Automated Driving Systems (ADS) have made great achievements in recent years thanks to
the efforts from both academia and industry. A typical ADS is composed of multiple modules …

There is a lack of approaches to derive accident scenarios automatically for the testing of
Autonomous Drive systems. Current approaches that generate test scenarios do not scale …

The application of naturalistic driving data (NDD) has the potential to answer critical
research questions in the area of driving behavior assessment, as well as the impact of …

Intelligent‐driving technologies play crucial roles in reducing road‐traffic accidents and
ensuring more convenience while driving. One of the significant challenges in developing …

Decision making is an essential component of autonomous vehicle technology and received
significant attention from academic and industry organizations. One of the promising …

Safely and efficiently completing unprotected left turns at intersections is challenging for both
automated vehicles and human drivers, given that it is hard to predict the intentions of other …

Currently, the most prevalent way to evaluate an autonomous vehicle is to directly test it on
the public road. However, because of recent accidents caused by autonomous vehicles, it …

The truck operation of freeway has an impact on traffic safety. In particular, the gradually
increasing in truck proportion will inevitably affect the freeway traffic operation of different …

Urban road intersections play an important role in deciding the total travel time and the
overall travel efficiency. In this paper, an innovative traffic grid model has been proposed …

It is necessary to evaluate the safety of highly automated vehicles (HAVs) rigorously before
their deployment on public roads. This paper describes a procedure to conduct behavioral …