Intelligent vehicles (IVs) have gained worldwide attention due to their increased
convenience, safety advantages, and potential commercial value. Despite predictions of …

The emergence of new services and applications in emerging wireless networks (eg,
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …

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 first comprehensive introduction to Multi-Agent Reinforcement Learning (MARL),
covering MARL's models, solution concepts, algorithmic ideas, technical challenges, and …

Autonomous driving (AD) holds the potential to revolutionize transportation efficiency, but its
success hinges on robust behavior planning (BP) mechanisms. Reinforcement learning (RL) …

In the near future, autonomous vehicles (AVs) may cohabit with human drivers in mixed
traffic. This cohabitation raises serious challenges, both in terms of traffic flow and individual …

Intelligent energy management in renewable-based power distribution applications, such as
microgrids, smart grids, smart buildings, and EV systems, is becoming increasingly important …

The rapid improvements in communication and self-driving technology in recent years have
made connected autonomous cars an essential component of urban road transit. Connected …

Connected and automated vehicles (CAVs) require multiple tasks in their seamless
maneuverings. Some essential tasks that require simultaneous management and actions …

Lane-Change (LC) maneuvers are deemed to jeopardize traffic safety, mobility, and
sustainability. Cooperative Lane-Change (CLC) solves this problem by accelerating the LC …