Dit eindrapport behandelt het onderzoek van CDM@Airports, gericht op Collaborative Decision Making in de logistieke processen van luchtvrachtafhandeling op Nederlandse luchthavens. Dit project, met een looptijd van ruim twee jaar, is gestart op 8 november 2021 en geëindigd op 31 december 2023. HET PROJECT CDM@AIRPORTS OMVAT DRIE WERKPAKKETTEN: 1. Projectmanagement, dit betreft de algehele aansturing van het project incl. stuurgroep, werkgroep en stakeholdermanagement. 2. Onderzoeksactiviteiten, bestaande uit a) cross-chain-samenwerking, b) duurzaamheid en c) adoptie van digitale oplossingen voor datagedreven logistiek. 3. Management van een living lab, een ‘quadruple-helix-setting’ die fysieke en digitale leeromgevingen integreert voor onderwijs en multidisciplinair toegepast onderzoek.
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The constant growth of air traffic, especially in Europe, is putting pressure on airports, which, in turn, are suffering congestion problems. The airspace surrounding airport, terminal manoeuvring area (TMA), is particularly congested, since it accommodates all the converging traffic to and from airports. Besides airspace, airport ground capacity is also facing congestion problems, as the inefficiencies coming from airspace operations are transferred to airport ground and vice versa. The main consequences of congestion at airport airspace and ground, is given by the amount of delay generated, which is, in turn, transferred to other airports within the network. Congestion problems affect also the workload of air traffic controllers that need to handle this big amount of traffic.This thesis deals with the optimization of the integrated airport operations, considering the airport from a holistic point of view, by including operations such as airspace and ground together. Unlike other studies in this field of research, this thesis contributes by supporting the decisions of air traffic controllers regarding aircraft sequencing and by mitigating congestion on the airport ground area. The airport ground operations and airspace operations can be tackled with two different levels of abstractions, macroscopic or microscopic, based on the time-frame for decision-making purposes. In this thesis, the airport operations are modeled at a macroscopic level.The problem is formulated as an optimization model by identifying an objective function that considers the amount of conflicts in the airspace and capacity overload on the airport ground; constraints given by regulations on separation minima between consecutive aircraft in the airspace and on the runway; decision variables related to aircraft entry time and entry speed in the airspace, landing runway and departing runway choice and pushback time. The optimization model is solved by implementing a sliding window approach and an adapted version of the metaheuristic simulated annealing. Uncertainty is included in the operations by developing a simulation model and by including stochastic variables that represent the most significant sources of uncertainty when considering operations at a macroscopic level, such as deviation from the entry time in the airspace, deviation in the average taxi time and deviation in the pushback time. In this thesis, optimization and simulation techniques are combined together by developing two methods that aim at improving the solution robustness and feasibility. The first method acts as a validation tool for the optimized solution, and it improves the robustness of solution by iteratively fine-tuning some of the optimization model input parameters. The second method embeds the optimization in a simulation environment by taking full advantage of the sliding window approach and creating a loop for a continuous improvement of the optimized solution at each window of the sliding window approach. Both methods prove to be effective by improving the performance, lowering the total amount of conflicts up to 23.33% for the first method and up to 11.2% for the second method, however, in contrast to the deterministic method, the two methods they are not able to achieve a conflict-free scenario due to the effect of uncertainty.In general, the research conducted in this thesis highlights that uncertainty is a factor that affects to a large extent the feasibility of optimized solution when applied to real-world instances, and it, moreover, confirms that using simulation together with optimization has the potentiality toivdeal with uncertainty. The framework developed can be potentially applied to similar problems and different optimization solving methods can be adapted to it.Keywords: Optimization, Simulation, Integrated airport operations, Uncertainty
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This study presents a model-based analysis of the groundconnectivity performance of the future Santa Lucia-Mexico City multi-airport system. The plan of the currentgovernment is to connect the two airports by a dedicatedline, either by bus or other transport so that passengersand airlines can get the benefit of a coordinatedoperation. Performance indicators such as minimumconnecting time, vehicle utilization and passengerwaiting time are used to evaluate the future performance.Results reveal that when all passengers are allowed to usethe connection, a big number of vehicles are required forproviding a good level of service while in the case of arestricted use to only transfer passengers the operationwith Bus would have a good performance.
The carbon dioxide emissions of aviation play an important role in many studies and databases. But unfortunately, a detailed and reliable overview of emission factors, and algorithms to calculate these based on factors like seating class, airline type, and aircraft type, did not exist for the Dutch aviation sector. This study calculated such emissions for a sample of over 5000 international flights in 2019 from the 5 Dutch main airports. The data about the flights were gathered from FlightRadar and enriched with seating capacities specific to the airline performing ten flights. in this way, emissions could be assigned to each of the four seating classes (economy, economy-plus, business and first). By aggregating the data to airline types and distance of the flight, algorithms were developed that help researchers and policy-makers to calculate the emissions. Societal IssueThe carbon footprint of Dutch aviation is about 10% of the total footprint. To prevent the world to exceed 1.5 degrees C and enter 'dangerous climate change', emissions need to decline to zero before 2050. This study helps assess and understand current aviation emissions from Dutch airports.Benefit to societyThe results were an update of emissions factors as used by the funding organisation, MilieuCentraal, and the official emission factors list (https://www.co2emissiefactoren.nl/lijst-emissiefactoren/).
INCLAVI will address the skills mismatches that exist in the aviation sector related to the freedom of movement of persons with disabilities and accessibility requirements in line with the EC Strategy for the Rights of Persons with Disabilities 2021-2030.The project accomplishes this through rigorous cooperation between key global industry and labour market actors combined with a world-class HEI and VET consortium. INCLAVI will also further improve the collaboration between HEIs and VET.INCLAVI will design and co-create a new training curriculum utilising expertise from HEI, VET and Industry Actors to support the reskilling of aviation sector employees and key target groups who have a role in the passenger journey of PwDs from door to door. The training will address students and professionals in areas of work related to travel agencies, airports, and airlines.
In the SensEQuake project, the Research Centre for Built Environment NoorderRuimte of Hanze University of Applied Sciences, StabiAlert, Target Holding and NHL Stenden Leeuwarden are investigating the following question:How can we provide relevant and understandable information to support decision makers when an earthquake has occurred?In case of a crisis such as an earthquake, parties such as the provincial government, large company sites, airports or hospitals need information on the scope and severity of the effect of the crisis.Systematic updates of the actual situation on site are of the essence for emergency services. At present only a small amount of the data necessary for this information needed is being collected. And the data that is collected is not processed into relevant and easily understandable information for the decision makers. This project aims to fill this gap.The objective of the project is to integrate the existing sensor technologies into a decision support system, allowing a wider and more immediate use of sensor data for public interest, particularly in crisis times.A heat-map will be produced based on scenario earthquakes and loss (hazard and risk assessment) estimation tools. After running several scenario quakes, critical points in respect to the expected damages and the distribution of existing sensors will be defined. More sensors in critical locations will also be placed to create a high enough resolution.
