Machine Learning for Dynamic Airspace Configuration towards Optimized Mobility in Emergency Situations
| 项目名称： | Machine Learning for Dynamic Airspace Configuration towards Optimized Mobility in Emergency Situations |
| 摘要： | Air traffic control (ATC) system is extremely complex so it is impossible to address every component under emergency operation. In this project, the research team narrows the research scope down to airspace configuration. Current national airspace configuration follows a static layout which cannot adapt to the dynamic air traffic conditions or incoming emergency events. Therefore, the team proposes to boost the current ATC system by developing a novel machine learning (ML)-based dynamic airspace configuration (DAC) framework. Different from the traditional statistical and graphical based DAC approaches, the proposed ML-based framework aims to discover the difference of DAC on areas with different air traffic pattern, so that a mapping between ATC control and the air traffic evaluation metrics can be found. The proposed framework will provide: a DAC model that is able to self-adjust the airspace configuration based on the air traffic demands of different time periods of the day or emergency events, thus providing increased airspace capacity, safety and efficiency of ATC operations under unexpected situations with rapid demand changes. |
| 状态： | Active |
| 资金： | 220580 |
| 资助组织： | Center for Advanced Transportation Mobility<==>Office of the Assistant Secretary for Research and Technology |
| 项目负责人： | Song, Houbing；Liu, Dahai |
| 执行机构： | Embry-Riddle Aeronautical University |
| 开始时间： | 20201001 |
| 预计完成日期： | 20220331 |
| 主题领域： | Aviation；Operations and Traffic Management；Planning and Forecasting；Security and Emergencies |
相关文献
- Simulation Study of Emergency Evacuation of Greater Jackson due to Hazardous Material Incident
- Combining Virtual Reality and Machine Learning for Intelligent Sustainable Traffic Management
- Combining Virtual Reality and Machine Learning for Enhancing the Resiliency of Transportation Infrastructure in Extreme Events
- Multi-scale and Collaborative Disaster Evacuation Planning Framework
- Incident and Emergency Situations Simulations
- Proactive Management of Mobility Impact of Interdependent Subsurface Utility and Roadway Construction through Incentives
检索历史
应用推荐
