Is more information better? How dismounted soldiers use video feed from unmanned vehicles: Attention allocation and information extraction considerations

Research output: Contribution to journalArticlepeer-review

Abstract

Operational tactics in urban areas are often aided by information from unmanned aerial vehicles (UAVs). A major challenge for dismounted soldiers, particularly in urban environments, is to understand the conflict area in general and particularly from the UAV feed. The UAV feed is usually used to enhance soldiers' situation awareness abilities but less for identifying specific elements. A possible way to further enhance soldiers' abilities is to provide them with multiple sources of information (e.g., aerial and ground views). This study examined the benefits of presenting video feed from UAVs and unmanned ground vehicles (UGVs) in a combined interface, relative to presenting aerial feed alone. Thirty former infantry soldiers with no experience in operating unmanned vehicles participated. Objective performance, subjective evaluations, and eyetracking patterns were examined in two scenarios. In Scenario 1, performance scores in both identification and orientation tasks were superior in the combined configuration. In Scenario 2, performance scores in the identification tasks were improved, and the addition of the UGV feed did not harm performance in the orientation task. Eye movement scanning patterns reinforced that both UAV and UGV feeds were used for the mission. The combined configuration generated consistent benefits with regard to the identification tasks, perceived mental demand, and reduction of false reports without having any apparent cost on participants. Ground views may provide additional support to dismounted soldiers.

Original languageAmerican English
Pages (from-to)26-48
Number of pages23
JournalJournal of Cognitive Engineering and Decision Making
Volume7
Issue number1
DOIs
StatePublished - 1 Mar 2013

Keywords

  • Attention allocation
  • Dismounted soldiers
  • MOUT
  • Unmanned vehicles
  • Video feed

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics
  • Engineering (miscellaneous)
  • Applied Psychology
  • Computer Science Applications

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