Computer Vision & Intelligent Transportation Systems

Dear Colleagues,

Perception systems have a key role in intelligent transportation systems (ITS) applications. There are a wide variety of sensors included in this topic. Cameras, radars, and lidars are the most usual ones. Radars and cameras are the preferred option in the industry, in order to avoid anti-aesthetic effects on the cars appearance. The latest ones have suffered a small revolution thanks to the application of convolutional neural networks to the image processing.  These sensors, cameras, radars, and lidars are used in several ITS applications, like intelligent traffic lights control, automatic number plate recognition, traffic flow detection, vehicle's speed detection, asphalt pavement cracks detection, and so on. Inside the vehicle, there are several advanced driver assistance systems (ADAS) that rely on perception systems, like the collision mitigation brake system, the driving monitoring system, and the parking assistance system. In addition, regarding the self-driving car, these sensors are used for localization (visual odometry, lidar odometry, 3D maps, etc.), perception (trajectory planning, scene understanding, traffic signs detection, drivable space detection, obstacle avoidance, etc.), and so on.  The aim of this Special Issue is to get a view of the latest works in these fields, and to give the reader a clear picture on the advances that are to come.  Welcome topics include, but are not strictly limited to, the following: 

• Computer vision and image processing;
• Lidar and 3D sensors;
• Radar and other proximity sensors;
• Infrastructure ITS applications;
• Advanced driver assistance systems onboard the vehicles;
• Self-driving car perception and navigation systems.

Prof. Dr. Javier Alonso Ruiz
Dr. Jeroen Ploeg
Dr. Martin Lauer
Dr. Angel Llamazares Llamazares
Prof. Dr. Noelia Hernández Parra
Dr. Carlota Salinas
Guest Editors

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