Literature DB >> 16435690

Mission control of multiple unmanned aerial vehicles: a workload analysis.

Stephen R Dixon1, Christopher D Wickens, Dervon Chang.   

Abstract

With unmanned aerial vehicles (UAVs), 36 licensed pilots flew both single-UAV and dual-UAV simulated military missions. Pilots were required to navigate each UAV through a series of mission legs in one of the following three conditions: a baseline condition, an auditory autoalert condition, and an autopilot condition. Pilots were responsible for (a) mission completion, (b) target search, and (c) systems monitoring. Results revealed that both the autoalert and the autopilot automation improved overall performance by reducing task interference and alleviating workload. The autoalert system benefited performance both in the automated task and mission completion task, whereas the autopilot system benefited performance in the automated task, the mission completion task, and the target search task. Practical implications for the study include the suggestion that reliable automation can help alleviate task interference and reduce workload, thereby allowing pilots to better handle concurrent tasks during single- and multiple-UAV flight control.

Entities:  

Mesh:

Year:  2005        PMID: 16435690     DOI: 10.1518/001872005774860005

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  5 in total

1.  Understanding human management of automation errors.

Authors:  Sara E McBride; Wendy A Rogers; Arthur D Fisk
Journal:  Theor Issues Ergon Sci       Date:  2014

2.  Understanding the effect of workload on automation use for younger and older adults.

Authors:  Sara E McBride; Wendy A Rogers; Arthur D Fisk
Journal:  Hum Factors       Date:  2011-12       Impact factor: 2.888

3.  Unmanned aerial vehicles (drones) in out-of-hospital-cardiac-arrest.

Authors:  A Claesson; D Fredman; L Svensson; M Ringh; J Hollenberg; P Nordberg; M Rosenqvist; T Djarv; S Österberg; J Lennartsson; Y Ban
Journal:  Scand J Trauma Resusc Emerg Med       Date:  2016-10-12       Impact factor: 2.953

Review 4.  UAV IoT Framework Views and Challenges: Towards Protecting Drones as "Things".

Authors:  Thomas Lagkas; Vasileios Argyriou; Stamatia Bibi; Panagiotis Sarigiannidis
Journal:  Sensors (Basel)       Date:  2018-11-17       Impact factor: 3.576

5.  Supervised Classification of Operator Functional State Based on Physiological Data: Application to Drones Swarm Piloting.

Authors:  Alexandre Kostenko; Philippe Rauffet; Gilles Coppin
Journal:  Front Psychol       Date:  2022-01-06
  5 in total

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