
Research Article
Visible Light Two-Way Communication Method for Vehicle-Road Collaboration
@INPROCEEDINGS{10.1007/978-3-031-65123-6_36, author={Caipeng Gu and Jijing Cai and Meilei Lv and Jiefan Qiu and Chenzhuo Jin and Kai Fang}, title={Visible Light Two-Way Communication Method for Vehicle-Road Collaboration}, proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Systems. 19th EAI International Conference, QShine 2023, Shenzhen, China, October 8 -- 9, 2023, Proceedings, Part II}, proceedings_a={QSHINE PART 2}, year={2024}, month={8}, keywords={IoV Visible light communication Snappy compression Frame synchronization Transformer}, doi={10.1007/978-3-031-65123-6_36} }
- Caipeng Gu
Jijing Cai
Meilei Lv
Jiefan Qiu
Chenzhuo Jin
Kai Fang
Year: 2024
Visible Light Two-Way Communication Method for Vehicle-Road Collaboration
QSHINE PART 2
Springer
DOI: 10.1007/978-3-031-65123-6_36
Abstract
With the increasing placement of sensor nodes on vehicles and Internet of Vehicles equipment, the need for online debugging of sensor nodes has grown significantly. However, current methods for online debugging of sensors heavily rely on the existing network infrastructure. In the event of communication infrastructure failure, retrieving and repairing transmission information becomes nearly impossible. In our research, we’ve employed the optical modules that accompany sensor nodes to establish a hybrid communication debugging system based on visible light communication (VLC). To enhance the efficiency of debugging information uploads, this article organizes and optimizes the original data, utilizing the Snappy compression algorithm to minimize empty time slots and achieve data compression during source encoding, thereby saving time. In addition, to bolster the reliability of data uploads, we’ve developed a frame synchronization mechanism tailored for the optical camera at the receiving end of the uplink. By employing the Transformer algorithm for frame header position prediction, we’ve improved the reliability of data collection.