Recent Advances in Intelligent Vehicles and Intelligent Transportation Systems

Dear Colleagues,

Intelligent vehicles are an integral part of intelligent transportation systems, which utilize a combination of sensors, cameras, radar, and advanced algorithms to navigate roads safely without human intervention. Ongoing research in this area focuses on several key areas, including environmental perception, decision-making, path planning, and vehicle control.

Environmental Perception: Intelligent vehicles rely on a variety of sensors, such as lidars, radars, and cameras, to perceive their environment. These sensors provide data about the surrounding objects, including their position, speed, and direction. Research in this area aims to improve the accuracy and reliability of these sensors, as well as develop algorithms to fuse data from multiple sensors for a more comprehensive understanding of the vehicle's surroundings.

Decision-Making and Path Planning: Once the vehicle has perceived its environment, it must make decisions about how to navigate safely and efficiently. This involves selecting the best path to reach the destination while avoiding obstacles and adhering to traffic rules. Research in this area focuses on developing advanced algorithms that can handle complex scenarios, such as intersections, pedestrian crossings, and merging into traffic.

Vehicle Control: Intelligent vehicles require precise control algorithms to ensure smooth and safe driving. These algorithms must take into account various factors, such as road conditions, weather, and the behavior of other road users. Research in this area aims to develop robust control systems that can adapt to changing conditions and respond appropriately in emergency situations.

This Special Issue addresses new environmental perception, decision-making, path planning, and vehicle control techniques used in intelligent vehicles and intelligent transportation systems. Survey papers are also welcome.

Dr. Jinghua Guo
Dr. Jingyao Wang
Guest Editors

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