Driving safety has been a concern since the first cars appeared on the streets. Driver
inattention has been singled out as a major cause of accidents early on. This is hardly …

The inclusion of in-vehicle sensors and increased intention and state recognition
capabilities enable implicit in-vehicle interaction. Starting from a systematic literature review …

Human driving behaviors are personalized and unique, and the automobile fingerprint of
drivers could be helpful to automatically identify different driving behaviors and further be …

Driver braking behavior was analyzed using time-series recordings from naturalistic rear-
end conflicts (116 crashes and 241 near-crashes), including events with and without visual …

Objective We present a model for visual behavior that can simulate the glance pattern
observed around driver-initiated, non-critical disengagements of Tesla's Autopilot (AP) in …

With modern infotainment systems, drivers are increasingly tempted to engage in secondary
tasks while driving. Since distracted driving is already one of the main causes of fatal …

Real-time driving risk status prediction is critical for developing proactive traffic intervention
strategies and enhance driving safety. However, the optimal observation time window length …

As the development and deployment of in-vehicle intelligent safety systems (ISS) for crash
avoidance and mitigation have rapidly increased in the last decades, the need to evaluate …

Cyclists and pedestrians account for a significant share of fatalities and serious injuries in
the road transport system. In order to protect them, advanced driver assistance systems are …

There is currently no established method for evaluating human response timing across a
range of naturalistic traffic conflict types. Traditional notions derived from controlled …