Driver behavior is receiving increasing attention because of the staggering number of road
accidents. Many road safety reports regard human behavior as the most important factor in …

Driving Behavior (DB) is a complex concept describing how the driver operates the vehicle
in the context of the driving scene and surrounding environment. Recently, DB assessment …

Driver workload inference is significant for the design of intelligent human–machine
cooperative driving schemes since it allows the systems to alert drivers before potentially …

Abstract To apply Artificial Intelligence (AI), Machine Learning (ML) and Machine Reasoning
(MR) in health informatics are often challenging as they comprise with multivariate …

Driver workload (DWL) is an important factor that needs to be considered in the study of
traffic safety. The research focus on DWL has undergone certain shifts with the rapid …

The concept of vehicle automation ceases to seem futuristic with the current advancement of
the automotive industry. With the introduction of conditional automated vehicles, drivers are …

Analysis of physiological signals, electroencephalography more specifically, is considered a
very promising technique to obtain objective measures for mental workload evaluation …

Conditional Automated Driving (CAD) has attracted widespread attention due to the
substantial gap in achieving fully autonomous driving, wherein an essential endeavor …

One debatable issue in traffic safety research is that the cognitive load by secondary tasks
reduces primary task performance, ie, driving. In this paper, the study adopted a version of …

The goals of this study are the suggestion of a better classification method for detecting
stressed states based on raw electrocardiogram (ECG) data and a method for training a …