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WEVJ
Volume 17
Issue 6
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World Electr. Veh. J., Volume 17, Issue 6 (June 2026) – 2 articles

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38 pages, 5684 KB  
Review
Vision and Multimodal Perception for Autonomous Driving: Deep Learning Architectures, Tasks, and Sensor Fusion
by Savvas Nikolaidis and Paraskevas Koukaras
World Electr. Veh. J. 2026, 17(6), 277; https://doi.org/10.3390/wevj17060277 - 22 May 2026
Abstract
The rapid development of autonomous vehicles is based mainly on their ability to accurately perceive their environment, where artificial intelligence and computer vision act as the core of environmental perception. In this regard, deep learning-based perception architectures have revolutionized the field of autonomous [...] Read more.
The rapid development of autonomous vehicles is based mainly on their ability to accurately perceive their environment, where artificial intelligence and computer vision act as the core of environmental perception. In this regard, deep learning-based perception architectures have revolutionized the field of autonomous driving. However, as the use of single sensors fails to ensure reliability in complex scenarios, multimodal sensor fusion has become an essential part of modern deep learning architectures. In this context, covering the literature from 2020 to 2025, we analyze the transition from traditional Convolutional Neural Networks (CNNs) to modern Vision Transformers (ViTs) and explore data fusion design methodologies at various processing levels. In addition, significant limitations related to adverse weather conditions and dynamic environments, computational resources and overall quality and management of data are identified. The conducted comparative analysis indicates that vision-transformer and multimodal fusion methodologies provide higher accuracy in perception tasks but at the cost of increased computational requirements and sensor synchronization challenges. Finally, it becomes clear that achieving full autonomy requires further research in subjects such as collaborative perception, unsupervised domain adaptation and the creation of lightweight models, thus offering a roadmap for future developments. Full article
(This article belongs to the Section Automated and Connected Vehicles)
28 pages, 4773 KB  
Perspective
New Paradigms in Automotive Engineering
by Ching-Chuen Chan, Tianlu Ma, Xiaosheng Wang, Yibo Wang, Hanqing Cao and Chaoqiang Jiang
World Electr. Veh. J. 2026, 17(6), 276; https://doi.org/10.3390/wevj17060276 - 22 May 2026
Abstract
Driven by global energy transformation and the progress of artificial intelligence technology, traditional automotive engineering is undergoing profound changes. Transportation is rapidly advancing toward electrification and intelligence. Against this background, this paper identifies three emerging paradigms for the development of electric vehicles: Heart [...] Read more.
Driven by global energy transformation and the progress of artificial intelligence technology, traditional automotive engineering is undergoing profound changes. Transportation is rapidly advancing toward electrification and intelligence. Against this background, this paper identifies three emerging paradigms for the development of electric vehicles: Heart Revolution, Brain Evolution, and Network Integration. This paper points out that automobiles are evolving from traditional one-way energy consumers to dynamic energy nodes in smart grids. With the support of artificial intelligence technology, the role of automobiles is also shifting from a simple means of transportation to an intelligent mobile terminal. At the same time, this paper focuses on analyzing the application of the integration theory of “Four Networks and Four Flows” in automobile upgrading. The theory does not focus on the optimization of a single node unit but emphasizes a systematic perspective to improve overall performance and support sustainable development. This paper suggests that the development of the automobile industry must be deeply integrated with the humanity world, information world and physical world. By building a five-in-one architecture of “Human–Vehicle–Road–Cloud–Satellite”, the automobile industry could follow a practical pathway toward coordinated development. At the same time, breakthroughs in core technologies such as solid-state batteries and wide-bandgap semiconductors are also imminent. This paper aims to provide a sustainable and high-performance automobile development path and integrate the concept of human-oriented design into it. Meanwhile, China’s new energy vehicle industry is used as a representative context to illustrate its engineering and industrial implementation. Full article
(This article belongs to the Special Issue New Journey of Energy and Electric Vehicle Revolutions—Infinite Possibilities in the Science World: In Honor of Prof. Dr. C.C. Chan’s 90th Birthday)
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