Special Issue "Advances in Machine Learning Applications to Autonomous Vehicular Networks"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".

Deadline for manuscript submissions: 31 December 2020.

Special Issue Editors

Dr. Daniel Gutiérrez Reina
Guest Editor
Electronic Engineering Department, University of Seville, Calle San Fernando, 4, 41004 Sevilla, Spain
Interests: multi-hop networks; sensor networks; VANETs; FANETs; evolutionary computation; machine learning; deep learning
Special Issues and Collections in MDPI journals
Prof. Dr. Sergio Toral Marín
Co-Guest Editor
Electronic Engineering Department, University of Seville, Calle San Fernando, 4, 41004 Sevilla, Spain
Interests: machine learning; UAVs; multi-hop networks; deep learning

Special Issue Information

Dear Colleagues,

Autonomous vehicular networks (AVNs) have experienced enormous attention from the research community and industry in the last decade. A plethora of applications can be accomplished by the cooperation and coordination of a fleet of vehicles that communicate with each other through wireless links. AVNs can be found both in aerial and aquatic scenarios for applications including monitoring and sensing, communication services, disaster relief, and goods delivery, among others. Many issues should be addressed in a distributed manner for the successful implementation of such applications. Therefore, the classical and new issues of mobile networks should be reformulated for the case of AVN scenarios.

Machine learning techniques have gained tremendous momentum in the last few years due to the availability of massive data and high computational resources at a low cost. However, classical machine learning approaches, such as supervised and unsupervised learning and evolutionary algorithms, work on centralized systems. Consequently, suffering synchronization and scalability problems in distributed systems like AVNs. This Special Issue will publish novel approaches of machine learning techniques for application in AVN scenarios. The main topics of interest include, but are not limited to the following:

  • Supervised machine learning techniques for AVNs
  • Unsupervised machine learning techniques for AVNs
  • Evolutionary computation for AVNs
  • Genetic programming for AVNs
  • Swarm intelligence for AVNs
  • Deep learning for AVNs
  • Reinforcement learning and deep reinforcement learning for AVNs
  • Bayesian optimization for AVNs
  • Game theory for wireless AVNs
  • Neural networks for AVNs
  • Soft computing approaches for AVNs
  • Blockchain approaches for AVNs

Dr. Daniel Gutiérrez Reina
Prof. Dr. Sergio Toral
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 papers will be 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. Electronics is an international peer-reviewed open access monthly 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 1500 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.


  • Autonomous vehicular systems;
  • Machine learning;
  • UAVs;
  • Drones;
  • Deep learning;
  • Evolutionary computation.

Published Papers

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