# Physiological and Behavioral Changes of Passive Fatigue on Drivers during On-Road Driving
### Research Questions  
In summary, considering the different manifestations of driving under states of active fatigue versus passive fatigue, the more hazardous nature of the passive fatigue, and the expected more frequent passive fatigue in the coming autonomous vehicle age, the necessity and urgency to investigate passive fatigue is confirmed after the above literature review of practical needs and theoretical categorization of active versus passive fatigue.  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt}} \hline \hline \multicolumn{1}{c}{**Indicators**} & \multicolumn{1}{c}{**Comparisons between Active Fatigue versus Passive Fatigue**} \\ \hline Pupil diameter [15] & Decreased significantly in both conditions of active fatigue and 1 h passive fatigue driving, while no statistically significant change was reported after 90-min passive fatigue driving. \\ \hline Blink duration [15] & Only increased in active fatigue driving. \\ \hline Mean velocity of saccade [15] & Only increased in active fatigue driving. \\ \hline Saccade duration [15] & Increased in active fatigue driving and 1.5-h passive fatigue driving. \\ \hline Standard deviation of lane position (SDLP) [16] & Lower SDLP in passive fatigue driving. \\ \hline Response time (RT) [16] & Slower braking and steering RTs in the passive driving. \\ Collision [16] & More collisions in the passive fatigue driving. \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparisons of physiological and behavioral indicators for active fatigue versus passive fatigue.  
Figure 1: Attention allocation under passive fatigue.  
More specifically, the current study aims to address three important research questions: First, what are the changes of eye movement and driving performance during passive fatigue of drivers, especially in a real-world scenario? Second, does there exist any compensatory behavioral strategies to mitigate the risks of passive fatigue? Third, what are the representative indicators for the early versus late stage of fatigue? Answers to this question can inform the parameter selections for the development of a Driver Monitor System (DMS).  
To address the above-mentioned research questions, techniques of eye tracking and CAN-bus (measuring driving performance) are implemented. Eye tracking and driving performance have been proven to be highly correlated with fatigue [12] and are more feasible to apply in the real world with no direct body contact with drivers. Real-world driving is emphasized in the current study as previous passive fatigue studies were mostly conducted in driving simulators with highway or autonomous driving settings [16]. Extensive literature search in major databases, including ProQuest, Web of Sciences, etc., only generated a couple of papers on passive fatigue in a real-world scenario. There is only one recent initial attempt to study passive fatigue of drivers in a real-world scenario, signifying the necessity of real-world examination of driving performance. However, it emphasizes use of a motion seat [17], not a full scope examination of the core driving behaviors, that is, eye movement and vehicle manipulations. Personal communications with major recent authors (including Fellow and Dr. [PERSON] [4] and Dr. [PERSON] [18]) on this topic in the United States and China confirmed the lack of studies on passive fatigue in a real-world scenario. However, they confirmed and agreed the necessity to execute such research, although they reminded us the potential technical difficulty and financial costs. Therefore, to maximize the external validity, the current study was carried out in a real highway environment [6].