Hierarchical Composite Highway Vehicle Precise Identification Based on Multi-Source Data Fusion

DOI

10.2991/978-94-6463-514-0_28How to use a DOI?

Keywords

Hierarchical composite highway; Vehicle precise identification; ETC gantry; Multi-sensor fusion

Abstract

In the hierarchical composite highway environment, anomalies such as misidentification and reverse identification may occur between ETC gantry antennas and onboard media, leading to confusion in stored path and billing information within onboard media, causing abnormalities in toll collection at exits. To achieve precise identification of vehicles in both upper and lower layers, a multi-level data fusion-based hierarchical vehicle identification method is proposed. The basic idea is to utilize front-end perception devices such as ETC positioning antennas, LiDARs, video cameras, and license plate recognition camera. The target positioning information formed by the fusion of LiDARs and video cameras is fused with the target positioning information identified by ETC positioning antennas and gantry cameras, the identification information of successfully matched vehicles is extracted from the transaction records of ETC positioning antennas to obtain accurate vehicle perception data. The identification information is written into onboard media through ETC positioning antennas, achieving precise matching of driving vehicles and onboard media at the front end, forming complete structured vehicle information and unstructured vehicle images to support hierarchical and precise vehicle identification. The accuracy of the algorithm was validated through the development and testing of a prototype system.

Copyright

© 2024 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  - Lin Li
AU  - Hengyu Li
AU  - Jian Gao
AU  - Wanjun Li
AU  - Jierui Zhu
PY  - 2024
DA  - 2024/09/28
TI  - Hierarchical Composite Highway Vehicle Precise Identification Based on Multi-Source Data Fusion
BT  - Proceedings of the 2024 7th International Symposium on Traffic Transportation and Civil Architecture (ISTTCA 2024)
PB  - Atlantis Press
SP  - 267
EP  - 273
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-514-0_28
DO  - 10.2991/978-94-6463-514-0_28
ID  - Li2024
ER  -