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

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Review of Automotive Sensors Based on Autonomous Driving

Authors
Weiqi Liu1, *
1Faculty of Mechanical Engineering and Mechanics of Ningbo University, Ningbo, Zhejiang, 315211, China
*Corresponding author. Email: 226003375@nbu.edu.cn
Corresponding Author
Weiqi Liu
Available Online 23 October 2025.
DOI
10.2991/978-94-6463-864-6_59How to use a DOI?
Keywords
Autonomous Driving; Sensor Fusion; Environment Sensing; Solid-State Lidar; Edge Computing
Abstract

With the development of autonomous driving technology towards L3-L5 level, high-precision environment sensing becomes a core challenge for system safety and reliability. This paper systematically reviews the latest advances in autonomous driving sensor technologies, covering performance optimization and multimodal fusion strategies for optical sensors (lidar, camera, infrared thermal imaging), electromagnetic wave sensors (4D imaging radar), acoustic and inertial sensors. However, existing sensors still have significant limitations in scenarios such as extreme weather (rain, snow, haze), dynamic target recognition and computational power bottlenecks, and cutting-edge technologies such as solid-state LDAR and vehicle-circuit-cloud collaborative sensing offer potential paths to address these challenges. By analyzing the edge computing acceleration, spatio-temporal synchronization verification and reliability testing methods, this paper further emphasizes the necessity of interdisciplinary collaboration (mechanical engineering, material science, artificial intelligence) to balance the sensor reliability, environmental robustness and cost controllability, and provides theoretical support and technical references for the engineering of the autonomous driving sensing system.

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_59How 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  - Weiqi Liu
PY  - 2025
DA  - 2025/10/23
TI  - Review of Automotive Sensors Based on Autonomous Driving
BT  - Proceedings of the 2025 2nd International Conference on Electrical Engineering and Intelligent Control (EEIC 2025)
PB  - Atlantis Press
SP  - 704
EP  - 715
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-864-6_59
DO  - 10.2991/978-94-6463-864-6_59
ID  - Liu2025
ER  -