Bruce Artz

Driver Distraction: Evaluation with Event Detection Paradigm

The effects of eight in-vehicle tasks on driver distraction were measured in a large, moving-base driving simulator. Forty-eight adults, ranging in age from 35 to 66, and 15 teenagers participated in the simulated drive. Hand-held and hands-free versions of phone dialing, voicemail retrieval, and incoming calls represented six of the eight tasks. Manual radio tuning and climate control adjustment were also included to allow comparison with tasks that have traditionally been present in vehicles. During the drive the participants were asked to respond to sudden movements in surrounding traffic. The driver’s ability to detect these sudden movements or events changed with the nature of the in-vehicle tasks that were being performed. Driving performance measures such as lane violations and heading error were also computed. The performance of the adult group was compared with the performance of the teenage drivers. Compared with the adults, the teens were found to choose unsafe following distances, have poor vehicle control skills, and be more prone to distraction from hand-held phone tasks.

Evaluation of Lane Departure Warnings for Drowsy Drivers

Lane departure warning (LDW) is a driver warning system designed to reduce the number of unintended lane departures. We addressed warning effectiveness and customer acceptance when the unintended lane departures are the result of drowsy driving. Thirty-two adults who were sleep deprived for 23 hours participated in the study and drove Fords VIRTTEX driving simulator. Four Human Machine Interfaces (HMI) for LDW were evaluated: Steering Wheel Torque, Rumble Strip Sound, Steering Wheel Vibration and Head Up Display. A yaw deviation technique was used to produce controlled lane departures in the first two hours of the drive while for the last 20 minutes driver-initiated lane departures were analyzed. The Steering Wheel Vibration HMI, accompanied by Steering Wheel Torque, was found to be the most effective HMI for LDW in a group of drowsy drivers, with faster reaction times and smaller lane excursions. The Vibration HMI was also perceived by the drowsy drivers to be acceptable and helpful.

Leading Indicators of Drowsiness in Simulated Driving

Drowsiness while driving was measured using three measures: a physiological measure of eye closure, a sustained reaction time task and a subjective assessment. The study was conducted in Fords VIRTTEX driving simulator. Thirty-two adults who were sleep deprived for 24 hours and six adults who had a full night of sleep participated in the study. The performance of the sleep-deprived group was compared with that of the control group. Sleep-deprived drivers had significantly longer PVT reaction times, a greater number of lapses, higher PERCLOS values and perceived themselves as sleepier than did the control group. This study demonstrated the ability to successfully implement drowsiness measures in a driving simulator. The advantage of a three-hour simulator drive in providing increasing levels of drowsiness in each subject was established. These findings provide metrics that can be used to evaluate the efficacy and acceptability of safety systems for drowsy drivers.

Analysing classes of motion drive algorithms based on paired comparison techniques

A paired comparison experiment using 23 subjects was run on the VIRTTEX driving simulator to compare a lane position based motion drive algorithm (MDA) with a classical MDA for a highway speed, lane change manoeuvre. Two different tuning states of the lane position algorithm and four different tuning states for the classical algorithm were tested. The subjective fidelity of the six different motion cases was compared with each other and a Bradley–Terry model was fit to find the fidelity merit of each case. In addition, the driving performance of the subjects for six motion cases was recorded and compared. The motion-tuning cases were selected such that the trade-off in motion quality between overall motion scaling and motion shape distortion (shape-error), as well as the trade-off between lateral specific force and roll-rate motion errors, could be studied. It was found that when the overall scaling is the same, drivers perform better with the lane position algorithm than with the the classical algorithm. A well-tuned, manoeuvre-specific, classical MDA, however, did achieve a subjective fidelity level on a par with the lane position MDA. A generically tuned classical MDA, however, has a significantly reduced fidelity and driving performance when compared with a lane position algorithm with the same scale factor. A strong trade-off between motion shape-errors and overall motion scaling was found. A small increase in motion cue shape-error, combined with an increase in the scale factor from 0.3 to 0.5, led to improved performance and increased subjective fidelity. The results of the experiment also suggest that simulator motion can be improved by reducing the angular-rate shape-error at the expense of the specific force shape-error (while keeping the total normalised shape-error constant).