计算机科学
空中交通管制
杠杆(统计)
碰撞
国家空域系统
终端(电信)
数据挖掘
工程类
计算机安全
机器学习
计算机网络
航空航天工程
作者
Ashim Kumar Thapa,John Shortle,Lance Sherry
标识
DOI:10.1109/icns58246.2023.10124323
摘要
Collision Risk Models (CRM) are used by regulatory safety agencies to determine the safe separation minima and monitor the air-to-air collision risk level of an airspace. CRMs estimate the expected number of aircraft collisions and "total" risk for a given Air Traffic concept-of-operation (e.g. parallel approaches). The fidelity of the models, and assumptions used in the models, are determined by the required confidence interval required for the safety analysis, the capabilities of current analytical and simulation methods, availability of empirical data sets, and the capabilities of computational resources.This paper provides an overview of the state-of-the-art for CRMs for Terminal Area operations. Opportunities to apply recently developed AI/ML, and data analytics methods such as analytical and rare-event simulation methods, availability of empirical data sets, and leverage available computational resources are identified.
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