An Integrated Cognitive Performance Evaluation Framework for Urban Search and Rescue Applications

Authors: Antonio D. Lee, Steven X. Jiang

Abstract:

A variety of techniques and methods are available to evaluate cognitive performance in Urban Search and Rescue (USAR) applications. However, traditional cognitive performance evaluation techniques typically incorporate either the conscious or systematic aspect, failing to take into consideration the subconscious or intuitive aspect. This leads to incomplete measures and produces ineffective designs. In order to fill the gaps in past research, this study developed a theoretical framework to facilitate the integration of situation awareness (SA) and intuitive pattern recognition (IPR) to enhance the cognitive performance representation in USAR applications. This framework provides guidance to integrate both SA and IPR in order to evaluate the cognitive performance of the USAR responders. The application of this framework will help improve the system design.

Keywords: Cognitive performance, intuitive pattern recognition, situation awareness, urban search and rescue.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1124123

References:

[1] R. Murphy, J. Kravitz, S. Stover, R. Shoureshi, “Mobile robots in mine rescue and recovery”, Robotics & Automation Magazine, IEEE 16(2): 91-103, 2009.
[2] G. Klein, “Naturalistic Decision Making”, Human Factors, 50(3), 456-460, 2008.
[3] Van Merriënboer, JJG, Clark, RE, de Crook, MBM, “Blueprints for complex learning: The 4C/ID-model”, Educational Technology Research and Development 50(2): 39-61, 2002.
[4] J. M. Schraagen, S. F. Chipman, V. L. Shalin, (2000). “Cognitive task analysis”, Lawrence Erlbaum.
[5] Hoffman, RR, Crandall, B., Shadbolt, NR. “Use of the critical decision method to elicit expert knowledge: A case study in the methodology of cognitive task analysis”, Human Factors: The Journal of the Human Factors and Ergonomics Society 40(2): 254-276, 1998.
[6] B., G. Crandall, G. Klein, R. R. Hoffman, (2006). “Working minds: A practitioner's guide to cognitive task analysis”, MIT Press.
[7] C. A. Bolstad, J. M. Riley, D. G. Jones, M.R. Endsley (2002). “Using goal directed task analysis with Army brigade officer teams”, SAGE Publications.
[8] Pirolli, P., and S. Card (2005). “The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis”, In Proceedings of International Conference on Intelligence Analysis. McLean, VA, USA, May, 2005.
[9] Diaper, D., and N. Stanton (2003). “The handbook of task analysis for human-computer interaction”, CRC.
[10] Stanton, N. (2005). “Human factors methods: A practical guide for engineering and design”, Ashgate Publishing.
[11] Kitano, H, Tadokoro, S, Noda, I, Matsubara, H, Takahsahi, T, Shinjou, A, and Shimada, S (1999). Robo cup rescue: Search and rescue in large-scale disasters as a domain for autonomous agents research. In IEEE: International Conference on Systems, Man, and Cybernetics, IEEE Press (Vol.6, pp.739-743), 1999. Tokyo, Japan.
[12] Johns, K, and Taylor T (2009). Professional Microsoft robotics developer studio, Wrox Press.
[13] Parkes, KR (1995). "The effects of objective workload on cognitive performance in a field setting: A two‐period cross‐over trial." Applied Cognitive Psychology 9(7): S153-S171.