Autonomous vehicles (AVs) have now drawn significant attentions in academic and
industrial research because of various advantages such as safety improvement, lower …

The huge advantages of intelligent vehicles (IVs) in improving road safety and operating
efficiency have become a research focus in the industry. IVs have made significant progress …

In this survey, we systematically summarize the current literature on studies that apply
reinforcement learning (RL) to the motion planning and control of autonomous vehicles …

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 …

Microscopic modeling of driving behavior is the basis for traffic design and traffic simulation
studies and can be applied to automated driving systems to provide human-like decision …

Calibrating microscopic car-following (CF) models is crucial in traffic flow theory as it allows
for accurate reproduction and investigation of traffic behavior and phenomena. Typically, the …

In this article, we propose a novel personalized planning and control approach for lane
change assistance system which can efficiently learn a model prediction control (MPC) …

Car-following models have made significant contributions to our understanding of
longitudinal driving behavior. However, they often exhibit limited accuracy and flexibility, as …

In the coming decades, it is a universal consensus that autonomous vehicles (AVs) and
human-driven vehicles will share the traffic roads. Trajectory planning of AVs has been …

Developing an autonomous driving system which can generate human-like actions requires
the ability to utilize the basic driving skills learned from the driving data. The efficiency of the …