Dealing with Adverse Weather Conditions by Enhanced Collaborative Decision Making in a TAM APOC

Piekert, Florian; Carstengerdes, Nils; Suikat, Reiner; Schier, Sebastian

doi:10.1007/978-981-33-4669-7_8

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…However, there was clear indication that the solution improves resilience, and provides benefits for predictability and punctuality of airport operations. Regarding human performance, Piekert et al (2019) presented first assessment results, providing evidence of an operator perceived better collaborative decisionmaking process when using the project tool suite and by following the updated SESAR collaborative decision-making procedures.…”

Section: Deficiencies and Research Challengesmentioning

confidence: 99%

Metrics to Evaluate Multi-Stakeholder Airport Control Center Decision-Making Processes - a Critical Discussion

Piekert¹,

Carstengerdes²,

Schier³

et al. 2023

Human Factors in Transportation

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Since the beginning of the century, airport management decision-making processes have been under scientific discussion. The introduction of Airport Collaborative Decision Making (A CDM) has set an operational standard which is a about to be succeeded by Total Airport Management and Performance Based Airport Management. Within the design and validation of these concepts and the necessary tools multiple assessments of the decision-making processes have been made. Although being under research for almost 20 years, the right selection of metrics to evaluate the decision-making processes remains still a challenge. Reflecting the different stakeholder objectives and the intricate dependent working processes into metrics and performance indicators is complex and was in some cases not sensitive to the introduced operational improvement.Summarizing the experiences of the past, this paper suggests a novel approach towards the evaluation of airport control centre decision-making processes. This approach assesses performance on bases of comprehensive indicators such as costs and decision time which are valid for all stakeholders. It allows the application of computational power to calculate reliable reference values as well as to identify optimization potentials. Moreover, this paper suggests to encounter objective metrics for human factors aspects as well as to consider additional communication and personality indicators. Last but not least recurrence analysis and cross-lagged panel designs are introduced to analyse effects over time and causal relationships between human factors and performance indicators.This novel approach to decision-making evaluation leads away from single performance indicator selection and assessment to a more comprehensive evaluation of the airport in connection with highly sophisticated communication pattern analysis.

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Section: Deficiencies and Research Challengesmentioning

confidence: 99%

Metrics to Evaluate Multi-Stakeholder Airport Control Center Decision-Making Processes - a Critical Discussion

Piekert¹,

Carstengerdes²,

Schier³

et al. 2023

Human Factors in Transportation

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“…The terminal is located between these runways. Oslo has been subject to multiple airport management simulations conducted by the German Aerospace Center [17,18]. Therefore, knowledge about the operational procedures is available.…”

Section: Scenario Selection and Analysismentioning

confidence: 99%

Looking into the Crystal Ball—How Automated Fast-Time Simulation Can Support Probabilistic Airport Management Decisions

2022

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Airport management plays a key role in the air traffic system. Introducing resources at the right time can minimize the effects of disruptions, reduce delays, and save costs as well as optimize the carbon footprint of the airport. Efficient decision-making is a challenge due to the uncertainty of the upcoming events and the results of the applied countermeasures. So-called ‘what-if’ systems are under research to support the decision-makers. These systems consist of a user interface, a case management system, and a prediction engine. Within this paper, we evaluate different types of prediction engines (flow, event, and motion models) that can be used for airport management what-if systems by comparing them in terms of accuracy and calculation speed. Hence, two different operational situations are examined to evaluate the performance of the prediction engines. The comparison shows that accuracy and calculation speed are opposed. The flow model has the lowest accuracy but the shortest calculation time and the motion model has the highest accuracy but the longest calculation time. The event model lies between the other two models. The acceptable accuracy of a prediction tool is strongly dependent on the respective airport, whereas the calculation time is strongly dependent on the available decision time. Regarding airport management, this means that the selection of a prediction engine has to be made in dependence of the airport and the decision processes. The results show the advantages and disadvantages of each prediction engine and provide a first quantification by which a selection for what-if systems can happen.

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“…It can greatly meet the requirements of passengers, airports, airlines and relevant units of flight operation. At the same time, scientific and efficient flight plan adjustment cannot be achieved without coordinated decision-making by airlines, air traffic control, airports and other parties [4]. In the absence of coordinated decision-making, information exchange is not timely, and participants may make contradictory decisions due to incomplete or different information.…”

Section: Introductionmentioning

confidence: 99%

Research and design of flight plan adjustment system based on cooperative decision mechanism

Li¹,

Liu²,

Shen³

et al. 2022

International Conference on Mechanisms and Robotics (ICMAR 2022)

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Recently, with the continuous improvement of living standards and the rapid development of civil aviation industry, more and more people choose convenient and efficient aircraft as a means of travel, and the number of flights increases rapidly. However, in the process of flight operation, it is inevitable to encounter complicated weather, other airspace user activities or air resource flow restrictions, which seriously affect the flight normality and passenger satisfaction. In order to solve such problems, people also put forward higher requirements for flight time resource management. In this paper, based on the collaborative decision-making mechanism, this paper carries out flight plan adjustment through the early predictions, assessment analysis, dynamic update and so on, implementation of passengers, airlines and flights running related units and efficient coordination, make the flight security requirements and Air traffic control, integrated airport security ability to achieve the optimal matching, to ensure flight safety, stable, orderly, and maintain flight release order, Improve the normal rate of flight clearance.

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Dealing with Adverse Weather Conditions by Enhanced Collaborative Decision Making in a TAM APOC

Cited by 3 publications

References 6 publications

Metrics to Evaluate Multi-Stakeholder Airport Control Center Decision-Making Processes - a Critical Discussion

Metrics to Evaluate Multi-Stakeholder Airport Control Center Decision-Making Processes - a Critical Discussion

Looking into the Crystal Ball—How Automated Fast-Time Simulation Can Support Probabilistic Airport Management Decisions

Research and design of flight plan adjustment system based on cooperative decision mechanism

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