TECHNOLOGY AREA(S): Air Platform, Human Systems

ACQUISITION PROGRAM: PMA-205, Naval Aviation Training Systems

OBJECTIVE: Develop an innovative and adaptive training system, techniques and computer-based simulation trainer, for Unmanned Aerial Systems (UAS) operators to maintain attentiveness during long shiftwork associated with extended UAS missions.

DESCRIPTION: With the expanding use of UAS comes the increasing need for UAS operators to maintain attention for long periods of time during the missions. Shifts of up to 12 hours in length are not uncommon. Shiftwork is associated with higher fatigue levels, degraded task performance and higher error rates [1]. While existing UAS simulations aim to train operators (i.e., Air Vehicle Operators, Sensor Operators) on job-related skills, there are no systems currently that focus on attention. Investigations of larger group 4 and 5 UAS mishaps have indicated that issues with channelized attention contributed to the mishap(s) [2]. Channelized attention occurs when all of an individual’s cognitive resources are focused on one aspect of the environment, causing other equally important cues to be missed [2]. Intelligence, Surveillance, and Reconnaissance (ISR) type missions require sensor operators to track contacts of interest for extended periods in order to correctly identify and classify contacts of interest (COIs). Larger UAS are used for long surveillance type missions that require operator attention even if multiple crews are used. This research aims to develop tailored adaptive training techniques to minimize the issue of channelized attention. Training techniques capable of presenting long term mission requirements need to be developed, as no such technology currently exists.

Research on attentional training [3, 4] has indicated that it is possible to train attention and create effects that transfer to tasks after training. Further, a recent meta-analysis found that attentional training may be more effective if it is adaptive [4]. Adaptive training is broadly defined as any instruction that is tailored to an individual trainee’s strengths and weaknesses so that the training experience varies from one individual to another based on either task performance, aptitudes, or test scores. Training can be adapted based on attributes measured prior to training, or during training based on task performance or scores. Many aspects of training can be adapted such as feedback, task difficulty, instruction, etc. The goal of adaptive training solutions is to provide the effectiveness of one-on-one tutoring through computer-based training that does not require an instructor in the loop [5].

Cost-effective, computer-based simulation training solutions that are able to adapt to the learning characteristics of different individuals [5], to the affordances inherent in UAS (i.e., operators are segregated from aircraft), and to the specific details involved with different missions are sought. This effort will develop adaptive training techniques and a computer-based simulation trainer that apply specifically to the UAS domain to aid and improve attention during long mission requirements. Pre-training and post-training evaluations should be performed to measure improvement in attention of UAS operators.

PHASE I: Design, develop and demonstrate a proof of concept for adaptive training techniques and a computer based simulation trainer to improve operator attentiveness during long shift work. System should accommodate different UAS missions, individual operator characteristics and learning styles. Develop protocol for approval of the use of human subjects in a training effectiveness evaluation.

PHASE II: Finalize the adaptive training proof of concept with the candidate UAS mission requirements within the computer-based simulation. Develop individual test subject baselines. Then, post-training, perform an effectiveness evaluation to demonstrate the improved attention of UAS operators.

PHASE III DUAL USE APPLICATIONS: Finalize all aspects of the training. Perform testing and prepare any and all necessary documentation, such as user's guides and instructor's manuals. Integrate the training solution into a full UAS training environment and to applicable UAS platforms. Develop commercialization plan to transition to industry/relevant users. Private Sector Commercial Potential: Advances in this technology are applicable to the gaming community, and digital tutoring technologies. Methods and technologies developed under this effort could be used by industries which use simulation in place of live training (e.g., commercial aviation, nuclear power generation, emergency management, law enforcement) to ensure that their training systems are warding off attention-related decrements in performance of tasks. Additionally, organizations specializing in training effectiveness and workload assessment could employ the tools and techniques developed here to ensure consistent training outcomes and provide workload assessments for their clientele.

REFERENCES:

• Tvaryanas, A. P., Platte, W., Swigart, C., Colebank, J., & Miller, N. L. (2008). A resurvey of shift work-related fatigue in MQ-1 Predator unmanned aircraft system crewmembers
• Thompson, W. T., Tvaryanas, A. P., & Constable, S. H. (2005). U.S. military unmanned aerial vehicle mishaps: Assessment of the role of human factors using human factors analysis and classification system (HFACS) (Report No. HSW-PE-BR-TR-2005-0001). Brooks City-Base, TX: United States Air Force 311th Human Systems Wing
• Karbach, J. & Kray, J. (2009). How useful is executive control training? Age differences in near and far transfer of task-switching training. Developmental Science, 12, 978-990
• Peng, P. & Miller, A. C. (2016). Does attention training work? A selective meta-analysis to explore the effects of attention training and moderators. Learning and Individual Differences, 45, 77-87
• Landsberg, C. R., Astwood, R. S., Van Buskirk, W. L., Townsend, L. N., Steinhauser, N. B., Mercado, A. D. (2012). Review of adaptive training system techniques. Military Psychology, 24:2, 96-113
• McCarley, J. S., & Wickens, C. D. (2004). Human factors concerns in UAV flight. University of Illinois at Urbana-Champaign Institute of Aviation, Aviation Human Factors Division

KEYWORDS: UAS; Target Detection; Sustained attention; Adaptive training; Fatigue; Shift work

** TOPIC AUTHOR (TPOC) **

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