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Autonomous Capability Paper Authored by Team From Codes AF, TH, and TI Wins Code AF Best Paper Award
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Autonomous Capability Paper Authored by Team From Codes AF, TH, and TI Wins Code AF Best Paper Award

The paper titled, “Using an Automated Air Traffic Simulation Capability for a Parametric Study in Traffic Flow Management” won the Aviation Systems Division (Code AF) Best Paper Award for 2018. The paper describes experiments performed with an automated simulation capability to study the impact of varying levels of airline participation in the Collaborative Trajectory Options Program (CTOP) on strategic ground delay and flight time, and the impact of departure uncertainty on tactical Time-Based Flow Management (TBFM) system delays. Authors from three divisions came together on this paper: Heather Arneson (AF), Tony Evans (AF), Deepak Kulkarni (Decision Support Systems group, TI), Paul Lee (TH), Jinhua Li (AF), and Mei Yeuh Wei (Decision Support Systems group, TI). The award review process involved both the Code AF supervisors and the Ames Office of the Chief Scientist.

BACKGROUND: Integrated Demand Management (IDM) is a near- to mid-term NASA concept that proposes to address mismatches in air-traffic system demand and capacity by using the CTOP, a strategic flow management capability, to pre-condition demand into the more tactical TBFM system. Human-In-The-Loop (HITL) simulations have been conducted to develop and evaluate the IDM concept. While much can be learned from a HITL simulation, these are time consuming and expensive. In order to study a broader scope of parameters, a simulation capability has been developed automating both the human components and collaboration between operational systems.

NASA PROGRAM FUNDING: Air Traffic Management eXploration (ATM-X) project / Integrated Demand Management (IDM), Aeronautics Research Mission Directorate (ARMD)

COLLABORATORS: Heather Arneson (AF), Tony Evans (AF), Deepak Kulkarni (TI), Paul Lee (TH), Jinhua Li (AF), and Mei Yeuh Wei (TI)

POINT OF CONTACT: Deepak Kulkarni, deepak.kulkarni@nasa.gov

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