The rapidly evolving aviation environment, driven by the Fourth Industrial Revolution, encompasses smart operations, communication technology, and automation. Airports are increasingly developing new autonomous innovation strategies to meet sustainability goals and address future challenges, such as shifting labor markets, working conditions, and digitalization (ACI World, 2019). This paper explores high-level governance strategies, a benchmarking study, that facilitates this transition. It aims to identify the key characteristics and features of the benchmarking study applicable to the development of autonomous airside operations. It also examines areas for improvement in operations, focusing on Key Performance Areas (KPAs) and strategic objectives related to airside automation. The findings highlight several essential performance areas and formulate it to a tailored benchmarking study that airports or aviation stakeholders can adopt to develop automation in airside operations. These criteria and features are summarized into a benchmarking framework that reflects strategy objectives. This paper contributes a valuable benchmarking methodology, supporting the growing global aviation demand for improvements toward more sustainable and smart autonomous airside operations. This outcome motivates aviation stakeholders to innovate to meet environmental and social sustainability goals.
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This research examines the impact of transitioning to an autonomous operation on the airside of Schiphol airport, with a specific focus on emissions that affect both the environment and the staff working within airport premises. This study will explore current emissions from vehicles on Schiphol's airside, assessing their environmental impact and identifying harmful emissions. It will evaluate potential solutions, notably the role of electric vehicles, comparing this to the status quo before mapping the transition to an autonomous airside and its environmental consequences. A significant focus will be on the implications for staff working in these conditions. Additionally, it will review relevant laws and regulations to propose improvements, aiming to enhance Schiphol's environmental footprint. Conducted by Bright Sky for Schiphol Airport, this research aims to address overlooked harmful substances at the airport, seeking prompt solutions. Utilized by Schiphol, the findings will shed light on the necessity for innovation towards electric and autonomous vehicles, underlining the urgency for environmental improvements and technological advancements to tackle pollution issues effectively.
MULTIFILE
The adoption of electric autonomous vehicles (EAVs) is set to revolutionize airport ground operations. Airports are increasingly developing new autonomous innovation strategies to meet sustainability goals and address future challenges, such as shifting labor markets, evolving working conditions, and the growing impact of digitalization [1]. The traditional business model, in which manufacturers sell vehicles to operators (ground handlers), may no longer be relevant. The increasing complexity and advancement of EAVs will drive up costs, making the ownership model less appealing and shifting the focus from product-oriented to service-oriented models. This paper aims to provide a conceptual framework for potential business models for the implementation of EAVs in airport airside operations.
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In this paper, a general approach for modeling airport operations is presented. Airport operations have been extensively studied in the last decades ranging from airspace, airside and landside operations. Due to the nature of the system, simulation techniques have emerged as a powerful approach for dealing with the variability of these operations. However, in most of the studies, the different elements are studied in an individual fashion. The aim of this paper, is to overcome this limitation by presenting a methodological approach where airport operations are modeled together, such as airspace and airside. The contribution of this approach is that the resolution level for the different elements is similar therefore the interface issues between them is minimized. The framework can be used by practitioners for simulating complex systems like airspace-airside operations or multi-airport systems. The framework is illustrated by presenting a case study analyzed by the authors.
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In this paper, a general approach for modeling airport operations is presented. Airport operations have been extensively studied in the last decades ranging from airspace, airside and landside operations. Due to the nature of the system, simulation techniques have emerged as a powerful approach for dealing with the variability of these operations. However, in most of the studies, the different elements are studied in an individual fashion. The aim of this paper, is to overcome this limitation by presenting a methodological approach where airport operations are modeled together, such as airspace and airside. The contribution of this approach is that the resolution level for the different elements is similar therefore the interface issues between them is minimized. The framework can be used by practitioners for simulating complex systems like airspace-airside operations or multi-airport systems. The framework is illustrated by presenting a case study analyzed by the authors.
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Recently KLM has revealed the plan to downsize the full-freight cargo fleet in Schiphol Airport, for that reason it is important for the company and the airport to explore the consequences of moving the cargo transported by the full freighters into the bellies of the passenger flights. The consequences of this action in terms of capacity and requirements are still unknown for the stakeholders. The current study illustrates that once the freighters are phased out, the commercial traffic needs to adjust mainly their load factors in order to absorb the cargo that was previously transported by the full freighters. The current model is a version that includes the airside operation of the airport and also the vehicle movement which allows addressing the uncertainties of the operation as well as the limitations and potential problems of the phasing-out action.
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KLM is downsizing the full-freight cargo fleet in Schiphol Airport, for that reason it is important for the company and the airport to explore the consequences of moving the cargo transported by the full freighters into the bellies of the passenger flights. The consequences of this action in terms of capacity and requirements are still unknown. The current study illustrates how to analyse the uncertainty present in the system for identifying the limitations and potential consequences of the reduction of full freighter fleet. The options we identify for coping with the current demand is by adjusting their load factors or increase the number of flights. The current model includes the airside operation of the airport, the truck movements and the traffic that arrives at Schiphol which allows addressing the impact of uncertainties of the operation as well as the limitations and potential problems of the phasing-out action.
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Airport capacity, expressed as the maximum number of air traffic movements that can be accommodated during a given period of time under given conditions, has become a hard constraint to the air transportation, due to the scarce amount of resources on the ground and restrictions in the airspace. Usually the problem of capacity at airports is studied separating airspace operations from ground operations, but it is evident that the two areas are tied to each other. This work aims at developing a simulation model that takes into account both airspace and ground operations. The approach used is a divide and conquer approach, which allows the combination of four different models. The four models refer to the airside, and airspace operations. This approach allows to evaluate the system from diffrent angles depending on the scope of the study, the results show the analytic potential of this approach.
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This study introduces a novel methodology for the post-analysis of operational predictability by leveraging timestamps collected through the Airport Collaborative Decision Making (A-CDM) framework. Focusing on the start-up and departure phases, the analysis highlights the importance of accurately planning and managing key timestamps, such as the Target Off-Block Time (TOBT) and Target Start-Up Approval Time (TSAT), which are critical for operational efficiency. Using one week of sample data from Schiphol Airport, this research demonstrates the potential benefits of the proposed framework in improving predictability during the start-up phase, particularly by identifying and analyzing outliers and anomalies. The start-up phase, a critical component of the outbound process, was broken down into subphases to allow for a more detailed assessment. The findings suggest that while 96% of flights maintain TOBT accuracy within ±20 minutes, 68% of flights miss their TOBT by 2 to 17.5 minutes, with 364 notable outliers. These deviations highlight areas for further investigation, with future work aiming to explore the impact of influencing factors such as weather, resource availability, and support tools. The proposed framework serves as a foundation for improving operational predictability and efficiency at airports.
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Airports and surrounding airspaces are limited in terms of capacity and represent the major bottlenecks of the air traffic management system. This paper addresses the problems of terminal airspace management and airport congestion management at the macroscopic level through the integrated control of arrivals and departures. Conflict detection and resolution methods are applied to a predefined terminal route structure. Different airside components are modeled using network abstraction. Speed, arrival and departure times, and runway assignment are managed by using an optimization method. An adapted simulated annealing heuristic combined with a time decomposition approach is proposed to solve the corresponding problem. Computational experiments performed on case studies of Paris Charles De-Gaulle airport show some potential improvements: First, when the airport capacity is decreased, until a certain threshold, the overload can be mitigated properly by adjusting the aircraft entry time in the Terminal Maneuvering Area and the pushback time. Second, landing and take-off runway assignments in peak hours with imbalanced runway throughputs can significantly reduce flight delays. A decrease of 37% arrival delays and 36% departure delays was reached compared to baseline case.
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