Intelligent Vehicles and Autonomous Driving

Dear Colleagues,

This Special Issue is dedicated to providing a platform for experts, scholars, and engineering technicians in the fields of intelligent vehicles and autonomous driving to share scientific research results, cutting-edge technologies, academic development trends, and research ideas, and to promote cooperation in the industrialization of academic achievements.

In recent years, intelligent vehicle and autonomous driving technologies have achieved rapid developments with the promotion of artificial intelligence and vehicle networking technologies. Environment perception is responsible for understanding the surrounding environment of the vehicle. High-precision environment perception modules can provide a safety guarantee for intelligent vehicles and enhance the active safety of the transportation system. Decision making, planning, and control are also the core technologies of intelligent vehicles and autonomous driving, and they are also the focus of research in the industry.

Currently, the target detection and track algorithm based on deep learning generally have high accuracy when the network is deep, but the algorithm is time consuming. To improve the control accuracy and the adaptability of the decision-making model to different drivers, it is necessary to study driver-orientated cooperative control technologies.

To better design intelligent vehicles and autonomous driving systems, we need to comprehensively consider issues such as perception, control algorithms, positioning and mapping, human–machine interaction, and river behavior analyzation, so as to improve vehicle safety and comfort.

This Special Issue includes but is not limited to the following topics:

1. Vehicle states perception technologies;
2. Intelligent decision technologies;
3. Positioning and mapping technology;
4. Cooperative control technologies;
5. Motion planning and trajectory tracking;
6. Multi-object tracking;
7. 3D object detection;
8. Human–machine co-driving;
9. Human–machine interaction;
10. Driver behavior analyzation.

Dr. Lie Guo
Guest Editor

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• intelligent vehicle
• advanced driver assistance systems
• environmental perception
• motion planning
• trajectory tracking
• driver behavior
• human–machine cooperation
• human–machine interaction