Airport Ground Research Articles

Efficiency-Based Airport Ground Conflict Detection and Resolution: Integrating Stand Hold Strategy with Constrained Position Shifting

Efficiency-Based Airport Ground Conflict Detection and Resolution: Integrating Stand Hold Strategy with Constrained Position Shifting

How organizational citizenship behaviors promote job performance: evidence from the aviation industry

In the 21st century, the working environment is changing rapidly, and competition is fierce. In industries such as airlines, it is crucial to identify the factors that drive employee performance. This study aims to determine the elements of organizational citizenship behaviors (OCBs) that have an impact on work performance. A mixed research method was employed for the study, which collected survey data from 195 employees of ground service companies in Vietnam, including Saigon Ground Service Company (Sags), Vietnam Airport Ground Service Company (Viags), and Hanoi Ground Service Joint Stock Company (Hgs). The results revealed that five factors of OCBs affect job performance, ranked in descending order: (1) Voice-speaking up about concerns, (2) civic virtue, (3) conscientiousness, (4) courtesy, and (5) altruism. The study also proposed some implications for managers of ground service companies to enhance their employees’ job performance.

Resilience assessment of airport aircraft area network operations under thunderstorm weather

Thunderstorms can cause a decrease in airports' dynamic capacity, and taxiway runway capacity is a key element of airport airfield operations. In this paper, based on the cell transmission model (CTM), the meteorological operation parameters of thunderstorms are set according to the airport aircraft taxiing rules, and a CTM is proposed for evaluating the resilience of the airport aircraft area operation network under thunderstorm weather. Based on the CTM, the network performance parameters are obtained, and the number of aircraft waiting for the network and the network operation efficiency are used as the basic performance indicators to establish a resilience index that reflects the dynamic change in the resilience of the thunderstorm meteorological interference network. Finally, this paper collects and analyzes the operation data of Tianjin Binhai International Airport in 2019 to build a CTM for aircraft operation in the flight area. The results show that the model's simulated airport departure operation data is almost consistent with the trend of the actual departure operation data, which verifies that the model can be used to simulate traffic for the airport airfield operation network. In addition, based on the resilience index, the sensitivity analysis of different parameters to network performance under thunderstorm weather was also studied. Based on the evaluation results of different parameter scenarios and indicators, we drew the resilience map of the airport ground operation network, and found that the network shows different resilience levels in different thunderstorm level scenarios. This study provides a great method and evaluation index for modeling and resilience evaluation of aircraft operation networks in the airfield, which is expected to improve airport operations, reduce flight delays, and improve service quality.

Airport Ground Optimizer (AGO): A decision support system initiative for air traffic controllers with optimization and decision-aid algorithms

The growing global air traffic has necessitated more efficient ground management in airports, especially during peak hours. Current approaches mainly consist of radar-based systems and radio communications, which provide limited visual assistance. Hence, Decision Support Systems (DSS) are designed to assist human Air Traffic Controllers (ATCos) by providing reliable recommendations based on current data and situations. The Airport Ground Optimizer (AGO) is a DSS designed for ATCos to manage the complexities of ground traffic in airports. It is based on advanced optimization algorithms and intuitive user interfaces, offering an enhanced operational experience. AGO uses mixed-integer programming (AGO-MIP) and stochastic programming (AGO-STC) to detect conflicts based on expected gate release and taxi times, and then optimizes the entire schedule to minimize hold fuels, resolve conflicts, and reduce fuel consumption, emissions, and delay times. Its key strength lies in translating complex mathematical solutions into user-friendly visual representations. AGO's core functionality includes comprehensive visualizations such as position charts, delay graphs, and potential conflict maps, providing a clear, real-time picture of ground operations for informed decision-making. AGO's queue and gate occupancy analysis calculates and visualizes the maximum queue length and concurrent number of aircraft at gates, enhancing airport capacity, reducing aircraft waiting times, and streamlining ground traffic flow. Simulated in a high-traffic Turkish airport layout, AGO-MIP demonstrated significant improvement in operational efficiency compared to traditional First Come First Served (FCFS) approach. AGO outperformed the traditional FCFS approach, reducing hold fuel by 27.9%, cutting delay time by 21.6%, lowering HC, CO, and NOx emissions by 16.4%, 22.5%, and 29.3% respectively, and decreasing the maximum queue length and its duration by 15.3% and 26.6%, as well as decreasing the number of delayed aircraft by 4.8%. The AGO-STC is also tested using pushback release uncertainties in the case airport, providing robust and feasible sequences, clear feedback for all possible scenarios, and detailed outcomes for each scenario. The study concludes by discussing potential developments and current issues of the tool in detail.

Evaluation of digital solutions for passenger attitudes towards health measures at Dalaman airport during COVID-19 period

During the COVID-19 pandemic, the Ministry of Transport and Infrastructure and airline companies implemented various measures to prevent the spread of the virus and reduce the risk of transmission. Among the various measures implemented, those utilizing digital technologies to minimize contact between passengers at airport terminals and ground services personnel have been particularly noteworthy. Self-service technologies not only enhance time and space efficiency but also minimize interpersonal contact. This research aims to evaluate the positive impact of COVID-19 measures implemented at Dalaman Airport on passenger satisfaction and to examine the role of digital technologies in this effect. To this end, face-to-face surveys were conducted with at least 415 passengers at Dalaman Airport between October and November 2023. The data obtained were analyzed using the SPSS program to determine the effects of COVID-19 measures and digital technologies on passenger satisfaction. The research factor analysis, reliability analysis, correlation, and regression analyses to examine the relationships between satisfaction, digitization, and measures reducing discomfort, revealing significantly positive relationships. As a result, this research recommends airport management to realign technology investments and customer service policies centered on passenger satisfaction. Digitalisation efforts can facilitate passengers to better adapt to new norms and provide a safer and more comfortable travel experience. The research also highlights that future studies with generalized findings across a wider range of airports and passenger demographics will develop a more comprehensive understanding of how digital technologies can be used more effectively in the aviation sector.

Measuring Self-Actualizing Tendency of Airport Ground Staff and Conducting Differential Analysis

Measuring Self-Actualizing Tendency of Airport Ground Staff and Conducting Differential Analysis

Preferences and welfare impacts of new metro serving airport access

The construction of a new rail infrastructureto connectairportswith cities plays a vital role in enhancing the accessibility of airport ground access and mitigating negative externalities resulting fromautomobiles. To identify air travelers’ preferences for airport ground access by considering a new metro line in Taiwan, we develop nested logit models, which combine revealed and stated preference data. The results reveal significant effects of travel time, travel cost, and individual characteristics; the metro and taxis are highly substituted for airport access. Consumer surplus or accessibility is not equally distributed across air travelers. Travelers who are female, young adults, lower income, and without vehicles in the household obtain considerable consumer benefits from using the new metro. Policy incentives to time and cost have a small impact on the increase in metro share, but consumer surplus surges considerably.

Multi-criteria decision-making for the selection of best airport ground access mode with a new fuzzy rough-entropy based method

In order to cope with the inherent complexities and uncertainties of settings such as transportation problems, the adoption of proper decision procedures becomes a pivotal issue. Particularly, multi-criteria group decision-making (MCGDM) uses multiple evaluations of the options based on several criteria to select the optimal choice and/or rank the alternatives. In this paper we are interested in the Entropy-REGIME method for MCGDM and its ability to handle uncertainty in the presence of fuzzy rough numbers (that allow the practitioner to represent and process imprecise data). To this end we propose a hybrid framework of the fuzzy rough-entropy based REGIME method that involves two main components: fuzzy rough-entropy for the evaluation of the objective weights of the decision criteria, and fuzzy rough-REGIME to rank the alternatives based on the weighted criteria. Its motivation is a case study that concerns the selection of the best transport mode to access Istanbul newly constructed airport. We consider four alternatives for ground access options, namely, underground metro, bus rapid transit, light rail transit, and premium bus services. Our findings show that an underground metro system is the optimal mode, followed by light rail transit, bus rapid transit, and premium bus services. Additionally, to demonstrate the superiority and effectiveness of the proposed technique, comparisons are made with existing methods.

Aircraft Taxi Path Optimization Considering Environmental Impacts Based on a Bilevel Spatial–Temporal Optimization Model

Aircraft taxiing emissions are the main source of carbon dioxide and other pollutant gas emissions during airport ground operations. It is crucial to optimize aircraft taxiing from both spatial and temporal perspectives to improve airport operation efficiency and reduce aviation emissions. In this paper, a bilevel spatial and temporal optimization model of aircraft taxiing is constructed. The upper-level model optimizes the aircraft taxiing path, and the lower-level model optimizes the taxiing start time of the aircraft. By the iterative optimization of the upper- and lower-level interactions, the aviation fuel consumption, flight waiting time, and number of taxiing conflicts are reduced. To improve the calculation accuracy, the depth-first search algorithm is utilized to generate the set of available paths for aircraft during the model solution process, and a model solution method based on the genetic algorithm is constructed. Simulation experiments using Tianjin Binhai International Airport as the research object show that adopting the waiting taxiing strategy can effectively avoid taxiing conflicts and reduce aviation fuel consumption by 753.18 kg and 188.84 kg compared to the available path sets generated using Dijkstra’s algorithm and those created manually based on experience, respectively. Conversely, adopting an immediate taxi-out strategy caused 54 taxiing conflicts and increased aviation fuel consumption by 49.44 kg. These results can provide safe and environmentally friendly taxiing strategies for the sustainable development of the air transportation industry.

Analysis of Traffic Organisation in the Kiss-and-Fly Zone of Kraków Airport: Eye-Tracking Study

When choosing the way to come to airports, quite a large number of passengers prefer when they are dropped off/picked up at airports using kiss-and-fly (K&F) zones. Such a travel option is associated with a special traffic organisation on the airport ground access. As there are no common regulations or standards when creating such a complex infrastructure object, it could be a challenge for drivers when searching and moving through it. Therefore, the main aim of the presented study was to assess and verify the eye-tracking technique as an objective tool, which can allow one to identify and estimate confusion points met by road users when using such an object. The field tests with 23 drivers were conducted in the K&F zone of Kraków Airport, and the data analysis focused on the traffic organisation and road signage as its key and integral parts. The eye-tracking approach allowed us to clearly find confusing situations for drivers as well as explain their reasons confirming its suitability and usefulness for the declared aim. Also, the perception of standardised and unstandardised signage of the K&F zone as well as the influence of route familiarity for drivers were discussed.

Leveraging Emerging Technologies for Enhanced Airport Ground Movement Management Efficiency and Reliability

The Executive summary serves to give the highlights of the research paper and an overview of the objectives, methods used, key findings and implications. It is a brief rundown of the whole research document and provides time-pressed readers with some insights onto the study without having to go into deeper details. Introduction: This research paper examines how blockchain, edge computing and autonomous systems can be integrated inside airports in order to enhance performance and reliability of airport ground movement management. There is need for innovative approaches towards optimizing ground movement in highly complex airports to ensure that they operate seamlessly in a growing air traffic scenario. Objectives: The main aim of this study is to explore how blockchain, edge computing and autonomous systems could change airport ground movement management entirely. These technologies will be exploited for improving data sharing, enhancing real-time processing capabilities as well as enabling automatic decision support services on the ground operations. Methodology: In this case a mixed method approach has been used which involves qualitative and quantitative analysis. Qualitative methods like surveys and questionnaires are done so as researchers get insights from different stakeholders, Integrating various stakeholders, including airlines, airports, and regulators, regarding their perspectives on integrating new technologies into ground movement management!!! Quantitative methods involve data analysis to assess the effectiveness and efficiency of proposed technological solutions. Additionally, simulations and case studies are conducted to evaluate the impact of these technologies on ground movement optimization. Key Findings: The research yields promising results, indicating significant improvements in routing efficiency, reduced taxiing times, and increased operational reliability. The integration of blockchain facilitates secure data sharing, while edge computing enables real-time processing, leading to faster decision-making in ground movement management! Autonomous systems contribute to optimizing resource routing and allocation decisions, further enhancing operational efficiency. Implications and Recommendations: The findings of the research carry both theoretical and practical implications. Theoretical implications include advancing knowledge in the field of airport ground movement management by exploring the potential of emerging technologies. On a practical level, the research provides valuable insights for airport stakeholders seeking to modernize their ground movement control systems?? Recommendations include addressing the complexity of integrating multiple emerging technologies and overcoming challenges related to data security and system interoperability. Conclusion: In conclusion, the research underscores the significance of integrating blockchain, edge computing, and autonomous systems into airport traffic management to enhance efficiency and reliability!!! By addressing key challenges in ground movement management, the study paves the way for more streamlined and resilient airport operations, ultimately benefiting the aviation industry as a whole.

Airport–Industry–City Integrated Accessibility Using Big Data Case View from Beijing Capital International Airport

Big data technology can help collect, analyze, and process large-scale transportation, population, economic, and other relevant data, which has been proven to be more accurate in assessing the accessibility of different areas. An aerotropolis is composed of the airport as the core, airport-related industry as the link, and the airport-oriented city as the carrier, airport–industry–city (AIC) system. To better grasp the development quality of aerotropolises, an AIC integrated accessibility measurement model is constructed comprising the accessibility of airport route network, airport ground traffic, and airport information coverage. Using big data of traffic, network and information from 2001 to 2020, we apply the model to the Beijing Capital International Airport (PEK) aerotropolis. The results show that PEK’s AIC connectivity exceeded 1 for the first time in 2008, reaching 1.0890, which the range of the scale is [0, +∞]. It fluctuated significantly from 2017 to 2020, showing a double life-cycle S-curve. So, the PEK aerotropolis’ development can be divided into four stages: germination (before 2001), high-speed development (2002–2011), gradual formation (2012–2019), and “seeking change in the process of change” (after 2020). Our model offers a new tool for identifying the development stages of aerotropolises and for improving connectivity—namely, improving the accessibility of the airport node network, the layout of airside-preferring enterprises, and the network structure of new Internet-based airport cities. Obviously, the AIC integrated accessibility can indeed guide the scientific development of an aerotropolis.

Joint runway–gate assignment based on the Branch-and-Price algorithm

Airport runway assignment and gate assignment are both crucial problems for large multirunway airports. A cooperative schedule for the runway and gate can have a significant effect on airport ground operation efficiency and safety. This paper focuses on the joint assignment problem of runways and gates considering parking time differences and airline preferences. A quadratic model is established to reduce taxiing fuel consumption loss and increase the robustness of gate assignment. An improved branch-and-price algorithm is proposed by utilizing an improved pulse algorithm and various acceleration strategies to improve the solution performance. The actual flight data at an international hub airport are utilized to validate the proposed model. The results indicate that the joint assignment model can effectively reduce ground taxiing loss, optimize gate assignment robustness, and increase the utilization rate of contact gates. The proposed algorithm also achieves better computational accuracy and efficiency.

Routing and Scheduling in Multigraphs With Time Constraints—A Memetic Approach for Airport Ground Movement

Routing and scheduling problems with increasingly realistic modelling approaches often entail the consideration of multiple objectives, time constraints, and modelling the system as a multigraph. This detailed modelling approach has increased computational complexity and may also lead to violation of the additivity property of the costs. In the worst scenario, increased complexity makes the problem intractable for exact algorithms. Even when the problem is solvable, exact algorithms may not provide solutions within the given time budget, and the found solutions are not guaranteed to be optimal due to the additivity property violation. Approximate solution methods become more suitable in this case. This paper focuses on one particular real-world application, the Airport Ground Movement Problem, where both time constraints and parallel arcs are involved. We introduce a novel Memetic Algorithm for Routing in Multigraphs with Time constraints (MARMT) and present a comprehensive study of its different variants based on diverse genetic representation methods. We propose a local search operator that enhances search efficiency and effectiveness. MARMT is tested on real data based on two airports of different sizes. Our results show that MARMT does not suffer from the non-additivity property problem as it outperforms the state-of-the-art exact algorithm when allowed to converge. When a time budget of 10 seconds is imposed on MARMT, it is able to provide solutions with quality comparable (within 1-5% degradation) to the ones given by the exact algorithm with respect to the aggregated objective values. MARMT can be adapted for other applications, such as train operations.

Exploring factors and customer perceptions of airport services: A quantitative textual analysis

<span lang="EN-GB">This study conducted an analysis of 1500 user generated content from Google Travel to examine the factors influencing airport services and customer perceptions. Quantitative textual analysis is employed to extract meaningful insights. Our findings highlighted the most frequently used words in airport user generated content, reflecting critical aspects of airport experiences such as the airport itself, the quality of service, and international travel. A cluster analysis revealed five distinct clusters, representing flight operations, location, views, customer feelings, and intangible services. A co-occurrence network analysis showed strong correlations among keywords associated with positive experiences, underscoring the importance of service quality and infrastructure in customer satisfaction. Furthermore, through topic modeling, we categorized words into five distinct groups: airport flights, ground services, international services, customer experience, and location. The practical implications of this study are substantial. The insights can help airport management identify strengths and areas needing improvement, ultimately enhancing customer satisfaction and the overall airport experience.</span>

Towards solving the airport ground workforce dilemma: A literature review on hiring, scheduling, retention, and digitalization in the airport industry

The airport ground workforce is critical for a smooth operation of the entire aviation industry. This fact has been embarrassingly exposed during the recovery from the COVID-19 pandemic in Summer 2022, when various airlines and airports had to cut flights to reduce excessive delays, lost luggage, and other downstream effects, in absence of ground workforce sufficient to handle the rising travel demands. Our study discusses the challenges inherent to solving this airport ground workforce dilemma, partially caused and amplified by excessive layoffs during the peak of COVID-19. These industry challenges are dissected into four categories: Hiring new talents, workforce scheduling, staff retention, and digitalization. For each challenge, we review the existing literature on the subject and discuss potential avenues for solving the existing airport ground workforce dilemma. Our review covers more than 100 papers from the highly scattered literature on the subject and, accordingly, we believe that our study may serve as a starting point for coordinated efforts by the scientific community to tackle this challenging problem.

Developing ESP learning materials for airport ground handling services students: A needs analysis

Developing ESP learning materials for airport ground handling services students: A needs analysis

Assessing airport ground access interventions: An integrated approach combining mode choice modeling and microscopic traffic simulation

Airport ground accessibility is an important and integral part of airport planning, which significantly impacts airport attractiveness and its environmental sustainability. In this paper, we propose the combined use of road micro-simulation with meso-scope discrete choice modeling to support the evaluation of airport access interventions. The proposed integrated framework allows us to appraise mode choice and infrastructural interventions simultaneously to accurately assess the performance of airport access road networks in accommodating larger traffic. We validate and demonstrate the benefits of the proposed approach by applying it to a real-world case study based on the Milan–Bergamo Airport (BGY), in which (i) we conduct an ex-post counterfactual analysis to assess the impact of the interventions undertaken to mitigate the large growth (54.6%) in the years 2013–2019, and (ii) evaluate future scenarios up to 2030 considering the additional expected growth and introduction of direct rail services. Results indicate that BGY’s ground access interventions have contributed to effectively accommodating traffic growth by significantly mitigating road congestion and associated pollutant emissions. Results also inform on the need and effectiveness of additional interventions to meet the substantial expected future growth.

Reliable and robust scheduling of airport operation resources by simulation optimization feedback and conflict resolution

Reliable and robust airport flight ground service resources collaborative scheduling has emerged as an issue of major concern at congested airports, which has great significance on airport service quality and operation efficiency. Due to the uncertainty of the service process of multiple vehicles in airport ground operations, the combination of simulation and optimization (sim-opt) techniques has been proven to be an effective means to solve the collaborative scheduling problem. However, existing models still have limitations on the reliability of feasible solutions and the robustness of evaluations. In this work, we developed a conflict resolution based sim-opt framework that combines the search capability of mathematical optimization models with the ability of simulation models to describe uncertainty. The dynamic window is introduced to divide the flight zone into multiple sub-intervals, which allows for iterative search and evaluation of the optimal schedule solution while reducing model calculation time. Additionally, a matching algorithm based on slack and tight constraints is proposed to optimize the possible resource requirements of each vehicle, thereby improving the initial schedule solution’s search depth and reliability. Furthermore, a conflict resolution feedback mechanism between adjacent windows is constructed to optimize the scheduling plan, reducing misjudgment and omission of the optimal solution and enhancing the sim-opt framework’s robustness. Finally, experiments on real airport datasets of three different scales demonstrate that our proposed method efficiently allocates resources with a smaller flight delay time as well as reducing total vehicle cost time during the flight ground service process.

An agent-based simulator for airport ground handling services

Airport ground handling plays an essential role in shortening the turnaround time for better utilization of aircraft that can reduce the cost per flight. One of the key challenges for improving the efficiency of airport ground operations is to comprehensively simulate the ground handling processes to optimize and evaluate various operation strategies. In this work, we develop an agent-based simulator that specifically focuses on the whole process of airport ground handling from landing to takeoff. It allows different types of agents, i.e. aircraft, ground vehicles, operators, and dispatchers, to execute their own behaviors according to the ground operation characteristics. The interactions among different agents are also modeled according to the specific service agreements. We use the Shanghai Pudong International Airport (PVG) for the case study to demonstrate the interfaces and outputs of the simulator including the simulated flight information, the progress of ground handling services, airfield status, etc. With the developed simulator, we could not only reproduce the real-world operations of different types of services but also have enough potential to optimize and evaluate various airport ground operation strategies under a series of complex scenarios.