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	+ Home Search Aviation Systems		Dr. Hanbong Lee and co-authors received the 2020 Best Paper in the Aviation Systems Division Award The 2020 Aviation Systems Division (Code AF) Best Paper Award was given to Dr. Hanbong Lee for his paper, “Fast-Time Simulation for Evaluating the Impact of Estimated Flight Ready Time Uncertainty on Surface Metering,” presented at the 38th Digital Avionics Systems Conference. Most airports today manage departures in the order they leave the gate. This overloads runways on busy days, causing increased delays and emissions. NASA, in collaboration with the Federal Aviation Administration, or FAA, and industry partners, has developed the Airspace Technology Demonstration 2, or ATD-2, project. Part of this project combines arrival, departure and airport surface traffic data into an integrated schedule that can be accessed by air traffic controllers in many locations simultaneously. This makes it easier to predict aircraft movement across multiple airports and reduces the number of delays experienced. Lee will present his work using fast-time simulations to investigate the impact of estimated flight ready time uncertainty on airport surface traffic management performance. Abstract: NASA has been developing and demonstrating new concepts and technologies for Integrated Arrival, Departure, and Surface (IADS) traffic management capabilities under the Airspace Technology Demonstration 2 (ATD-2) project. One of the IADS capabilities is surface metering enabled by a tactical surface scheduler to provide controllers with the pushback advisories for departures at gates. The tactical surface scheduler uses the estimated flight ready times provided by airlines, called Earliest Off-Block Times (EOBTs), as input to calculate the target off-block times for pushback advisories. However, the EOBTs are often inaccurate and deviate from the actual flight ready times, which may reduce the benefits of surface metering. In this study, a linear regression model is developed to model the EOBT uncertainty distribution over time based on actual EOBT data collected at Charlotte airport. This EOBT model is integrated with a tactical surface scheduler and a fast-time simulation tool. To evaluate the impact of the EOBT accuracy on airport surface operations, fast-time simulations are implemented for selected traffic scenarios under different levels of EOBT accuracy. Simulation results show that the EOBT uncertainty affects several performance metrics related to the surface metering, such as gate hold, taxi time reduction, and target takeoff time predictability, which in turn influences ATD-2's scheduler performance. Biography: Dr. Hanbong Lee is an Aerospace Engineer at NASA Ames Research Center, leading the Urban Air Mobility (UAM) Network Scheduler team in the ATM-X project. Before joining the UAM sub-project, he led the Systems Analysis team and performed various air traffic data analyses and fast-time simulations under the Airspace Technology Demonstration 2 (ATD-2) project for the integrated departure, arrival, and surface operations. He received his B.S. in Mechanical and Aerospace Engineering from Seoul National University, Korea and both M.S. and Ph.D. degrees in Aeronautics and Astronautics from Massachusetts Institute of Technology. His research interests include scheduling algorithms for efficient and safe operations of advanced air mobility and traditional air traffic, air traffic data analysis using machine learning algorithms, and applications of fast-time simulations to aviation industry. + Back to Top
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