Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving
and transportation systems to digitize and synergize connected automated vehicles …

Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …

The emergence of vehicle-to-everything (V2X) technology offers new insights into
intersection management. This, however, has also presented new challenges, such as the …

In the context of autonomous driving, the iterative linear quadratic regulator (iLQR) is known
to be an efficient approach to deal with the nonlinear vehicle model in motion planning …

To address the coordination issue of connected automated vehicles (CAVs) at urban
scenarios, a game-theoretic decision-making framework is proposed that can advance …

This research proposes an integrated behavioral and motion planner with proactive right-of-
way acquisition capability. The proposed planner overcomes the shortcomings of …

The development of autonomous vehicles has shown great potential to enhance the
efficiency and safety of transportation systems. However, the decision-making issue in …

Reinforcement learning-based techniques, empowered by deep-structured neural nets,
have demonstrated superiority over rule-based methods in terms of making high-level …

This paper proposes a novel deep learning framework for multi-modal motion prediction.
The framework consists of three parts: recurrent neural network to process target agent's …

In order to resolve the driving conflict and improve the safety and efficiency of autonomous
vehicles at unsignalized intersections, a new decision-making method based on game …