Driving is a social activity which involves endless interactions with other agents on the road.
Failing to locate these agents and predict their possible future actions may result in serious …

Automobile industry and academic researchers expend considerable effort to develop driver
assistance systems. DASs are aware of certain driving situations and support drivers …

In this paper, we systematically study how to use edge computing to monitor the movements
of multiple connected and automated vehicles (CAV) and warn of potential accidents (eg …

Connected and automated vehicles (CAVs) are supposed to share the road with human-
driven vehicles (HDVs) in a foreseeable future. Therefore, considering the mixed traffic …

Autonomous vehicles operating in complex real-world environments require accurate
predictions of interactive behaviors between traffic participants. This paper tackles the …

We present an autonomous driving planning algorithm that takes into account neighboring
drivers' behaviors and achieves safer and more efficient navigation. Our approach leverages …

In contrast to a traditional mechanical car, the Smart Car is a highly computerized
automobile featuring ubiquitous computing, intuitive human-computer interaction and an …

With the growing popularity of digital twin and autonomous driving in transportation, the
demand for simulation systems capable of generating high-fidelity and reliable scenarios is …

Digital Twin is an emerging technology that replicates real-world entities into a digital space.
It has attracted increasing attention in the transportation field and many researchers are …

Autonomous vehicles currently suffer from a time-inefficient driving style caused by
uncertainty about human behavior in traffic interactions. Accurate and reliable prediction …