Version 1
: Received: 1 May 2024 / Approved: 2 May 2024 / Online: 2 May 2024 (09:34:20 CEST)
How to cite:
Raza, M.; Muslam, M. M. A.; Murtaza, M.; Cheng, C.-T.; Albahlal, B. M. Driving through the Mind: Investigating Driver Cognitive Impairment with Physiological Measures of Mental Workload. Preprints2024, 2024050116. https://doi.org/10.20944/preprints202405.0116.v1
Raza, M.; Muslam, M. M. A.; Murtaza, M.; Cheng, C.-T.; Albahlal, B. M. Driving through the Mind: Investigating Driver Cognitive Impairment with Physiological Measures of Mental Workload. Preprints 2024, 2024050116. https://doi.org/10.20944/preprints202405.0116.v1
Raza, M.; Muslam, M. M. A.; Murtaza, M.; Cheng, C.-T.; Albahlal, B. M. Driving through the Mind: Investigating Driver Cognitive Impairment with Physiological Measures of Mental Workload. Preprints2024, 2024050116. https://doi.org/10.20944/preprints202405.0116.v1
APA Style
Raza, M., Muslam, M. M. A., Murtaza, M., Cheng, C. T., & Albahlal, B. M. (2024). Driving through the Mind: Investigating Driver Cognitive Impairment with Physiological Measures of Mental Workload. Preprints. https://doi.org/10.20944/preprints202405.0116.v1
Chicago/Turabian Style
Raza, M., Chi-Tsun Cheng and Bader M Albahlal. 2024 "Driving through the Mind: Investigating Driver Cognitive Impairment with Physiological Measures of Mental Workload" Preprints. https://doi.org/10.20944/preprints202405.0116.v1
Abstract
The intricate interplay between driver cognitive dysfunction, mental workload (MWL), and heart rate variability (HRV) provides a captivating avenue for investigation within the domain of transportation safety studies. This article presents a comprehensive review and examines cognitive hindrance stemming from mental workload and heart rate variability. It scrutinizes the mental workload experienced by drivers by leveraging data gleaned from prior studies that employed heart rate monitoring systems and eye tracking technology, thereby illuminating the correlation between cognitive impairment, mental workload, and physiological indicators such as heart rate and ocular movements. The investigation is grounded in the premise that the mental workload of drivers can be assessed through physiological cues, such as heart rate and eye movements. The study discovered that heart rate variability (HRV) and infrared (IR) measurements played a crucial role in evaluating fatigue and workload for skilled drivers. However, the study overlooked potential factors contributing to cognitive impairment in drivers and could benefit from incorporating alternative indicators of cognitive workload for deeper insights. Furthermore, investigated driving simulators demonstrated that an eco-safe driving Human-Machine Interface (HMI) significantly promoted safe driving behaviors without imposing excessive mental and visual workload on drivers. Recommendations were made for future studies to consider additional indicators of cognitive workload, such as subjective assessments or task performance metrics, for a more comprehensive understanding.
Keywords
mental workload (MWL); heart rate variability (HRV); take over request (TOR); society of automotive engineers (SAE); driver cognitive impairment; human machine interface (HMI); eye tracking; driver safety; technology development
Subject
Social Sciences, Transportation
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
