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Abstract
Law Enforcement Officers (LEOs) experience high levels of workload and stress while on duty. LEO cognitive state varies under different driving conditions, such as patrol, pursuit, and emergency driving. In-vehicle interfaces further increase LEO workload, as LEOs need to process information from the mobile computer terminal and radio, creating a need for adapting information intake under high workload. To address this need, this study introduces a system designed for real-time adaptation of in-vehicle technology for LEOs based on their cognitive state. The system leverages real-time data to track and manage the workload dynamically. Gaze behavior analysis is utilized to determine attention allocation during various driving scenarios. Sensory outputs are monitored to assess physiological measures of workload. Additionally, vehicle dynamics data provide insights into driving behavior under different driving conditions. Based on the live processing of these variables, the system adjusts the in-vehicle interface and information delivery based on the LEO's cognitive state. The system is intended to optimize the interaction between the officer and in-vehicle technology, resulting in better performance and optimizing workload levels. The proposed system could offer a novel approach to integrate context-aware technology into police vehicles. This approach aims to contribute to the field of live information processing and human-system interaction, and more broadly contributes to the advancement of adaptive technologies in high-stress professional environments.
Keywords
Adaptive system, workload, driver performance, law enforcement.
1. Introduction
Law Enforcement Officers (LEOs) must contend with several tasks requiring in-vehicle technology while driving, from cell phones and dispatch radios to interaction with the mobile computer terminal (MCT). This multitasking increases cognitive workload and the risk of motor vehicle crashes (MVCs), representing one of the leading causes of line-of-duty deaths for LEOs (National Law Enforcement Memorial Fund, 2021).
LEOs face distinct challenges in their work due to the use of in-vehicle technologies. Research has indicated that the MCT and radio are among the most important and frequently used in-vehicle technologies for LEOs AR. These technologies, while essential, significantly increase the risk of distraction and cognitive overload. This effect is more pronounced in novice LEOs (nLEOs), who possess less experience to handle multitasking and the use of these technologies (Park, Wozniak, & Zahabi, 2024). To address these challenges, our research team sought to develop adaptive technology...