Topic: Intelligent Decision-Making and Control for Complex Autonomous Driving Systems

The rapid development of autonomous driving technologies is creating new opportunities for safer, more efficient, and more intelligent transportation systems. However, autonomous vehicles must operate under diverse traffic conditions and interact with other vehicles, pedestrians, road infrastructure, and human drivers, making decision-making and control challenging. Integrating vehicle planning, control, traffic operations, and safety considerations is therefore essential to developing reliable autonomous driving systems.

This Special Issue aims to provide a platform for researchers to share recent advances in intelligent decision-making and control for complex autonomous driving systems. Contributions addressing theoretical methods, computational approaches, simulation, and experimental or practical applications are particularly welcome. The Special Issue encourages research that connects autonomous vehicle technologies with intelligent transportation systems, traffic safety, human factors, and emerging data-driven and AI-based methods. Original research papers and high-quality review articles are welcome.

Potential topics include, but are not limited to:

● Intelligent decision-making and motion planning for autonomous vehicles;

● Path planning, trajectory planning, and trajectory optimization;

● Automated vehicle guidance and control;

● Robust, adaptive, predictive, and learning-based control;

● Connected and automated vehicles and cooperative driving;

● Vehicle-to-vehicle and vehicle-to-infrastructure coordination;

● Autonomous driving in mixed traffic environments;

● Traffic flow modeling, prediction, and intelligent traffic management;

● Collision avoidance, risk assessment, and road safety;

● Driver behavior, human factors, and human–vehicle interaction;

● Intelligent intersection and traffic signal control;

● Reinforcement learning, artificial intelligence, and data-driven methods;

● Multi-vehicle interaction, merging, lane changing, and platooning;

● Sensor fusion, state estimation, and decision-making under uncertainty;

● Applications of autonomous driving in intelligent transportation systems.