Older drivers are at risk for vehicle crashes due to impairments of visual processing and attention, placing these drivers at greater risk in driving tasks that require continuous attention to neighboring traffic, especially lead vehicles (LVs). We investigated car following behavior in 42 younger drivers (ages 18 to 44 years) and 58 older drivers (ages 65 to 86 years) in a driving simulator. T...

Cars have changed from pure transportation devices to fully interactive, voice-based systems. While voice interaction in the car has previously required on-board processing, the growing speed and ubiquity of wireless technologies now enable interaction with a distant source. Will the perceived source of the information influence driver safety, responses to the information, and attitudes toward ...

With increasing urbanization in China, many cities are facing serious environmental problems due to continuous and substantial increase in automobile transportation. It is becoming imperative to examine effective ways to reduce individual automobile use to facilitate sustainable transportation behavior. Empirical, theory-based research on sustainable transportation in China is limited. In this ...

Car-following (CF) behavior is one of the most important driving behaviors. Accurately understanding and modeling CF essential for traffic flow simulation user-acceptable advanced assistance systems (ADASs). In previous decades, models were calibrated based on drivers or trajectories, with short-term changes ignored. Recent studies have indicated that these could be caused by occasional irritat...