Research on cooperative perception method based on heterogeneous graph attention network

Zhibang Zhong; Lijuan Li; Yanqing Li; Yong Wang; Chao Li

doi:10.1117/12.3031369

19 July 2024 Research on cooperative perception method based on heterogeneous graph attention network

Zhibang Zhong, Lijuan Li, Yanqing Li, Yong Wang, Chao Li

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131818P (2024) https://doi.org/10.1117/12.3031369
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

In this paper, we explore the use of cooperative perception to improve the perception performance of autonomous vehicles. By aggregating perception data from multiple nearby vehicles and roadside units, we can see through obstructions, detect objects at a distance, and improve detection accuracy. We propose a new cooperative perception framework, V2X-HAN. This framework mainly uses a heterogeneous graph attention network model, which can better capture the complex structure and rich information in the heterogeneous graph, achieve better feature fusion, and thus improve the accuracy of detection. We trained and validated the OPV2V and V2XSet datasets, and compared them with related models. Many experimental results show that V2X-HAN has achieved good detection results in cooperative perception.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhibang Zhong, Lijuan Li, Yanqing Li, Yong Wang, and Chao Li "Research on cooperative perception method based on heterogeneous graph attention network", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131818P (19 July 2024); https://doi.org/10.1117/12.3031369

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