Driving style recognition provides an effective way to understand human driving behaviors
and thereby plays an important role in the automotive sector. However, most works fail to …

For autonomous driving systems, vehicle detection is an important part and challenging
problem due to the complex traffic scenes and poor computing resources. This paper …

The advent of in-vehicle networking systems as well as state-of-the-art sensors and
communication technologies have facilitated the collection of large volume and almost real …

Driving style may have an important effect on traffic safety. Proactive crash risk prediction for
lane-changing behaviors incorporating individual driving styles can help drivers make safe …

Abstract The introduction of Automated Vehicles (AVs) into the transportation network is
expected to improve system performance, but the impacts of AVs in mixed traffic streams …

Traffic congestion is monotonically increasing, especially in large cities, due to rapid
urbanization. Traffic congestion not only deteriorates traffic operation and degrades traffic …

As the market penetration rate of automated vehicles (AVs) increases, there will be a
transition period when the traffic stream is composed of both AVs and human-driven …

Remaining driving range (RDR) research has continued to consistently evolve with the
development of electric vehicles (EVs). Accurate RDR prediction is a promising approach to …

Transportation safety is highly correlated with driving behavior, especially human error
playing a key role in a large portion of crashes. Modern instrumentation and computational …

Real-time risk assessment studies have investigated a limited length of corridors. However,
the necessity of assessing the safety performance of Connected Vehicles (CVs) requires …