Lidé na fakultě
Ing. Jiří Volt

2024, New Trends in Civil Aviation: Proceedings of the 24th International Conference on New Trends in Civil Aviation 2024, Praha, České vysoké učení technické v Praze), p. 287-293), ISBN 978-80-01-07181-6, ISSN 2694-7854

Air Traffic Control is a key element of Air Traffic Management that ensures safe and efficient operations in airspace and airports. This paper presents a study on the development and implementation of Air Traffic Control logic in an airport airside simulation model. This research focuses on the identification and resolution of potential aircraft conflicts within the airport movement area and uses an agent-based modelling approach to address these challenges. The agent-based approach facilitates the modelling of complex interactions between different entities, allowing for a detailed investigation of airport traffic dynamics and potential improvements. The study includes the identifi-cation of conflict areas in airport infrastructure, the creation of a fictional airport movement area, and the development and integration of control logic to resolve conflicts during simulation runs of the designed simulation scenarios. The results of the sim-ulations provide valuable insights into the impact of traffic volume, the use of bidirectional taxiway segments, and bay operations on the total time spent by aircraft in the infrastructure, the average number of clearances issued for particular aircraft, or the number of clearances required to traverse the created infrastructure.

Stať ve sborníku z prestižní konf.

2023, 2023 New Trends in Aviation Development (NTAD), Praha, IEEE Czechoslovakia Section), p. 89-94), ISBN 979-8-3503-7042-3, ISSN 2836-2756

In this paper we investigate opportunities to enhance the existing operational procedures of airbridge operators. Prior to exploring potential improvements, a simulation model of the Prague Airport north apron infrastructure is developed using AnyLogic simulation software. The primary focus of optimization revolves around human resource allocation. The optimization of airbridge operator processes is achieved through various configurations of the developed simulation model. Comparative analysis with the current operational framework is conducted, followed by a thorough evaluation of the results. Furthermore, recommendations are provided on how to implement such processes in practice to ensure that airbridge operators and necessary equipment are always available in sufficient quantities, thereby achieving the desired quality of aircraft handling. Versatility of the model also allows for future improvement and its application to optimize the configuration of aircraft ground handling processes.

Stať ve sborníku z prestižní konf. (Scopus)

2023, Transportation Research Procedia - INAIR 2023, Linz, Elsevier BV), p. 68-76), ISSN 2352-1465

The subject of this paper is to summarize current research in the area of aircraft departure delay prediction based on machine learning algorithms and to confirm the relevancy of the identified variables (factors) whose implementation into predictive models could improve their accuracy and thus the ability to accurately predict the Target Off Block Time (TOBT) at Collaborative Decision Making (CDM) airport. In order to predict delays, several prediction models have been developed. One of the large categories of mathematical models are machine learning methods. The article includes a comprehensive literature review focused on machine learning algorithms confirming that none of those approaches used data from aircraft ground handling to predict aircraft departure delays, mainly due to ground handling data availability and scope of the research. The paper describes variables that could extend the existing machine learning prediction models. This research is supported with the real operational data from Václav Havel Airport Prague. The case study at Prague airport verifies a correlation of proposed variables with TOBT time. In several cases, a strong correlation between the proposed variables and TOBT was confirmed.

Stať ve sborníku z prestižní konf. (Scopus)

2022, Transportation Research Procedia, Amsterdam, Elsevier B.V.), p. 246-255), ISSN 2352-1457

The subject of this paper is a development of the mathematical model for determining the number of airport equipment dedicated for the baggage loading and unloading. This model can predict the demand for the carts and loaders based on the input data. Based on this prediction, the optimal number of equipment is calculated. The ability to predict the required amount of the airport vehicles in advance could make the aircraft loading and unloading process more efficient. It would also allow better capacity planning of the ground handling system. In the first part, the current state and procedures for baggage loading and unloading are analysed. Based on the theory of linear programming, a mathematical model is created to predict a demand for equipment and calculate the optimal number needed to handle all flights. This model is subsequently implemented in the created software, which allows to perform experiments with the proposed mathematical model. Operation data from Václav Havel Airport Prague are used to verify the correct functioning of the model.

Stať ve sborníku z prestižní konf. (Scopus)