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 …

User trust has been identified as a critical issue that is pivotal to the success of autonomous
vehicle (AV) operations where artificial intelligence (AI) is widely adopted. For such …

Autonomous vehicle (AV) is expected to reshape the future transportation system, and its
decision-making is one of the most critical modules. Many current decision-making modules …

For autonomous driving, one of the major challenges is to predict pedestrian crossing
intention in ego-view. Pedestrian intention depends not only on their intrinsic goals but also …

Driver attention prediction is becoming an essential research problem in human-like driving
systems. This work makes an attempt to predict the d river a ttention in d riving a ccident …

Traffic accident anticipation aims to accurately and promptly predict the occurrence of a
future accident from dashcam videos, which is vital for a safety-guaranteed self-driving …

In recent years, studying how drivers allocate their attention while driving is critical in
achieving human-like cognitive ability for autonomous vehicles. And it has been an active …

Driver attention modeling is a crucial technique in building human-centric intelligent driving
systems. Considering the human visual mechanism, this study leverages multi-level visual …

Purpose-Perception has been identified as the main cause underlying most autonomous
vehicle related accidents. As the key technology in perception, deep learning (DL) based …

The way humans attend to, process and classify a given image has the potential to vastly
benefit the performance of deep learning models. Exploiting where humans are focusing …