To improve the driving performance of vehicles, it is of great significance to study the
changes in the driver's brain cognition during driving and to establish an intelligent driving …

In this study, we propose an electrophysiological analysis-based brain network method for
the augmented recognition of different types of distractions during driving. Driver …

Introduction: Traffic congestion is closely related to traffic accidents, as prolonged traffic
congestion often results in frustration and aggressive behavior. Moreover, in daily …

Driving stress is a critical factor leading to road traffic accidents. Despite numerous studies
that have been conducted on driving stress recognition, most of them only focus on accuracy …

The ability to recognize different driving styles of surrounding vehicles is crucial to determine
the safest and most efficient driving decisions, prevent accidents, and analyze the causes of …

Accurately analyzing drivers' driving styles is crucial for road safety and enhancing
intelligent driving systems. However, existing studies have not fully explored the hidden …

Electroencephalogram (EEG) research in driving behavior is integral to develo** and
implementing brain–machine collaborative intelligent driving assistance systems. However …

Introduction Multitasking during flights leads to a high mental workload, which is detrimental
for maintaining task performance. Electroencephalography (EEG) power spectral analysis …

Traffic congestion can lead to negative driving emotions, significantly increasing the
likelihood of traffic accidents. Reducing negative driving emotions as a means to mitigate …

Computational intelligence is used to create artificially intelligent systems with the ability to
learn, adapt, and solve problems. Learners' computational abilities can be improved with the …