Journal
Automotive Innovation
Automotive Innovation is a dedicated platform for the publication of innovative findings in automotive field and related disciplines.
This Feature Topic delves into the multifaceted landscape of end-to-end AD techniques, encompassing fundamental theories, innovative methodologies, and deployment techniques to address the aforementioned challenges. We aim to promote the real-world impact of self-driving technology. Topics of interest include, but are not strictly limited to, the following:
Advances in design of end-to-end autonomous driving framework
Representation learning in perception, prediction, planning, etc.
Scene understanding, including static and dynamic scenes
Trends in BEV representations, including sensor fusion, temporal fusion, etc.
Deployment of end-to-end autonomous driving algorithms
New perspectives on the future of end-to-end autonomous driving
Submit your manuscript to this collection through the participating journal.
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Hongyang Li
Assistant Professor, The University of Hong Kong, Hong Kong, China -
Shengbo Eben Li
Full Professor, Tsinghua University, Beijing, China -
Christoffer Petersson
Technical Expert in Deep Learning, Zenseact, Gothenburg, Sweden