Affiliation:
1. University of Michigan, Ann Arbor, Michigan
Abstract
This paper describes a paradigm for human/automation control sharing in which the automation acts through a motor coupled to a machine's manual control interface. The manual interface becomes a haptic display, continually informing the human about automation actions. While monitoring by feel, users may choose either to conform to the automation or override it and express their own control intentions. This paper's objective is to demonstrate that adding automation through haptic display can be used not only to improve performance on a primary task but also to reduce perceptual demands or free attention for a secondary task. Results are presented from three experiments in which 11 participants completed a lane-following task using a motorized steering wheel on a fixed-base driving simulator. The automation behaved like a copilot, assisting with lane following by applying torques to the steering wheel. Results indicate that haptic assist improves lane following by least 30%, p < .0001, while reducing visual demand by 29%, p < .0001, or improving reaction time in a secondary tone localization task by 18 ms, p = .0009. Potential applications of this research include the design of automation interfaces based on haptics that support human/automation control sharing better than traditional push-button automation interfaces.
Subject
Behavioral Neuroscience,Applied Psychology,Human Factors and Ergonomics
Cited by
143 articles.
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