Background: Much of the driver distraction and inattention work to date has focused on concerns over drivers removing their eyes from the forward roadway to perform non-driving-related tasks, and its demonstrable link to safety consequences when these glances are timed at inopportune moments. This extensive literature has established, through the analyses of glance from naturalistic datasets, a clear relationship between eyes-off-road, lead vehicle closing kinematics, and near-crash/crash involvement.
Objective: This paper looks at the role of driver expectation in influencing drivers' decisions about when and for how long to remove their eyes from the forward roadway in an analysis that consider the combined role of on- and off-road glances.
Objective: The objective was to examine naturalistic usage of infotainment systems to assess use characteristics and patterns.
Background: Infotainment systems continue to evolve in terms of their capabilities and information availability, raising concerns about their distraction potential. Assessing potential distraction requires understanding how challenging different tasks are and how frequently they occur during driving.
A variety of methodologies for understanding the prevalence of distracted driving, its risk, and other aspects of driver secondary activity, have been used in the last 15 years. Although the current trend is toward naturalistic driving studies, each methodology contributes certain elements to a better understanding that could emerge from a convergence of these efforts. However, if differing methods are to contribute to a common and robust understanding of driver distraction, it is critical to understand the strengths and limitations of each method.
View Article and Find Full Text PDFObjective: The aim of this study was to assess how scrolling through playlists on an MP3 player or its aftermarket controller affects driving performance and to examine how drivers adapt device use to driving demands.
Background: Drivers use increasingly complex infotainment devices that can undermine driving performance. The goal activation hypothesis suggests that drivers might fail to compensate for these demands, particularly with long tasks and large search set sizes.