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Proceedings of the Human Factors and Ergonomic Society annual meeting

Journal Volume: 50
Journal Issue: 22
Journal Year: 2006
Articles in SafetyLit: 24

A preliminary evaluation of a driver-infrastructure interface for a left-turn warning

An examination of the yardmaster's role in railroad yard safety

Are drivers with small feet or long legs at greater risk of rear end collisions?

Assessment of age differences in mental workload while driving using verbal versus visual-spatial subsidiary tasks

Brain waves suppressed by cell phone conversations

Comprehension of haptic seat displays for integrated driver warning systems

Evaluation of lane departure warnings for drowsy drivers

Field evaluation of a risk awareness and perception training program for younger drivers

Haptic and auditory cues for lane departure warnings

Novice and experienced driving performance with cell phones

Novice teen and experienced adult drivers on the smart road intersection: does six months of experience matter?

On-road evaluation of an in-vehicle curve warning device

Pedestrian detection with night vision systems enhanced by automatic warnings

Predictive displays for survey vessels

Prevention of rear-end crashes in drivers with task-induced fatigue through the use of auditory collision avoidance warnings

Queuing network modeling of driver workload and performance

The effect of phone interface and dialing method on simulated driving performance and user preference

The evolution and future of the highway safety field through the eyes of multiple generations of Lauer awardees

The occlusion procedure for assessing in-vehicle telematics: tests of current vehicle systems

Time-to-collision judgments of constant and non-constant velocities: implications for rear-end collisions

Truck drivers' ability to locate targets briefly seen in mirrors

Using a task analysis to identify potential information processing bottlenecks in intersection driving scenarios

Using glance behaviour to evaluate ACC driver controls in a driving simulator

Using machine learning techniques to reduce data annotation time