科技报告详细信息
Operator Trust Function for Predicted Drone Arrival
Trujillo, Anna C
关键词: AUTONOMY;    DRONE VEHICLES;    LININGS;    REGRESSION ANALYSIS;    MATHEMATICAL MODELS;    PILOTLESS AIRCRAFT;    RATINGS;    PREDICTIONS;   
RP-ID  :  NF1676L-28528
学科分类:航空航天科学
美国|英语
来源: NASA Technical Reports Server
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【 摘 要 】

To realize the full benefit from autonomy, systems will have to react to unknown events and uncertain dynamic environments. The resulting number of behaviors is essentially infinite; thus, the system is effectively non-deterministic but an operator needs to understand and trust the actions of the autonomous vehicles. This research began to tackle non-deterministic systems and trust by beginning to develop a user trust function based on intent information displayed and the prescribed bounds on allowable behaviors/actions of the non-deterministic system. Linear regression shows promise on being able to predict a person’s confidence of the machine’s prediction. Linear regression techniques indicated that subject characteristics, scenario difficulty, the experience with the system, and confidence earlier in the scenario account for approximately 60% of the variation in confidence ratings. This paper details the specifics of the liner regression model – essentially a trust function – for predicting a person’s confidence.

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