Artificial Intelligence and Control Technology for Unmanned Transport Systems
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: closed (30 March 2022) | Viewed by 10577
Special Issue Editors
Interests: intelligent control based on machine learning; vision-based control for autonomous vehicles; intelligent vehicle systems; optimal and robust control
Special Issues, Collections and Topics in MDPI journals
Interests: driving environment recognition based on machine learning; vision- based control for autonomous vehicles; intelligent vehicle systems; emotion recognition of driver in autonomous vehicles
Interests: computer vision; 3D feature extractor based on deep learning; video stabilization for self-driving; artificial intelligence; application to intelligence vehicle systems
Special Issue Information
Dear Colleagues,
The aim of this Special Issue is to bring together academics and industrial practitioners to exchange and discuss the latest innovations and applications of artificial intelligence (AI) in the domain of unmanned transport systems. In the past few decades, automated and intelligent transport systems have emerged, opening new research fields that are still evolving because of new challenges and technological advances in the area.
Topics
The scope of this Special Issue is the application of artificial intelligence techniques and algorithms to design and solve the existing problems of unmanned transport systems. These techniques include the following:
- Disturbance estimation and robust control for smart systems
- Fault diagnosis and failure control
- Intelligent object detection and data fusion
- Intelligent collision prediction and path planning
- Advances in control theories and applications for the smart platform
- Improving understanding of traffic, rule, and risk to control the platform in the environment
- Driver status recognition (emotion, health status, drowsiness, etc.)
- Deep learning and reinforcement learning technology for smart systems
Prof. Dr. Myo-Taeg Lim
Prof. Dr. Tae-Koo Kang
Prof. Dr. Dong-Sung Pae
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Disturbance estimation and robust control
- Sensor/actuator fault diagnosis and failure control
- Object detection and sensor fusion
- Collision detection and path planning
- Unmanned platform
- Environmental recognition
- Driver state recognition