Probabilistic arrival time prediction algorithm using a-priori knowledge and machine learning to enable sustainable air traffic management

Research Project

Project/Area Number	24K07723
Research Category	Grant-in-Aid for Scientific Research (C)
Allocation Type	Multi-year Fund
Section	一般
Review Section	Basic Section 22050:Civil engineering plan and transportation engineering-related
Research Institution	Japan Aerospace EXploration Agency
Principal Investigator	アンドレエバ森アドリアナ国立研究開発法人宇宙航空研究開発機構, 航空技術部門, 主任研究開発員 (30747499)
Co-Investigator(Kenkyū-buntansha)	上野誠也国立研究開発法人宇宙航空研究開発機構, 航空技術部門, 主幹研究開発員 (60203460)
Project Period (FY)	2024-04-01 – 2027-03-31
Project Status	Granted (Fiscal Year 2024)
Budget Amount *help	¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000) Fiscal Year 2026: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000) Fiscal Year 2025: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000) Fiscal Year 2024: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Keywords	time of arrival / probabilistic prediction / departures
Outline of Research at the Start	This research combines flight modeling and data-centric algorithms to increase the prediction accuracy of arrival times by focusing on the departure flight phases, and provide a probabilistic estimate of how accurate the estimation is to traffic controllers so that they plan for optimal management.