A Conceptual Analysis of Cognitive Distraction for Transit Bus Drivers

Abstract

The growing transit bus ridership nationally coupled with proliferation of advanced in-vehicle technologies is causing more distractions for the drivers. For transit vehicles, some distractions are caused by factors beyond the driver’s control such as operating equipment or attending to passengers. Earlier distraction studies have predominately explored the visual and physical distractions that prevented drivers from fully concentrating on the road. Though visual and physical distractions are a major cause for automobile accidents, driver inattention is thought to be responsible for many automobile accidents as well, but is not documented as such because of a lack in capability to collect relevant data. Driver distraction data from an earlier study at a regional transit agency revealed that cognitive distraction was perceived by the drivers as the highest form of distraction. This could be due to multitasking of driving and secondary tasks not directly related to driving such as passengers talking to driver, passengers talking on mobile phones, listening to broadcast messages etc. The driver’s cognitive state is important because though a person may be in the physical and visual state to drive efficiently; if their mind is inattentive that puts the driver and passengers at risk of an accident. The reason that this area has yet to be properly researched is not because the importance of one’s cognitive state while driving is questioned, but because identifying a way to properly obtain and analyze the data appears to be difficult. Most legislation focuses on visual and physical distraction such as handheld phones. Some states permit use of hand-free cell phone use while driving, ignoring the fact that cognitive distraction can still occur. The purpose of this concept paper is to analyze cognitive distraction data to determine its impact on transit bus drivers’ capability. Much of the theory and results applied in this paper are from the work of researchers working on similar projects. In order to understand cognitive distraction and how it can be mitigated, a Cognitive Distraction Model is outlined. The model was analyzed to evaluate the correlation between driver capability, and demographics and driving patterns. A model that provides an understanding about cognitive workload and driver capability could provide better psychological solutions to mitigate the number of accidents due to cognitive distraction. One might also be able to properly document other causes of automobile accidents (i.e. physical, visual, or cognitive), and inform drivers on the best cognitive state to embody in order to lessen the probability of having a vehicle accident. As more information is gained, this research could be expanded to better equip drivers in defensive driving and help regulators to formulate effective policies on driver distraction. Also, through additional research from the neurological and behavioral sciences, regulators could develop a better understanding of the causal factors and ways to prevent cognitive distraction.