Vehicle global localization based on V2I collaboration in GNSS-denied  environments

Di Wang; Fei Ge; Ke Wang; Hui Chen; Wenwen Jia; Xuelian Liu; Zhanwen Liu

doi:10.1117/12.3050786

20 January 2025 Vehicle global localization based on V2I collaboration in GNSS-denied environments

Di Wang, Fei Ge, Ke Wang, Hui Chen, Wenwen Jia, Xuelian Liu, Zhanwen Liu

Author Affiliations +

Proceedings Volume 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024); 1342207 (2025) https://doi.org/10.1117/12.3050786
Event: Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 2024, Xi'an, China

Abstract

Since GNSS signals tend to be blocked in underpass environments and general SLAM methods still struggle with cumulative errors in large-scale scenes, traditional localization methods are more likely to degrade in GNSS-denied areas. To address this problem, we design a vehicle-road-collaborative-based global positioning system, which combines the vehicle-end local positioning module and the road-end 3D target detection module to conduct global localization. Specifically, the vehicle utilizes the pre-calibrating global information of road-end system to bridge the gap between the local coordinate and the global coordinate. To further improve the positioning performance, we analyze the uncertainty of the perception results of the road-end system, and constructing a novel factor graph to fuse traditional self-motion constraints and the perception information of the road-end system. Meanwhile, to alleviate the communication delay problem, we build a dynamic interpolation module to align the observations at diverse sampling timestamps. We demonstrate the performance of our method by conducting comprehensive real experiments. Our qualitative and quantitative experimental results obviously outperform those of competing methods.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Di Wang, Fei Ge, Ke Wang, Hui Chen, Wenwen Jia, Xuelian Liu, and Zhanwen Liu "Vehicle global localization based on V2I collaboration in GNSS-denied environments", Proc. SPIE 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 1342207 (20 January 2025); https://doi.org/10.1117/12.3050786

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KEYWORDS

Point clouds

Interpolation

Object detection

3D acquisition

LIDAR

Target detection

Telecommunications

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