Computing the effects of operator attention allocation in human control of multiple robots

Published

Journal Article

In time-critical systems in which a human operator supervises multiple semiautomated tasks, failure of the operator to focus attention on high-priority tasks in a timely manner can lower the effectiveness of the system and potentially result in catastrophic consequences. These systems must integrate computer-based technologies that help the human operator place attention on the right tasks at the right times to be successful. One way to assist the operator in this process is to compute where the operator's attention should be focused and then use this computation to influence the operator's behavior. In this paper, we analyze the ability of a particular modeling method to make such computations for effective attention allocation in humanmultiple-robot systems. Our results demonstrate that it is not sufficient to simply compute and dictate how operators should allocate their attention. Rather, in stochastic domains, where small changes in either the endogenous or exogenous environment can dramatically affect model fidelity, model predictions should guide rather than dictate operator attentional resources so that operators can effectively exercise their judgment and experience. © 2006 IEEE.

Full Text

Duke Authors

Cited Authors

  • Crandall, JW; Cummings, ML; Della Penna, M; De Jong, PMA

Published Date

  • May 1, 2011

Published In

Volume / Issue

  • 41 / 3

Start / End Page

  • 385 - 397

International Standard Serial Number (ISSN)

  • 1083-4427

Digital Object Identifier (DOI)

  • 10.1109/TSMCA.2010.2084082

Citation Source

  • Scopus