PROBLEM The implementation of Graduated Driver Licensing (GDL) programs has significantly improved the crash and fatality rates of novice teen drivers, but these rates remain unacceptably high. METHOD A review of adolescent development research was undertaken to identify potential areas of improvement. RESULTS Research support for GDL was found to be strong, particularly regarding early acq...

This paper describes our first step for advances in humanmachine interactive systems for in-vehicle environments of the UTDrive project. UTDrive is part of an on-going international collaboration to collect and research rich multi-modal data recorded for modeling behavior while the driver is interacting with speech-activated systems or performing other secondary tasks. A simultaneous second goa...

We examined the utility and validity of intermittent video samples from black box devices for capturing individual difference variability in real-world driving performance in an ongoing study of obstructive sleep apnea (OSA) and community controls. Three types of video clips were coded for several dimensions of interest to driving research including safety, exposure, and driver state. The preli...

In a recent large-scale naturalistic study, driver-passenger interactions were identified as a major source of driver distraction. According to this study, driver inattention to the road is often caused by conversation with passengers. This suggests that when driving and conversing with passengers, drivers attempt to bridge the visual communication gap with passengers by turning to look at them...

Automotive collision warning systems (CWS) can enhance hazard identification and management. However, false alarms (FAs), which occur as a random activation of the system not corresponding to a threat and not interpretable by the driver, and unnecessary alarms (UAs), which occur in situations judged hazardous by the algorithm but not by the driver, may limit CWS effectiveness. A driving simulat...

In this paper, an end-to-end deep learning solution for driver distraction recognition is presented. In the proposed framework, the features from pre-trained convolutional neural networks VGG-19 are extracted. Despite the variation in illumination conditions, camera position, driver’s ethnicity, and genders in our dataset, our best fine-tuned model, VGG-19 has achieved the highest test accuracy...

Drivers operate in an increasingly complex visual environment, and yet there has been little recent research on the effects this might have on driving ability and accident rates. This paper is based on research carried out for the Scottish Executive’s Central Research Unit on the subject of external-to-vehicle driver distraction. A literature review/meta-analysis was carried out with a view to ...

with the introduction of the car radio, there have been concerns regarding how in-vehicle technology might undermine driving safety. Those concerns are particularly apparent today as many worry about the safety consequences of introducing vastly more complex technologies into the car, most prominently regarding the use of cell phones while driving. Developments in the areas of wireless communic...

This research adopted a model of goal activation to study the mechanisms underlying interrupted task performance. The effects of interruption timing, type of interruption, and age on task time and primary task resumption time were explored under conditions in which attention was switched back and forth between two tasks, much as when drivers shift attention between attending to the road and to ...

The crash risk associated with cell phone use while driving is a contentious issue. Many states are introducing Advanced Traveler Information Systems (ATIS) that may be accessed with cell phones while driving (e.g., 511 Traveler Information Services). In these contexts, there is a need for relevant research to determine the risk of cell phone use. This study compared driver performance while co...