Generative Artificial Intelligence Technologies and Applications for Road Environment Understanding

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 October 2024 | Viewed by 83

Special Issue Editors


E-Mail Website
Guest Editor
Department of Information Management, Chaoyang University of Technology, Taichung 413310, Taiwan
Interests: data mining; social networking; quality management; customer relationship management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue explores the latest advancements and applications of generative AI technologies to enhance understanding road environments. Generative AI models have demonstrated remarkable capabilities in synthesizing realistic data, enabling novel solutions for tasks such as scene generation, object detection, and semantic segmentation in road environments. The topics will cover theoretical foundations, methodological developments, and the practical applications of generative AI for road scene analysis, 3D environment modeling, traffic flow prediction, and other related areas. The Special Issue will provide a platform for disseminating innovative ideas, fostering interdisciplinary collaborations, and driving progress in this rapidly evolving field. The topics include but are not limited to the following:

  1. Generative adversarial networks for road scene synthesis and augmentation;
  2. Variational autoencoders for road environment modeling and reconstruction;
  3. Diffusion models for road scene generation and editing;
  4. Generative models for 3D road environment reconstruction;
  5. Conditional generative models for road object detection and segmentation;
  6. Generative models for traffic flow prediction and simulation;
  7. Adversarial training techniques for road environment understanding;
  8. Interpretability and explainability of generative models in road scene analysis;
  9. Multimodal generative models for road environments (e.g., combining vision and LiDAR data);
  10. Generative models for data augmentation and domain adaptation in road scene understanding;
  11. Generative models for road sign and lane marking synthesis;
  12. Applications of generative AI in autonomous driving, intelligent transportation systems, and road safety.

Prof. Dr. Rung-Ching Chen
Prof. Dr. Long-Sheng Chen
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

  • deep learning
  • synthetic data generation
  • road environments
  • scene understanding
  • intelligent transportation systems
  • autonomous driving
  • object detection
  • semantic segmentation
  • generative adversarial networks (GANs)
  • variational autoencoders (VAEs)

Published Papers

This special issue is now open for submission.
Back to TopTop