Separation provision and collision avoidance to avoid other air traffic are fundamental components of the layered conflict management system to ensure safe and efficient operations. Pilots have visual-based separation responsibilities to see and be seen to maintain separation between aircraft. To safely integrate into the airspace, drones should be required to have a minimum level of performance based on the safety achieved as baselined by crewed aircraft seen and be seen interactions. Drone interactions with crewed aircraft should not be more hazardous than interactions between traditional aviation aircraft. Accordingly, there is need for a methodology to design and evaluate detect and avoid systems, to be equipped by drones to mitigate the risk of a midair collision, where the methodology explicitly addresses, both semantically and mathematically, the appropriate operating rules associated with see and be seen. In response, we simulated how onboard pilots safely operate through see and be seen interactions using an updated visual acquisition model that was originally developed by J.W. Andrews decades ago. Monte Carlo simulations were representative two aircraft flying under visual flight rules and results were analyzed with respect to drone detect and avoid performance standards.

翻译：避免与其他空中交通相撞的间隔保持和防撞机制是分层冲突管理系统的基础组成部分，旨在确保安全高效运行。飞行员承担基于视觉的间隔责任，通过"看见"与"被看见"来维持飞机间的间隔。为确保安全融入空域，无人机应具备基于有人驾驶飞机"看见"与"被看见"交互所确立的安全基线的最低性能水平。无人机与有人驾驶飞机的交互不应比传统航空飞机间的交互更具危险性。因此，需要建立一套用于设计和评估无人机防撞系统的方法论，以降低空中相撞风险，该方法论需从语义和数学两个层面明确阐述与"看见"和"被看见"相关的适用运行规则。为此，我们采用J.W. Andrews数十年前提出的视觉获取模型更新版，模拟了机载飞行员如何通过"看见"与"被看见"交互实现安全运行。蒙特卡洛模拟基于两架飞机在目视飞行规则下的典型场景，并依据无人机探测与规避性能标准对结果进行了分析。