Masataka Adachi ¹ Sou Nobukawa ² Keiichiro Inagaki ^1*

• ¹ Science and Engineering, Chubu University, Kasugai, Aichi, Japan
• ² Chiba Institute of Technology, Narashino, Chiba, Japan

Fatigue is one of the crucial factors in human error-related traffic accidents. Despite the development of highly advanced intelligent transport systems, fatigue-related traffic accidents have not decreased. The factors inducing driver fatigue are classified into mental and physical categories. Physical fatigue results from muscle strain due to prolonged driving and operations. Mental fatigue, on the other hand, results from the continuous mental effort required for driving, including repeated perception and decision-making regarding driving situations and route planning. Monitoring driver fatigue can help prevent fatigue-related traffic accidents. Therefore, researchers have studied its relationship with various biomarkers such as sleep state, eye movement, facial expression, and electroencephalography (EEG) activation levels. Moreover, studies have revealed the relationship between fatigue and cognitive performance, which is affected by factors such as extended periods of driving. Furthermore, the strategy, quantity, and quality of driving operations and perception differ in various traffic environments. For instance, driving stress levels vary depending on factors such as the number of vehicles on the road, traffic congestion, and road conditions. However, the brain activity associated with mental and physical workload due to the traffic environment and its factors remains unknown. In particular, the relationship between mental and physical stress resulting from varying levels of operation and perception in different driving environments, the accumulation of driver fatigue caused by such stress, and the related brain activity are still unclear. In this study, we focused on investigating the mental and physical workload that accumulates in drivers and induces physical and mental fatigue, as well as the related brain activity caused by different traffic environments. We investigate these aspects through driving experiments, measuring EEG in driving environments created by varying the traffic environment and density using a driving simulator. The results confirmed differences in thetaand alpha-band spectral responses, which are associated with driver fatigue, across different traffic environments. Further examination of the causal relationship showed that mental and physical workload were associated with fatigue-related spectral responses depending on the traffic environment. These findings imply that the level of cognitive and operational load inherent in driving environments plays a crucial role in driver fatigue.