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Electronics
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Feature Papers in Electrical and Autonomous Vehicles, Volume 2
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Feature Papers in Electrical and Autonomous Vehicles, Volume 2

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

Deadline for manuscript submissions: 15 March 2026 | Viewed by 96

Special Issue Editors

Prof. Dr. Sergio Busquets-Monge

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Guest Editor
Electronic Engineering Department, Universitat Politècnica de Catalunya, 08028 Barcelona, Spain
Interests: power electronics; multi-level converters; electric vehicles
Special Issues, Collections and Topics in MDPI journals
Dr. Salvador Alepuz

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Guest Editor
Tecnocampus, Universitat Pompeu Fabra, 08302 Mataró, Spain
Interests: multi-level converters; renewable energy systems; electric vehicles
Special Issues, Collections and Topics in MDPI journals
Dr. Joan Nicolás-Apruzzese

E-Mail Website
Guest Editor
Electronic Engineering Department, Universitat Politècnica de Catalunya, 08028 Barcelona, Spain
Interests: power electronics; multi-level converters; electric vehicles
Special Issues, Collections and Topics in MDPI journals
Dr. Daniel Gutiérrez Reina

E-Mail Website
Guest Editor
Electronic Engineering Department, University of Seville, 41004 Sevilla, Spain
Interests: multi-hop networks; sensor networks; VANETs; FANETs; evolutionary computation; machine learning; deep learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce that the Section Electrical and Autonomous Vehicles is compiling a collection of papers submitted by the Editorial Board Members (EBMs) of our Section and outstanding scholars in this research field. We welcome contributions as well as recommendations from EBMs.

The purpose of this Special Issue is to publish insightful original articles and reviews discussing key topics in the field. We expect these papers to be widely read and highly influential. All papers in this Special Issue will be collected into a printed-edition book after the deadline and will be well-promoted.

Topics of interest include, but are not limited to, the following:

  • Electric vehicle chargers (on-board, off-board, and wireless power transfer);
  • Converters for electric drives and power trains;
  • Battery management systems;
  • New battery technologies;
  • Power supplies for auxiliary systems;
  • Power and energy management strategies;
  • Self-driving cars/autonomous driving/vehicles;
  • Artificial intelligence applications for vehicles and traffic;
  • Electric vehicles and smart cities/smart grids/smart homes;
  • Vehicle-to-grid (V2G), vehicle-to-home (V2H), vehicle-to-everything (V2X).

Prof. Dr. Sergio Busquets-Monge
Dr. Salvador Alepuz
Dr. Joan Nicolás-Apruzzese
Dr. Daniel Gutiérrez Reina
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. Electronics 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

  • electric vehicle
  • autonomous vehicle
  • power and energy management
  • battery
  • power train
  • EV auxiliary systems
  • artificial intelligence
  • traffic
  • V2G, V2H, V2X

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (1 paper)

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Research

25 pages, 1900 KB  
Article
Collision Risk Assessment of Lane-Changing Vehicles Based on Spatio-Temporal Feature Fusion Trajectory Prediction
by Hongtao Su, Ning Wang and Xiangmin Wang
Electronics 2025, 14(17), 3388; https://doi.org/10.3390/electronics14173388 - 26 Aug 2025
Abstract
Accurate forecasting of potential collision risk in dense traffic is addressed by a framework grounded in multi-vehicle trajectory prediction. A spatio-temporal fusion architecture, STGAT-EDGRU, is proposed. A Transformer encoder learns temporal motion patterns from each vehicle’s history; a boundary-aware graph (GAT) attention network [...] Read more.
Accurate forecasting of potential collision risk in dense traffic is addressed by a framework grounded in multi-vehicle trajectory prediction. A spatio-temporal fusion architecture, STGAT-EDGRU, is proposed. A Transformer encoder learns temporal motion patterns from each vehicle’s history; a boundary-aware graph (GAT) attention network models inter-vehicle interactions; and a Gated Multimodal Unit (GMU) adaptively fuses the temporal and spatial streams. Future positions are parameterized as bivariate Gaussians and decoded by a two-layer GRU. Using probabilistic trajectory forecasts for the main vehicle and its surrounding vehicles, collision probability and collision intensity are computed at each prediction instant and integrated via a weighted scheme into a Collision Risk Index (CRI) that characterizes risk over the entire horizon. On HighD, for 3–5 s horizons, average RMSE reductions of 0.02 m, 0.12 m, and 0.26 m over a GAT-Transformer baseline are achieved. In high-risk lane-change scenarios, CRI issues warnings 0.4–0.6 s earlier and maintains a stable response across the high-risk interval. These findings substantiate improved long-horizon accuracy together with earlier and more reliable risk perception, and indicate practical utility for lane-change assistance, where CRI can trigger early deceleration or abort decisions, and for risk-aware motion planning in intelligent driving. Full article
(This article belongs to the Special Issue Feature Papers in Electrical and Autonomous Vehicles, Volume 2)
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