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Evaluating the impact of sensor data uncertainty and maneuver uncertainty in a conflict probe

机译：在冲突探测器中评估传感器数据不确定性和操纵不确定性的影响

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A conflict probe estimates the future separation with other traffic, both for the current state of ownship and variations to this state, using assumptions on how traffic will maneuver. The separation margin between ownship and traffic used in the separation requirements accounts for i) sufficient spatial and temporal margin to restore separation in case it is lost and ii) uncertainty in the current and future position data. Uncertainty in the traffic state data can be attributed to sensor inaccuracies, datalink latency, limitations of the extrapolation models and pilot / automation actions that can not be taken into account in the extrapolation models. The goal of the research described in this paper is to use a priori and on-line sensor performance characteristics and knowledge regarding potential maneuvers of the other traffic to specify conflict probe and conflict resolution system parameters. As part of the approach to achieve this, a sensor simulation tool has been integrated with an experimental and configurable conflict probing implementation. This paper discusses the effects of uncertainty in traffic state data on conflict probing and the corresponding evasive maneuver strategy, based on simulation results for different sensor and probe settings and conflict geometries. Additionally, a demonstrator graphical user interface concept to provide information about the uncertainty and an integrated simulation setup are discussed.
机译：冲突调查会根据流量的调度方式，估算当前所有权状态和该状态的变化情况，以此来估计将来与其他流量的分离。分离要求中使用的所有权和交通之间的分离裕度说明了i）足够的空间和时间裕度，可以在丢失时恢复分离，以及ii）当前和未来位置数据的不确定性。交通状态数据的不确定性可归因于传感器的不准确性，数据链路等待时间，外推模型的限制以及无法在外推模型中考虑的飞行员/自动化操作。本文所述研究的目标是利用先验和在线传感器性能特征以及有关其他流量的潜在操作的知识来指定冲突探测和冲突解决系统参数。作为实现此目标的方法的一部分，已将传感器仿真工具与实验性和可配置的冲突探测实现集成在一起。本文基于不同传感器和探头设置以及冲突几何形状的仿真结果，讨论了交通状态数据中不确定性对冲突探测的影响以及相应的规避策略。此外，还讨论了演示器图形用户界面概念，以提供有关不确定性的信息以及集成的仿真设置。

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