Research on Comprehensive Vehicle Information Detection Technology Based on Single-Point Laser Ranging

In response to the limitations of existing vehicle detection technologies when applied to distributed sensor networks for road traffic holographic perception, this paper proposes a vehicle information detection technology based on single-point laser ranging. The system uses two single-point laser radars with fixed angles, combined with an adaptive threshold state machine and waveform segmentation fusion, to accurately detect vehicle speed, lane position, and other parameters. Compared with traditional methods, this technology offers advantages such as richer detection dimensions, low cost, and ease of installation and maintenance, making it suitable for large-scale traffic monitoring on secondary roads, highways, and suburban roads. Experimental results show that the system achieves high accuracy and reliability in low-to-medium-traffic flow scenarios, demonstrating its potential for intelligent road traffic applications.

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Publication Details

Journal
Sensors
Published
2025-02-20
DOI
https://doi.org/10.3390/s25051303
Citations
1
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
Field-Weighted Citation Impact
0.68
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article

Research on Comprehensive Vehicle Information Detection Technology Based on Single-Point Laser Ranging

Yunbo Liu, Hui Zhang, Xin Wen, Haiyu Chen
1 citations
Sensors
Autonomous Vehicle Technology and Safety
0.68
article

Research on Comprehensive Vehicle Information Detection Technology Based on Single-Point Laser Ranging

Yunbo Liu, Hui Zhang, Xin Wen, Haiyu Chen
article en
1 citations

Abstract

In response to the limitations of existing vehicle detection technologies when applied to distributed sensor networks for road traffic holographic perception, this paper proposes a vehicle information detection technology based on single-point laser ranging. The system uses two single-point laser radars with fixed angles, combined with an adaptive threshold state machine and waveform segmentation fusion, to accurately detect vehicle speed, lane position, and other parameters. Compared with traditional methods, this technology offers advantages such as richer detection dimensions, low cost, and ease of installation and maintenance, making it suitable for large-scale traffic monitoring on secondary roads, highways, and suburban roads. Experimental results show that the system achieves high accuracy and reliability in low-to-medium-traffic flow scenarios, demonstrating its potential for intelligent road traffic applications.

SensorsVol. 25(5)
Sun Yat-sen University (CN)
Sustainable cities and communities
Openalex Percentile: Top 34%
Autonomous Vehicle Technology and Safety
0.68
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