Research on Multi-Sensor Data Fusion Methods in Autonomous Driving

DOI

10.2991/978-94-6463-823-3_43How to use a DOI?

Keywords

Multi-Sensor Data Fusion; Autonomous Driving; Fusion Algorithms

Abstract

With the rapid development of autonomous driving and intelligent perception systems, multi-sensor data fusion technology has become a core means to address robust perception of complex scenes. This paper systematically discusses the hierarchical structure, core algorithms and key technical challenges of multi-sensor data fusion. First, analyze the information retention and computational complexity of data-level, feature-level, and decision-level fusion. Then, this text proposes a hybrid fusion strategy suitable for dynamic scenes. Second, combining traditional probabilistic models and deep learning methods, this paper realize the efficient alignment of LiDAR point cloud and image features through the attention mechanism. To address spatio-temporal synchronization and robustness challenges, this paper proposes a dynamic interpolation algorithm and adaptive confidence weighting. Additionally, a lightweight sparse convolutional network improves computational efficiency. The method in this paper has obvious improvement compared with traditional fusion strategy in target detection task, and the inference speed meets the real-time requirements. The results provide a theoretical basis and technical path for the engineering deployment of multimodal sensing 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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TY  - CONF
AU  - Zibo Feng
PY  - 2025
DA  - 2025/08/31
TI  - Research on Multi-Sensor Data Fusion Methods in Autonomous Driving
BT  - Proceedings of the 2025 3rd International Conference on Image, Algorithms, and Artificial Intelligence (ICIAAI 2025)
PB  - Atlantis Press
SP  - 434
EP  - 444
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-823-3_43
DO  - 10.2991/978-94-6463-823-3_43
ID  - Feng2025
ER  -