Modeling novice law enforcement officers’ interaction with in-vehicle technology

Abstract

Cognitive performance models have been used in several human factors domains such as driving and human-computer interaction. However, most models are limited to expert performance with rough adjustments to consider novices despite prior studies suggesting novices' cognitive, perceptual, and motor behaviors are different from experts. The objective of this study was to develop a cognitive performance model for novice law enforcement officers (N-CPM) to model their performance and memory load while interacting with in-vehicle technology. The model was validated based on a ride-along study with 10 novice law enforcement officers (nLEOs). The findings suggested that there were no significant differences between the N-CPM and observation data in most cases, while the results of the benchmark model were different from that of N-CPM. The model can be applied to improve future nLEO's patrol mission performance through redesigning in-vehicle technologies and training methods to reduce their workload and driving distraction.