Reducing risky driving: Assessing the impacts of an automatically-assigned, targeted web-based instruction program.

Introduction: Transportation safety research has consistently shown driver behavior is the primary cause in the majority of crashes. This study evaluated the effectiveness of an automatically-assigned, targeted web-based instruction program to reduce risky driving behavior.

Method: This quasi-experiment used a within-subjects, multiple-baseline stepwise ABC design; where "A" was the Phase I baseline, "B" was the Phase II driver awareness of program, and "C" was the Phase III WBI program.

The impact of driver distraction in tractor-trailers and motorcoach buses.

Driver distraction has become an increasing concern over the last decade as portable technology has emerged and its presence while driving has become more common. Driver distraction occurs when inattention leads to a delay in recognition of information necessary to accomplish the driving task. Two recent studies were conducted using a naturalistic data collection method and analysis of driver distraction.

Comparing handheld and hands-free cell phone usage behaviors while driving.

Objective: The goal of this study was to compare cell phone usage behaviors while driving across 3 types of cell phones: handheld (HH) cell phones, portable hands-free (PHF) cell phones, and integrated hands-free (IHF) cell phones. Naturalistic driving data were used to observe HH, PHF, and IHF usage behaviors in participants' own vehicles without any instructions or manipulations by researchers.

Methods: In addition to naturalistic driving data, drivers provided their personal cell phone call records.

An analysis of driving and working hour on commercial motor vehicle driver safety using naturalistic data collection.

Current hours-of-service (HOS) regulations prescribe limits to commercial motor vehicle (CMV) drivers' operating hours. By using naturalistic-data-collection, researchers were able to assess activities performed in the 14-h workday and the relationship between safety-critical events (SCEs) and driving hours, work hours, and breaks. The data used in the analyses were collected in the Naturalistic Truck Driving Study and included 97 drivers and about 735,000 miles of continuous driving data.