| Project/Area Number |
20K14855
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 22050:Civil engineering plan and transportation engineering-related
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| Research Institution | Japan Aerospace EXploration Agency |
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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)
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| Project Period (FY) |
2020-04-01 – 2025-03-31
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| Project Status |
Granted (Fiscal Year 2023)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2022: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2021: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2020: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | cellular automata / air traffic / air traffic intervention / CARATS Open Data / air traffic flow / model / radar data / route mapping / merge / new entrants / mixed air traffic / supersonic transport / air traffic flow model |
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| Outline of Research at the Start |
This study will clarify the mechanism of congestions of heterogeneous air traffic flows and indicate traffic patterns to allow smooth integration of new entrants, in particular supersonic transport (SST). A novel heterogeneous air traffic flow model will be developed and used to identify optimal traffic patterns to minimize the impact on orthodox aircraft.
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| Outline of Annual Research Achievements |
Air traffic inefficiencies lead to excess fuel burn, emissions and air traffic controller (ATCo) workload. Various stakeholders have developed metrics to assess the operation performance. Most metrics compare the actual trajectories to some benchmark ones to calculate excess time or distance. This research is inspired by cellular automata (CA) and develops a combined time-distance lateral inefficiency and predictability metric using discrete space and time mapping on published flight routes. It focuses on Tokyo International Airport, and uses only track data and published routes, which makes it easily applicable to any other hub airport worldwide. The mapping and velocity analyses are used to investigate when and where ATCos are most likely to intervene to provide safe separation.
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| Current Status of Research Progress |
Current Status of Research Progress
3: Progress in research has been slightly delayed.
Reason
Other work obligations delayed the progress of the current research.
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| Strategy for Future Research Activity |
This research introduced how a discrete and spatial mapping inspired from cellular automata can be used to evaluate air traffic predictability and inefficiencies.
Future works include a more detailed investigation of a traffic metric adjustable to the stakeholder’s needs, for example focusing on either traffic predictability, key for trajectory-based operations, or flight efficiency.
The results from the research can be further expanded to investigate the correlation between adverse-weather, new entrants such as supersonic aircraft, and traffic inefficiencies.
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