Vladimir Kuran

Vladimir Kuran is responsible for the development and user role administration of several operational systems at Prague Airport. He got his master's degree at Czech Technical University at 2004 and since then has worked for an airline, bizjet operator and airport authority. He participates in various innovation activities (SESAR, EATIN). Kuran's effort was rewarded when Prague Airport won the 2023 digital transformation award announced by the joint initiative of ACI Europe and the SESAR joint undertaking.

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Machine learning automation of target off-block time

Airports utilizing collaborative decision-making (A-CDM) rely on accurate estimates of target off-block time (TOBT) set by airlines or ground handlers. This time indicates the end of ground handling, including possible ground delays, and should be updated whenever changes in the handling progress occur. Last-minute changes in TOBT can disrupt pre-departure sequence and air traffic flow management, making its timely and accurate estimate vital. As one of the EATIN (Eurocontrol Air Transport Innovation Network) initiatives, this work presents a machine learning model for TOBT predictions, their implementation into Prague Airport’s operating system and their distribution to stakeholders and the network manager.

The audience will learn:

• A machine learning model for turnaround and target off-block time predictions
• The validation steps and integration of machine learning into Prague Airport's operating system
• The approach used at Prague Airport to automatically distribute the model's outcome to stakeholders and the network manager
• An analysis showing the acceptance of the model's outcome by ground handlers at Prague Airport