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.     

On the relationship between airport pricing models

Airport pricing papers can be divided into two approaches. In the traditional approach the demand for airport services depends on airport charges and on congestion costs of both passengers and airlines; the airline market is not formally modeled. In the vertical-structure approach instead, airports provide an input for an airline oligopoly and it is the equilibrium of this downstream market which determines the airports’ demand. We prove, analytically, that the traditional approach to airport pricing is valid if air carriers have no market power, i.e. airlines are atomistic or they behave as price takers (perfect competition) and have constant marginal operational costs. When carriers have market power, this approach may result in a surplus measure that falls short of giving a true measure of social surplus. Furthermore, its use prescribes a traffic level that is, for given capacity, smaller than the socially optimal level. When carriers have market power and consequently both airports and airlines behave strategically, a vertical-structure approach appears a more reasonable approach to airport pricing issues.     

Control strategies for departure process delays at airport passenger terminals

This paper explores the characteristics of process delays at airport passenger terminals and establishes a queuing model for both passengers and baggage served by different connecting type facilities. The impact of delay propagation on other processes and flights is investigated using an analytical approach. In addition, the extra costs incurred on passengers, process operators, and airlines are examined using the delay cost functions. To reduce the impact of process delays, various delay-controlled strategies are proposed, such as setting scheduled times for completion of a process, increasing the number of service counters, and priority service for emergent flights. Taoyuan International Airport in Taiwan is used as a case study when facing special events. Results showed that the model can effectively and efficiently estimate delay propagation and its costs. In addition, processes that are not consecutive allow more buffer time between different operations, which helps ease propagation of delays caused by previous services.     

Predictability impacts of airport surface automation

Past evaluations of airport surface operations automation technologies have focused on capacity utilization, delay mitigation and fuel efficiency impacts. Predictability, while recognized as an important operational performance goal, has received little attention. One reason could be that applicable predictability metrics have not been developed in the context of airport surface operations management. This research fills the gap by proposing metrics for predictability performance evaluation. Using results from a SARDA human-in-the-loop simulation conducted at NASA Ames’ Future Flight Central, we present a comprehensive assessment of the predictability impacts of airport surface automation. A wide range of the impacts is considered, which includes variability in taxi-out time, predictability of take-off time and take-off sequence, entropy of the airfield state, and perceived predictability from users.     

Performance based clustering for benchmarking of US airports

Managing service operations is gaining significant attention in both academic and practitioner circles. In this broad area, performance evaluation and process improvement of airlines and air carriers has been the focus of several studies. Although efficient airport operations are critical for improved performance of airlines and air carriers, few studies have focused on airport performance measurement. This study evaluates the operational efficiencies of 44 major US airports across 5 years using multi-criteria non-parametric models. These efficiency scores are treated by a clustering method in identifying benchmarks for improving poorly performing airports. Efficiency measures are based on four resource input measures including airport operational costs, number of airport employees, gates and runways, and five output measures including operational revenue, passenger flow, commercial and general aviation movement, and total cargo transportation. The methodology presented here can be generalized to other industries and institutions.     

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.     

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.     

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.     

枢纽机场航线网络优化研究

枢纽机场航线网络优化主要解决由于航线网络结构与功能定位不匹配而导致的机场连通性低、航线网络同质化竞争严重、运行效率低下的问题。通过改进引力模型对城市对间的客流量进行预测,以此为预测的客流量为依据之一,以提高机场连通性为目的,构建航线网络优化模型,并进行求解。实现提高枢纽机场连通性、构建符合功能定位的层级网络的目标。并以位于我国中部,具有"连接南北,贯穿东西"地理优势的西安咸阳国际机场为例进行分析。由于国际航线受客观因素较多,本文主要研究国内客运航线,国际及货运不在本文研究之列。     

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.     

Development and demonstration of an integrated decision support system for airport performance analysis

Airport decision makers are frequently facing complex decision-making problems related to airport planning, design, and operations. The airport decision-making process is further perplexed by the large number of stakeholders having different, and sometimes conflicting, objectives regarding the assessment of the airport performance. Despite the rich experience in both models and tools for airport performance analysis, existing models and tools address only fragmented parts of the airport decision-making process. At present, airport stakeholders lack models and tools able to provide an integrated view of the total airport processes and analyze the tradeoffs between the various measures of airport effectiveness. The objective of this paper is threefold: (i) to introduce the concept of total airport performance analysis, (ii) to describe the development of a Decision Support System capable of performing integrated airport analysis, and (iii) to demonstrate the capabilities of this Decision Support System by analyzing a real-world airport planning case of the Athens International Airport.     

Estimating fuel burn impacts of taxi-out delay with implications for gate-hold benefits

The aviation community is actively investigating initiatives to reduce aircraft fuel consumption from surface operations, as surface management strategies may face fewer implementation barriers compared with en route strategies. One fuel-saving initiative for the air transportation system is the possibility of holding aircraft at the gate, or the spot, until the point at which they can taxi unimpeded to the departure runway. The extent to which gate holding strategies have financial and environmental benefits hinges on the quantity of fuel that is consumed during surface operations. A pilot of an aircraft may execute the taxi procedure on a single engine or utilize different engine thrust rates during taxi because of a delay. In the following study, we use airline fuel consumption data to estimate aircraft taxi fuel consumption rates during the “unimpeded” and “delayed” portions of taxi time. We find that the fuel consumption attributed to a minute of taxi-out delay is less than that attributed to minute of unimpeded taxi time; for some aircraft types, the fuel consumption rate for a minute of taxi delay is half of that for unimpeded taxi. It is therefore not appropriate, even for rough calculations, to apply nominal taxi fuel consumption rates to convert delayed taxi-out time into fuel burn. On average we find that eliminating taxi delay would reduce overall flight fuel consumption by about 1%. When we consider the savings on an airport-by-airport basis, we find that for some airports the potential reduction from reducing taxi delay is as much as 2%.     

Benchmarking airports with specific safety performance measures

The purpose of this paper is to develop safety performance measures and test the measures on data for air traffic management failure events. Failure events are classified by the severity of the consequence of occurrence, resulting in the rate of occurrence in severity categories. The safety measures are standard statistics calculated from this “distribution” for comparison of airport operations by stochastic ordering. For comparisons a benchmark is developed from the aggregation of failure data on a set of comparable airports. Airport performance is then compared with the benchmark using the defined safety measures. The benchmark comparison was implemented with failure data for major airports in Canada from 2005 to 2012. The results show a number of patterns and anomalies and some airports perform poorly in comparison to a class of similar operations. We conclude by suggesting benchmarking safety measures as a natural addition to the information system on aviation safety compiled by a national regulatory body to unravel anomalies such as implementation problems of a safety management system.     

Impact of slot controls with a market-based allocation mechanism at San Francisco International Airport

This paper presents an empirical analysis of the possible impact of the application of slot controls as a demand-management measure at San Francisco International Airport (SFO). We examine the specific case of slot controls allocated with a market-based mechanism. The paper first describes the nature of the delay problem at SFO and how slot controls would work to manage demand, briefly reviewing their history in the US. We then describe the methodology used to analyze their potential impact given the assumption of a market-based allocation mechanism and present our findings on their predicted impacts on arrival delays and the nature and level of scheduled passenger air service at the airport. Finally, we present conclusions as to the overall potential of slot controls to alleviate delay at SFO and their non-delay consequences. The methods presented in the paper facilitate a detailed analysis of the incidence of the impact of slot controls on passengers, airlines and individual communities that depend on SFO for access to the national air transportation system.     

Airport apron roundabout – Operational concept and capacity evaluation

The paper presents one of the initial steps in the evaluation process towards possible implementation of an innovative taxiway intersection design at Munich Airport apron. A roundabout is proposed as a potential solution for the 12-line intersection area expected at redesigned Apron 3. Although it is a common solution used in road transport for complex intersections, the roundabout has never previously been used for airport surface operations nor has its possible use been considered or analyzed. The paper presents preliminary design and operations concepts of the apron roundabout, followed by its capacity evaluation under Munich Airport operating conditions. The aim was to analyze whether a roundabout is suitable to replace a conventional intersection, in terms of capacity.     

Modeling taxi drivers’ decisions for improving airport ground access: John F. Kennedy airport case

Taxi service is an important component of airport ground access, which affects the economic competitiveness of an airport and its potential positive impact on the surrounding region. Airports across the globe experience both taxi shortages and excesses due to various factors such as the airport’s proximity to the city center, timing and frequency of flights, and the fare structure. Since taxi drivers are independent entities whose decisions affect the taxi supply at airports, it is important to understand taxi drivers’ decision mechanisms in order to suggest policies and to maintain taxi demand and supply equilibrium at the airports. In this paper, New York City (NYC) taxi drivers’ decisions about airport pick-ups or cruising for customers at the end of each trip is modeled using logistic regression based on a large taxi GPS dataset. The presented approach helps to quantify the potential impacts of parameters and to rank their influence for policy recommendations. The results reveal that spatial variables (mainly related to proximity) have the highest impact on taxi drivers’ airport pickup decisions, followed by temporal, environmental and driver-shift related variables. Along with supplementary information from unstructured taxi driver interviews, the model results are used to suggest policies for the improvement of John F. Kennedy (JFK) airport’s ground access and passenger satisfaction, i.e. the implementation of taxi driver frequent airport server punch cards and a time-specific ride share program.     

Airport demand management: The operations research and economics perspectives and potential synergies

Airport demand management aims to mitigate air traffic congestion by limiting the imbalances between demand and capacity at busy airports through administrative measures (e.g., slot controls) or economic incentives (e.g., congestion pricing, slot auctions). This paper provides an integrated synthesis of the contributions of the fields of operations research/management science (OR/MS) and economics on the subject matter. From an operating standpoint, assessing the benefits of demand management requires estimates of airport capacity and models of airport on-time performance. From a managerial standpoint, the design of demand management mechanisms can be supported by decision-making models of flight scheduling. From an economic standpoint, the welfare impact of congestion pricing, slot controls and slot auctions depends on the market structure at the airport. This paper proposes an integrated framework that underscores the interdependencies between these operating, managerial and economic aspects to foster cross-disciplinary approaches toward more effective demand management policies at busy airports worldwide.     

Multiple hub network and high-speed railway: Connectivity,gateway, and airport leakage

This paper considers the relation between the role of airport as gateway (inter–intra transit airport) and the connectivity between air transport and high-speed rail (HSR) transport to discuss the possibility of a multiple gateway system with HSR. We deal with both international and domestic transport markets in the model analysis. In the international markets, only airlines compete against each other, while in the domestic market airlines and HSR compete against each other. The results suggest that the improvement of connectivity between air and HSR at the airport increases its international passengers, and therefore, that strengthens its role as gateway, for example, gathering more inter–intra transit passengers. However, the results also suggest that the demand of the area which the airport belongs to affects the role of airport as gateway.     

Managing corporate social responsibility strategies of airports: The case of Taiwan’s Taoyuan International Airport Corporation

Airports need to manage corporate social responsibility (CSR) strategies for sustainable development. This paper develops a new structured approach for airports to evaluate, prioritize and categorize CSR strategies, using Taiwan’s Taoyuan International Airport Corporation (TIAC) as an example. Based on TIAC’s CSR-related activities, 18 CSR strategies grouped into 5 CSR goals (corporate governance and finance, green airport and environmental management, service quality and social relationship, employee and work environment management, and safety and security) are identified using the CSR value chain and diamond framework. The pairwise comparison method used in analytic hierarchy process and the decision-making trial and evaluation laboratory method are used respectively to evaluate the relative importance, feasibility and achievability of these 18 strategies and to analyze their causal relationships via expert questionnaire surveys. A new method is developed to plan and manage the implementation of CSR strategies by incorporating the viewpoints of both internal and external stakeholders, thus reflecting the practical effects and strategic implications of the CSR implementation. The result suggests that TIAC’s CSR strategies in relation to airport safety and security, service quality and corporate governance are most significant and have a high implementation priority. This paper contributes to the airport industry and CSR research by proposing a proactive mechanism for quantitatively evaluating, prioritizing and categorizing CSR strategies.     

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.