time even by 50%.     

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.     

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.     

Modeling effects of different air traffic control operational procedures,separation rules,and service disciplines on runway landing capacity

This paper deals with modeling the possible effects of different advanced procedures, existing, innovative, and new air traffic control (ATC) separation rules, and service disciplines on the ultimate landing capacity of a single runway. The first implies a combination and/or exclusive use of conventional and steeper final approach and landing procedures. The second includes the current horizontal, innovative mixed horizontal/vertical and new vertical distance‐based and time‐based separation rules. The last embrace the common First Come, First Served and innovative Priority service discipline. Such increasingly complex and challenging applications are assumed to be based on the new technologies on‐board the aircraft and at the ATC to be developed in the scope of the current United States Next Generation Air Transport System and European Single European Sky ATM Research programs. The convenient analytical models for calculating the runway landing capacity are developed and applied to the generic case of a single runway according to the “what–if” scenario approach. This enables carrying out the sensitivity analysis of the landing capacity with respect to the most influential factors – the ATC advanced operational procedures, separation rules, service disciplines, and aircraft fleet mix. Copyright © 2013 John Wiley & Sons, Ltd.     

A critical examination of an airport noise mitigation scheme and an aircraft noise charge: the case of capacity expansion and externalities at Sydney (Kingsford Smith) airport

In the wake of the Australian airline liberalization in 1990 and its forecasted impact on air traffic, capacity has been expanded at Sydney (Kingsford Smith) airport (Sydney KSA) – Australia's busiest commercial airport – with the construction of the third runway in 1994. Coinciding with the approval for this capacity expansion, the Commonwealth Government amended the Federal Airports Corporation (FAC) Act to direct the FAC to carry out activities which protect the environment from the effects of aircraft operations, with the cost to be borne by the airline industry according to the ‘Polluter Pays Principle'. Noise management plans were part of the conditions for developmental approval for a third runway. To this end, since 1995, Sydney KSA imposes a noise levy designed to generate sufficient revenues to fund a noise mitigation scheme. Although the issues of aircraft noise, in particular its impact on property values and land use planning around the airport, have been extensively addressed in the literature, no one has empirically examined the implications of new environmental policies in conjunction with airline liberalization and change in airport infrastructure. Principles and policy analyses are discussed in this paper. By focusing on the specifics of Sydney KSA, broader policy issues likely to be relevant for other major airports around the world are discussed.     

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.     

Implementation and application of a stochastic aircraft boarding model

The aircraft turnaround processes is mainly controlled by the ground handling, airport or airline staff, except the aircraft boarding, which is driven by the passengers’ experience and willingness or ability to follow the proposed boarding procedures. The paper uses a prior developed, calibrated, stochastic aircraft boarding model, which is applied to different boarding strategies (chronological order of passenger arrival, hand luggage handling), group constellations and innovative infrastructural changes (Flying Carpet, Side-Slip Seat, Foldable Passenger Seat). In this context, passenger boarding is assumed to be a stochastic, agent-based, forward-directed, one-dimensional and discrete process. The stochastic model covers individual passenger behavior as well as operational constraints and deviations. A comprehensive assessment using one model allows for efficient comparison of current research approaches and innovative operational solutions for efficient passenger boarding.     

Crosswind‐based optimization of multiple runway orientations

The runway orientation must satisfy the operational requirements of aircraft for landing and takeoff. Actually, the runway orientation is the result of compromises between the airport usability (wind coverage) and additional factors, such as available land, existing obstructions, topographic difficulties, flight path interference among runways and airports, noise pollution, and other environmental impacts. Therefore, the solution of a combination of acceptable runway orientations, which avoids excessive crosswinds at least 95% of the time, as well as the optimal orientation solution, is essential to conduct those compromises in the runway orientation analysis. The objective of this paper is to develop a computer model, named the optimization of multiple runway orientations model, which is capable of simultaneously providing a combination of acceptable runway orientations, changing the allowable crosswind limit flexibly, and determining the optimal orientations of multiple runway configurations. Instead of visual estimation or geometric computation, this paper presents an analytical method for wind coverage analysis. The model is mainly running in spreadsheet and Visual Basic for Applications (VBA). The numerical example and comparison show that the optimization of multiple runway orientations model is competitively accurate and convenient in comparison with previous ones. This paper presents an up‐to‐date model for the optimization of multiple runway orientations. By combining it with the geographic information system obstructions model, it can become an essential element of a future model for airport development cost minimization that combines airfield land use, earthwork volume, and cost estimation modules. Copyright © 2013 John Wiley & Sons, Ltd.     

A multi-criteria evaluation of solutions and alternatives for matching capacity to demand in an airport system: the case of London

This paper applies multi-criteria decision-making (MCDM) methods to the evaluation of solutions and alternatives for matching airport system airside (runway) capacity to demand. For such a purpose, ‘building a new runway’ is considered as the solution and candidate airports of the system as alternatives for implementing the solution. The alternative airports are characterized by their physical/spatial, operational, economic, environmental, and social performance represented by corresponding indicator systems which, after being defined and estimated under given operating scenarios, are used as evaluation attributes/criteria by the selected MCDM methods. Two MCDM methods – Simple Additive Weighting and Technique for Order of Preference by Similarity to Ideal Solution – are applied to the case of the London airport system to rank and select the preferred alternative from three candidate airports – Heathrow, Gatwick, and Stansted – for where a new runway could be built.     

对轨道交通区间隧道下穿机场跑道相关问题的探讨

在上海虹桥综合交通枢纽工程建设中,针对国内首次轨道交通区间隧道下穿运营中的机场跑道的问题,全面介绍了机场跑道变形控制标准、隧道的埋深要求、结构设计、接缝防水构造等方面进行的研究过程,初步确定了机场跑道的变形控制标准,跑道范围内隧道的最小覆土深度,并提出了衬砌结构的计算和接缝防水构造的设计构思。     

Scheduling of airport runway operations using stochastic branch and bound methods

In this paper we present a solution methodology based on the stochastic branch and bound algorithm to find optimal, or close to optimal, solutions to the stochastic airport runway scheduling problem. The objective of the scheduling problem is to find a sequence of aircraft operations on one or several runways that minimizes the total makespan, given uncertain aircraft availability at the runway. Enhancements to the general stochastic branch and bound algorithm are proposed and we give the specific details pertaining to runway scheduling. We show how the algorithm can be terminated early with solutions that are close to optimal, and investigate the impact of the uncertainty level. The computational experiment indicates that the sequences obtained using the stochastic branch and bound algorithm have, on average, 5–7% shorter makespans than sequences obtained using deterministic sequencing models. In addition, the proposed algorithm is able to solve instances with 14 aircraft using less than 1 min of computation time.     

Modelling the capacity of closely-spaced parallel runways using innovative approach procedures

This paper develops analytical models for calculating the ultimate arrival, departure, and mixed operation capacity of closely-spaced parallel runways. Each capacity is defined as the maximum number of corresponding aircraft operations accommodated during a given period of time (usually one or a quarter of an hour) under constant (i.e. sustained) demand for service. As combined, they enable the capacity coverage curve to be synthesized. In particular, the capacity model for arrivals assumes the use of two rather innovative approach procedures – the Staggered Approach Procedure (SGAP) and the Steeper Approach Procedure (SEAP) in combination with the baseline Conventional Approach Procedure (CNAP) under Instrument Meteorological Conditions (IMC) and Instrumental Flight Rules (IFR).The model for arrival capacity that aims to estimate potential of these procedures uses main inputs such as: the geometry of given parallel runways and innovative SGAP and SEAP, and baseline CNAP; the Air Traffic Control (ATC) minimum separation rules; aircraft fleet mix characterized by the wake-vortex categories; capability of using different ILS Glide (GS) angles; final approach speeds; and the arrival runway occupancy time. In addition, the model for departure capacity uses inputs that embrace: the ATC separation rules between successive departures; aircraft fleet mix; and corresponding runway occupancy times. Finally, the model for mixed operation capacity uses inputs such as: the ATC arrival–departure separation rules; corresponding runway occupancy times; aircraft fleet mix for each type of operations; and proportion of the arrival and departure demand.The models are applied to calculating the ultimate capacity of closely-spaced parallel runways at two large airports, one in Europe and other in the US, assuming safe use of innovative SGAP and SEAP in combination with CNAP under IMC. The output from the models consists of the corresponding capacities and their variations depending on particular inputs.     

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.     

Flight schedule punctuality control and management: a stochastic approach

The insufficiency of infrastructure capacity in an air transport system is usually blamed for poor punctuality performance when implementing flight schedules. However, investigations have revealed that ground operations of airlines have become the second major cause of flight delay at airports. A stochastic approach is used in this paper to model the operation of aircraft turnaround and the departure punctuality of a turnaround aircraft at an airport. The aircraft turnaround model is then used to investigate the punctuality problem of turnaround aircraft. Model results reveal that the departure punctuality of a turnaround aircraft is influenced by the length of scheduled turnaround time, the arrival punctuality of inbound aircraft as well as the operational efficiency of aircraft ground services. The aircraft turnaround model proposed is then employed to evaluate the endogenous schedule punctuality of two turnaround aircraft. Model results, when compared with observation data, show that the operational efficiency of aircraft ground services varies among turnarounds. Hence, it is recommended that the improvement of departure punctuality of turnaround aircraft may be achieved from two approaches: airline scheduling control and the management of operational efficiency of aircraft ground services.     

Integrated sequencing and merging aircraft to parallel runways with automated conflict resolution and advanced avionics capabilities

Congestion in Terminal Maneuvering Area (TMA) in hub airports is the main problem in Chinese air transportation. In this paper we propose a new system to integrated sequence and merge aircraft to parallel runways at Beijing Capital International Airport (BCIA). This system is based on the advanced avionics capabilities. Our methodology integrates a Multi-Level Point Merge (ML-PM) system, an economical descent approaches procedure, and a tailored heuristic algorithm to find a good, systematic, operationally-acceptable solution. First, Receding Horizontal Control (RHC) technique is applied to divide the entire 24 h of traffic into several sub-problems. Then in each sub-problem, it is optimized on given objectives (conflict, deviation from Estimated Time of Arrival (ETA) on the runway and makespan of the arrival flow). Four decision variables are designed to control the trajectory: the entry time, the entry speed, the turning time on the sequencing leg, and the landing runway allocation. Based on these variables, the real time trajectories are generated by the simulation module. Simulated Annealing (SA) algorithm is used to search the best solution for aircraft to execute. Finally, the conflict-free, least-delay, and user-preferred trajectories from the entry point of TMA to the landing runway are defined. Numerical results show that our optimization system has very stable de-conflict performance to handle continuously dense arrivals in transition airspace. It can also provide the decision support to assist flow controllers to handle the asymmetric arrival flows on different runways with less fuel consumption, and to assist tactical controllers to easily re-sequence aircraft with more relaxed position shifting. Moreover, our system can provide the fuel consumption prediction, and runway assignment information to assist airport and airlines managers for optimal decision making. Theoretically, it realizes an automated, cooperative and green control of routine arrival flows. Although the methodology defined here is applied to the airport BCIA, it could also be applied to other airports in the world.     

Evaluating the operational performance of airside and landside at Chinese airports with novel inputs

ABSTRACT

This paper evaluates the operational performance of airside and landside at Chinese airports with two novel inputs. Furthermore, the airport landside operation is decomposed into passenger-terminal operations and cargo-warehouse operations. One novel input is the capability of the runway system which is introduced into airside performance evaluation. The other novel input is cargo warehousing which is introduced into landside performance evaluation. To address multiple optimal solutions when estimating Returns to Scale in Data Envelopment Analysis, we adopted the Zhu and Shen method. This empirical study shows that neither the number of runways nor total runway length is a genuine index of runway system capability in the evaluation of airside performance. Only four airports achieved full efficiency in all eight measures while eight airports did not achieve any full efficiency. In addition, one airport did not perform well in the benchmark analysis.     

Metaheuristics for efficient aircraft scheduling and re-routing at busy terminal control areas

Intelligent decision support systems for the real-time management of landing and take-off operations can be very effective in helping air traffic controllers to limit airport congestion at busy terminal control areas. The key optimization problem to be solved regards the assignment of airport resources to take-off and landing aircraft and the aircraft sequencing on them. The problem can be formulated as a mixed integer linear program. However, since this problem is strongly NP-hard, heuristic algorithms are typically adopted in practice to compute good quality solutions in a short computation time. This paper presents a number of algorithmic improvements implemented in the AGLIBRARY solver (a state-of-the-art optimization solver to deal with complex routing and scheduling problems) in order to improve the possibility of finding good quality solutions quickly. The proposed framework starts from a good initial solution for the aircraft scheduling problem with fixed routes (given the resources to be traversed by each aircraft), computed via a truncated branch-and-bound algorithm. A metaheuristic is then applied to improve the solution by re-routing some aircraft in the terminal control area. New metaheuristics, based on variable neighbourhood search, tabu search and hybrid schemes, are introduced. Computational experiments are performed on an Italian terminal control area under various types of disturbances, including multiple aircraft delays and a temporarily disrupted runway. The metaheuristics achieve solutions of remarkable quality, within a small computation time, compared with a commercial solver and with the previous versions of AGLIBRARY.     

Airport obstacle surfaces

The most commonly used criteria to determine complicated airport obstacle surfaces are FAR Part 77 imaginary surfaces, TERPS, and the one engine inoperative obstacle identification surface for air carriers. For each obstacle surface there are tradeoffs encountered in our practice between the obstruction penetration and extension of runway, change of flight profile, and allowable aircraft maximum payloads. For the purposes of both airport engineering and airport planning, a better understanding of these different obstacle surfaces and their application is important. In this paper, the differences and relationships between these surfaces are addressed. The conditions for the use of each criterion are discussed. In addition, the FAA's Obstruction Evaluation / Airport Airspace Analysis (OE/AAA) process is reviewed.     

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.     

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.