Topic Menu
► Topic MenuTopic Editors

Intelligent Transportation Systems
Topic 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 Topic 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. Angel Llamazares
Topic Editors
Keywords
- computer vision
- image processing
- lidar
- radar
- 3D perception systems
- convolutional neural networks
- CNN
- 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
- machine learning
- deep learning
- artificial intelligence
- autonomous vehicles
- driver assistance systems
- self-driving car
- machine vision
- automated driving
- autonomous car
- autonomous driving
- smart cities
- intelligent vehicle
- ITS
Participating Journals
Journal Name | Impact Factor | CiteScore | Launched Year | First Decision (median) | APC |
---|---|---|---|---|---|
![]()
Applied Sciences
|
2.5 | 5.3 | 2011 | 18.4 Days | CHF 2400 |
![]()
Sensors
|
3.4 | 7.3 | 2001 | 18.6 Days | CHF 2600 |
![]()
Sustainability
|
3.3 | 6.8 | 2009 | 19.7 Days | CHF 2400 |
![]()
Electronics
|
2.6 | 5.3 | 2012 | 16.4 Days | CHF 2400 |
![]()
Journal of Sensor and Actuator Networks
|
3.3 | 7.9 | 2012 | 19 Days | CHF 2000 |
Preprints.org is a multidisciplinary platform offering a preprint service designed to facilitate the early sharing of your research. It supports and empowers your research journey from the very beginning.
MDPI Topics is collaborating with Preprints.org and has established a direct connection between MDPI journals and the platform. Authors are encouraged to take advantage of this opportunity by posting their preprints at Preprints.org prior to publication:
- Share your research immediately: disseminate your ideas prior to publication and establish priority for your work.
- Safeguard your intellectual contribution: Protect your ideas with a time-stamped preprint that serves as proof of your research timeline.
- Boost visibility and impact: Increase the reach and influence of your research by making it accessible to a global audience.
- Gain early feedback: Receive valuable input and insights from peers before submitting to a journal.
- Ensure broad indexing: Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.