Representing Autonomous Systems’ Self-Confidence through Competency Boundaries:
作者： Andrew R. Hutchins , M. L. Cummings , Mark Draper , Thomas Hughes
关键词:
摘要: Abstract : A method for determining the self-confidence of autonomous systems is proposed to assist operators in understanding state unmanned vehicles under control. sensing-optimization/verification-action (SOVA) model, similar perception-cognition-action human informational processing has been developed illustrate how interact with their environment and areas uncertainty affect system performance. LIDAR GPS were examined scenarios where sensed surroundings could be inaccurate, while discrete probabilistic algorithms surveyed situations that result path planning uncertainty. Likert scales represent sensor algorithm uncertainties, these laid foundation Trust Annunciator Panel (TAP) consisting a series level indicators (ULIs). The TAP emphasizes critical role judgment oversight, especially when operate clustered or dynamic environments.
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