Commercial Motor Vehicle Driver Safety Research Articles

Evaluating the Impact of Grade Crossing Safety Factors through Signal Detection Theory

The purpose of this effort was to apply signal detection theory to descriptively model the impact of five grade crossing safety factors to understand their effect on driver decision making. The safety factors consisted of: improving commercial motor vehicle driver safety through federal regulations, increasing locomotive conspicuity with alerting lights, increasing locomotive conspicuity with reflectors, increasing sight lines, and improving warning device reliability. We estimated d’ and β for eight warning devices associated with each safety factor using data from the Federal Railroad Administration’s Highway-Rail Grade Crossing Accident/Incident database and Highway-Rail Crossing Inventory. We also calculated ω2 for each safety factor and device type to examine the reliability of each independent variable on grade crossing safety. The analysis indicated that the first four safety factors listed above were generally equally effective in improving grade crossing safety. Warning device reliability (which pertained to active warning devices only) still contributed to improvements in grade crossing safety, but the effects were more muted. Grade crossing devices (and particularly active warning devices) are an important safety tool because they increase drivers’ inclinations to stop, and this bias to stop has a greater impact than improving the driver’s ability to detect the train.

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. An assessment of the drivers’ workday determined that, on average, drivers spent 66% of their shift driving, 23% in non-driving work, and 11% resting. Analyses evaluating the relationship between driving hours (i.e., driving only) and SCE risk found a time-on-task effect across hours, with no significant difference in safety outcomes between 11th driving hour and driving hours 8, 9 or 10. Analyses on work hours (i.e., driving in addition to non-driving work) found that risk of being involved in an SCE generally increased as work hours increased. This suggests that time-on-task effects may not be related to driving hours alone, but implies an interaction between driving hours and work hours: if a driver begins the day with several hours of non-driving work, followed by driving that goes deep into the 14-h workday, SCE risk was found to increase. Breaks from driving were found to be beneficial in reducing SCEs (during 1-h window after a break) and were effective in counteracting the negative effects of time-on-task.