Information Sensing Technology for Intelligent/Driverless Vehicle, 2nd Edition

Dear Colleagues,

This Topic is a continuation of the previous successful Topic “Information Sensing Technology for Intelligent/Driverless Vehicle”.

As the basis for vehicle positioning and path planning, the environmental perception system is a significant part of intelligent/driverless vehicles, which is used to obtain the environmental information around the vehicle, including roads, obstacles, traffic signs, and the vital signs of the driver. In the past few years, environmental perception technology based on various vehicle-mounted sensors (camera, laser, millimeter-wave radar, and GPS/IMU) has made rapid progress. With further research into automatic driving and assisted driving, the information sensing technology of driverless cars has become a research hotspot, and thus the performance of vehicle-mounted sensors should be improved to adapt to the complex driving environment of daily life. However, in reality, there are still many developmental issues, such as immature technology, lack of advanced instruments, and experimental environments not being real. All these problems pose great challenges to traditional vehicle-mounted sensor systems and information perception technology, motivating the need for new environmental perception systems, signal processing methods, and even new types of sensors.

This Topic is devoted to highlighting the most advanced studies in technology, methodology, and applications of sensors mounted on intelligent/driverless vehicles. Papers dealing with fundamental theoretical analyses, as well as those demonstrating their applications to real-world and/or emerging problems, are welcome. We welcome original papers, and some review articles, in all areas related to sensors mounted on intelligent/driverless vehicles, including, but not limited to, the following suggested topics:

• Vehicle-mounted millimeter-wave radar technology;
• Vehicle-mounted LiDAR technology;
• Vehicle visual sensors;
• High-precision positioning technology based on GPS/IMU;
• Muti-sensor data fusion (MSDF);
• New sensor systems mounted on intelligent/driverless vehicles.

Dr. Yan Huang
Dr. Yi Ren
Dr. Penghui Huang
Dr. Jun Wan
Dr. Zhanye Chen
Dr. Shiyang Tang
Topic Editors