Proceedings of the 2025 2nd International Conference on Electrical Engineering and Intelligent Control (EEIC 2025)

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Multi-Sensor Fusion in Autonomous Driving

Authors
Yucheng Liu1, Xipei Tang2, *, Xiaohan Yu1
1Dublin International Transport College, Chang’an University, Xi’an, Shaanxi Province, 710064, China
2School of Traffic and Logistics Engineering, Wuhan University of Technology, Wuhan, Hubei, 430070, China
*Corresponding author. Email: wonder051126@ldy.edu.rs
Corresponding Author
Xipei Tang
Available Online 23 October 2025.
DOI
10.2991/978-94-6463-864-6_79How to use a DOI?
Keywords
Autonomous Driving; Multi-Sensor Fusion; Environmental Perception; Sensor Performance; Data Fusion
Abstract

Multimodal sensor fusion plays a significant role in vehicle driving, improving environmental perception accuracy and reliability. Subsequently, applications and challenges in environmental perception, positioning and navigation, attitude perception are discussed. And cutting-edge technologies such as the fusion of millimetre-wave radar and cameras are analyzed, especially the emerging integration of LiDAR with infrared sensors to enhance low-light environment perception capabilities. Innovations in environmental perception and modeling are also explored. Point cloud generation of multimodal data fusion is likewise studied. New fusion architectures and related hardware upgrades are researched as well. Two-dimensional image conversion methods with multi-adaptive high-precision depth completion are also analysed. The challenges in this field, such as sensor performance differences, data fusion problems, system safety and reliability, and the lack of standard specifications, are analyzed. Finally, it is pointed out that in the future, sensor performance needs to be optimized and data fusion algorithms improved to promote technological development and contribute to the construction of intelligent transportation systems.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 2nd International Conference on Electrical Engineering and Intelligent Control (EEIC 2025)
Series
Advances in Engineering Research
Publication Date
23 October 2025
ISBN
978-94-6463-864-6
ISSN
2352-5401
DOI
10.2991/978-94-6463-864-6_79How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yucheng Liu
AU  - Xipei Tang
AU  - Xiaohan Yu
PY  - 2025
DA  - 2025/10/23
TI  - Multi-Sensor Fusion in Autonomous Driving
BT  - Proceedings of the 2025 2nd International Conference on Electrical Engineering and Intelligent Control (EEIC 2025)
PB  - Atlantis Press
SP  - 912
EP  - 923
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-864-6_79
DO  - 10.2991/978-94-6463-864-6_79
ID  - Liu2025
ER  -