“A naval officer misinterprets the radar signal of an upcoming aircraft, a programming error causes a nurse to enter the wrong command dispelling a lethal amount of radiation to their patient, the poor training of a nuclear plant power engineer  causes confusion when monitoring the cooling levels of the reactor. All these incidents preceded a catastrophe that could have been avoided had the proper design methodologies been implemented with proper consideration of the human operator. Accidents due to radar malfunction, aircraft failure, or the malfunctioning of hospital equipment are typically attributable to poor human operator performance or faulty system design. The Human factors discipline seeks to bridge the gap between innovative engineering and human performance. In addition to evaluating the performance of small scale systems and singular operators, human factors specialists assist with the design for large-scale systems, such as intelligent surface and air transportation control. My goal as a human factors specialist and researcher is to provide design considerations and training for systems that require careful coordination with a human operator. From complex critical systems that monitor health and transportation to simple systems such as improved packaging design of medical labels, the human factors specialists strive to improve the human condition by understanding the strengths and limitations of the operator. Additionally, novel research and modeling techniques are frequently being developed in our field, such as machine-learning technology and nonlinear dynamics, to better understand human performance in complex and adaptive systems. Neuroscience has also played an integral role in understanding the underlying physiological basis of the operator’s behavior and decision-making. While an operator conducts a complex task requiring mental workload, a human factors researcher can measure their status of executive functioning, memory capacity, and the visual system using electroencephalography (EEG), functional near infrared spectroscopy (fNIRs), and even functional magnetic resonance imaging (fMRI). Finding neurophsyioloigcal differences across different groups (age, sex, health) has  important implications for design considerations that take into account large populations of users with varying physical and mental abilities. This is especially important in the context of surface transportation (driving, boating), operating complex machinery (power plant, air traffic control), and military systems (unmanned aerial vehicles).”

 

Key References

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Barfield, W., & Dingus, T. A. (Eds.). (2014). Human factors in intelligent transportation systems. Psychology Press.

Chan, R. K. C., Lim, J. M. Y., & Parthiban, R. (2021). A neural network approach for traffic prediction and routing with missing data imputation for intelligent transportation system. Expert Systems with Applications, 171, 114573.

Cunningham, M., & Regan, M. A. (2015). Autonomous vehicles: human factors issues and future research. In Proceedings of the 2015 Australasian Road safety conference,14.

Karwowski, W. (2012). A review of human factors challenges of complex adaptive systems: discovering and understanding chaos in human performance. Human factors, 54(6), 983-995.

Linkov, V., Zámečník, P., Havlíčková, D., & Pai, C. W. (2019). Human factors in the cybersecurity of autonomous vehicles: Trends in current research. Frontiers in psychology, 10, 995.

Louie, J. F., & Mouloua, M. (2019). Predicting distracted driving: The role of individual differences in working memory. Applied ergonomics, 74, 154-161.

Mallam, S. C., Lundh, M., & MacKinnon, S. N. (2015). Integrating human factors & ergonomics in large-scale engineering projects: Investigating a practical approach for ship design. International Journal of Industrial Ergonomics, 50, 62-72.

Meshkati, N. (1991). Human factors in large-scale technological systems’ accidents: Three Mile Island, Bhopal, Chernobyl. Industrial Crisis Quarterly, 5(2), 133-154.

Mouloua, M., Ahern, A., Rinalducci, E., Alberti, P., Brill, J. C., & Quevedo, A. (2010, September). The effects of text messaging on driver distraction: A bio-behavioral analysis. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 54(19), 541-1545. 

Strang, A. J., Horwood, S., Best, C., Funke, G. J., Knott, B. A., & Russell, S. M. (2012). Examining temporal regularity in categorical team communication using sample entropy.