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Intelligent Transportation Systems: Beyond Intelligent Vehicles
This special issue belongs to the section “Computing and Artificial Intelligence“.
Special Issue Information
Dear Colleagues,
The development of intelligent vehicles is essential for improving urban mobility and for contributing to the development of smart cities. Also, the intelligent vehicle is the central pillar of the future of intelligent transport systems (ITS). Within the area of intelligent vehicles research there are still many challenges/areas for improvement: perception systems, scene understanding, localization and mapping, navigation, path planning, trajectory planning, vehicle control, etc.
If you look at the equipment of the vehicle, there are a variety of sensors. GPS, IMU, cameras, radars, and lidars are the most common. Lidars are the least preferred option in the industry, to avoid anti-aesthetic effects on the cars’ appearance. Cameras and lidars have experienced a small revolution thanks to the application of convolutional neural networks to the image processing. These sensors are used for localization (visual odometry, lidar odometry, 3D maps, map matching, etc.), perception (trajectory planning, scene understanding, traffic sign detection, drive-able 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;
- Advanced driver assistance systems onboard vehicles;
- Self-driving car perception and navigation systems;
- Navigation and path planning;
- Automatic vehicle trajectory planning and control.
Prof. Dr. Javier Alonso Ruiz
Dr.ir. Jeroen Ploeg
Dr. Martin Lauer
Dr. Angel Llamazares Llamazares
Prof. Dr. Noelia Hernández Parra
Guest Editors
Manuscript Submission Information
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Keywords
- Computer vision
- Lidar
- Radar
- 3D perception systems
- Convolutional neural networks
- Traffic light detection
- Collision mitigation brake systems
- Driving monitoring system
- Visual odometry
- Lidar odometry
- 3D maps construction and localization
- Scene understanding
- Traffic sign detection
- Drivable space detection
- Obstacle detection.
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