The “Electrical and Autonomous Vehicles” Section addresses the different perspectives on the design, development, and usage of electric and autonomous vehicles, as well as their impact on people’s lives, on cities, and on power as well as energy systems. We welcome papers on innovative scientific and technical developments, sound case studies, and reviews which are relevant and/or related to “Electrical and Autonomous Vehicles”. As they are of an open access format, you have free and unlimited access to the full text of all the articles published in our journal. We welcome you to read our most highly cited papers published in 2021 listed below:

1. “Review of Electric Vehicle Technologies, Charging Methods, Standards and Optimization Techniques”
by Syed Muhammad Arif et al.
Electronics 2021, 10(16), 1910; https://doi.org/10.3390/electronics10161910
Available online: https://www.mdpi.com/2079-9292/10/16/1910

2. “Is There a Predisposition towards the Use of New Technologies within the Traffic Field of Emerging Countries? The Case of the Dominican Republic”
by Francisco Alonso et al.
Electronics 2021, 10(10), 1208; https://doi.org/10.3390/electronics10101208
Available online: https://www.mdpi.com/2079-9292/10/10/1208

3. “An Enhanced Multicell-to-Multicell Battery Equalizer Based on Bipolar-Resonant LC Converter”
by Xuan Luo et al.
Electronics 2021, 10(3), 293; https://doi.org/10.3390/electronics10030293
Available online: https://www.mdpi.com/2079-9292/10/3/293

4. “A Simulated Annealing Algorithm and Grid Map-Based UAV Coverage Path Planning Method for 3D Reconstruction”
by Sichen Xiao Azar et al.
Electronics 2021, 10(7), 853; https://doi.org/10.3390/electronics10070853
Available online: https://www.mdpi.com/2079-9292/10/7/853

5. “A Survey of Trust Management in the Internet of Vehicles”
by Sarah Ali Siddiqui et al.
Electronics 2021, 10(18), 2223; https://doi.org/10.3390/electronics10182223
Available online: https://www.mdpi.com/2079-9292/10/18/2223

6. “Ego-Motion Estimation Using Recurrent Convolutional Neural Networks through Optical Flow Learning”
by Baigan Zhao et al.
Electronics 2021, 10(3), 222; https://doi.org/10.3390/electronics10030222
Available online: https://www.mdpi.com/2079-9292/10/3/222

7. “Machine Learning-Based Vehicle Trajectory Prediction Using V2V Communications and On-Board Sensors”
by Dongho Choi et al.
Electronics 2021, 10(4), 420; https://doi.org/10.3390/electronics10040420
Available online: https://www.mdpi.com/2079-9292/10/4/420

8. “An Optimization Model for Energy Community Costs Minimization Considering a Local Electricity Market between Prosumers and Electric Vehicles”
by Ricardo Faia et al.
Electronics 2021, 10(2), 129; https://doi.org/10.3390/electronics10020129
Available online: https://www.mdpi.com/2079-9292/10/2/129

9. “Deep Feature-Level Sensor Fusion Using Skip Connections for Real-Time Object Detection in Autonomous Driving”
by Vijay John et al.
Electronics 2021, 10(4), 424; https://doi.org/10.3390/electronics10040424
Available online: https://www.mdpi.com/2079-9292/10/4/424

10. “A Survey on Deep Learning Based Approaches for Scene Understanding in Autonomous Driving”
by Zhiyang Guo et al.
Electronics 2021, 10(4), 471; https://doi.org/10.3390/electronics10040471
Available online: https://www.mdpi.com/2079-9292/10/4/471