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图像,语音和ADS-B轨迹数据集用于终端空域操作
Jay Patrikar1, Joao Dantas2, Brady Moon3
1Robotics Institute, Carnegie Mellon University, Pennsylvania, USA. patrikarjay@gmail.com.
Scientific data
|March 21, 2025
概括
TartanAviation是一个新的开源数据集,用于终端区域的空域操作,包含多模式数据,包括图像,语音和ADS-B轨迹. 该资源支持AI集成到空中交通管制和自动驾驶飞机的进步.
科学领域:
- 航空航天工程 航空航天工程
- 计算机科学 计算机科学
- 数据科学数据科学数据科学
背景情况:
- 空中交通管理依赖于各种数据流.
- 将人工智能集成到空中交通控制 (ATC) 中需要全面的数据集.
- 自主飞机的发展需要先进的操作数据.
研究的目的:
- 介绍TartanAviation,这是一个开源的,用于终端区域空域操作的多模式数据集.
- 使用同步的图像,语音和ADS-B轨迹数据提供机场环境的整体视图.
- 促进人工智能和机器学习集成到ATC系统和自主航空中.
主要方法:
- 从机场边界内部收集并发的图像,语音和ADS-B轨迹数据.
- 在多个月的时间里,收集了不同机场,季节,飞机类型和天气条件的数据.
- 提供原始和后处理数据,包括同步,过和插值版本.
主要成果:
- 数据集包括310万张图像,3374小时的空中交通控制语音和661天的ADS-B轨道数据.
- 包括用于数据收集和预处理的开源代码,增强可访问性.
- 提供多样化和同步的数据,对先进的航空研究至关重要.
结论:
- 塔尔坦航空是推动ATC和自动飞行AI发展的重要资源.
- 数据集的多模式性质和开源可用性加速了研究和开发.
- 能够在空域监控,安全和运营效率方面实现新型应用.
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