This paper reviews model predictive control (MPC) and its wide applications to both single
and multiple autonomous ground vehicles (AGVs). On one hand, MPC is a well-established …

There is considerable evidence that evaluating the subjective risk level of driving decisions
can improve the safety of Autonomous Driving Systems (ADS) in both typical and complex …

Lane-changing is a critical issue for autonomous vehicles (AVs), especially in complex
environments. In addition, different drivers have different handling preferences. How to …

Recently, road scene-graph representations used in conjunction with graph learning
techniques have been shown to outperform state-of-the-art deep learning techniques in …

Most current research in the field of autonomous vehicle control assumes that all vehicles
will follow the same patterns of automated driving behavior, resulting in systems with …

Subjective risk assessment is an important technology for enhancing driving safety, because
an individual adjusts his/her driving behavior according to his/her own subjective perception …

The safety of urban transportation systems is considered a public health issue worldwide,
and many researchers have contributed to improving it. Connected automated vehicles …

Driving risk prediction is important for the development of intelligent vehicles (IVs), and the
rise of human-like driving requires a driving risk prediction system to match the subjective …

Human drivers have complex and unique driving characteristics, even when driving in
common, well-defined scenarios such as lane changes. In this study, we propose using …

When it comes to the verification of novel complex and learning automated driving functions,
existing standards reach their limits. In this thesis, a generic method for the online …