| 研究課題/領域番号 |
20K14855
|
|---|
| 研究種目 |
若手研究
|
| 配分区分 | 基金 |
|---|
| 審査区分 |
小区分22050:土木計画学および交通工学関連
|
|---|
| 研究機関 | 国立研究開発法人宇宙航空研究開発機構 |
|---|
研究代表者 |
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)
|
|---|
| 研究期間 (年度) |
2020-04-01 – 2025-03-31
|
| 研究課題ステータス |
交付 (2023年度)
|
| 配分額 *注記 |
3,900千円 (直接経費: 3,000千円、間接経費: 900千円)
2022年度: 780千円 (直接経費: 600千円、間接経費: 180千円)
2021年度: 1,300千円 (直接経費: 1,000千円、間接経費: 300千円)
2020年度: 1,820千円 (直接経費: 1,400千円、間接経費: 420千円)
|
|---|
| キーワード | 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 |
|---|
| 研究開始時の研究の概要 |
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.
|
| 研究実績の概要 |
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.
|
| 現在までの達成度 (区分) |
現在までの達成度 (区分)
3: やや遅れている
理由
Other work obligations delayed the progress of the current research.
|
| 今後の研究の推進方策 |
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.
|
