In the past several years, there have been a number of driving assistance systems that have been programmed and introduced. This is with the goal of ensuring drivers’ safety and reducing their workload. Some examples of these systems are the ACC or the Adaptive Cruise Control where it is keeping a safe distance from the vehicle ahead and the driver’s car. There is also the lane-keep assist system that keeps the car in its lane via steering support.

Preventing Accidents from Happening

On the other hand, while the workload from the driver is reduced, it partly reduces their attention as well which can eventually lead to unexpected car accidents. Because of this, it becomes necessary to assess the driver’s workload from an engineering as well as human physiology point-of-view.

It is important to clear out the relationship between the driver’s brain activity and workload which includes judgment and recognition. As a result, it becomes necessary to assess the attention of the driver and also, to clarify the connection between their brain activity and their performance. In fact, one of the ways how this is done by requesting the driver to undergo in which it checks how the driver thinks and reacts to various road conditions.

Road Safety and Science

There’s a small number of studies focusing on neuroimaging that uses a driving simulator program to be able to examine brain activity while driving. In such studies, a functional MRI is put into used. On the other hand, fMRI has its shortcomings in assessing driver performance as it needs the subject to lie in a narrow cylinder throughout the study and doesn’t allow enough movement, especially the head. This could make the situation makes the task unnatural and unrealistic.

There is also NIRS that is used or Near-Infrared Spectroscopy that gained attention. Such noninvasive technique is using near-infrared light to be able to evaluate the decrease or increase in oxygenated or deoxygenated hemoglobin in tissues.

It is also capable of detecting hemodynamic of the brain in real-time while the subject is in motion. As a result, brain activity could be measured in different settings.