Research on QR code spraying technology for road surface in tunnels for car recognition and positioning

As the proportion of tunnels in the highway network gradually increases, traditional vehicle positioning methods are subject to many limitations in tunnels, resulting in a decrease in driving safety and efficiency inside tunnels. Therefore, this article innovatively proposes to spray QR codes on the road surface inside the tunnel, combined with the use of a specially optimized on-board driving recorder, and with the help of RViz, a powerful computer visualization tool, to achieve accurate identification and positioning of vehicles. During the experiment, three different variable factors were selected, namely vehicle speed (50km/h, 80km/h, 120km/h), asphalt grading type (AC, SMA, OGFC), and lighting conditions (5Lx, 10Lx, 15Lx), to investigate their effects on QR code recognition. In the process of experimental data processing and analysis, the visualization function of RViz is utilized to display the QR code recognition data under different variable conditions in an intuitive graphical interface, helping researchers gain clearer insights into the trend of data changes. The experimental results show that the highest recognition rates for vehicle speed, asphalt gradation type, and light intensity are between 50 to 80km/h for vehicle speed, and around 10Lx for AC asphalt gradation and light intensity control. We hope that the methods and research results proposed in this article can provide valuable references for the further development of intelligent transportation tunnel scenarios.

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Publication Details

Published
2025-04-25
DOI
https://doi.org/10.1117/12.3061485
Primary Topic
Technology and Security Systems
Type
article
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article

Research on QR code spraying technology for road surface in tunnels for car recognition and positioning

Jianfeng Hou, Danshu Yan, Haili Jiang, Zhiguo Zhao et al.
Technology and Security Systems
article

Research on QR code spraying technology for road surface in tunnels for car recognition and positioning

Jianfeng Hou, Danshu Yan, Haili Jiang, Zhiguo Zhao, F Yin, Ming Huang
article en

Abstract

As the proportion of tunnels in the highway network gradually increases, traditional vehicle positioning methods are subject to many limitations in tunnels, resulting in a decrease in driving safety and efficiency inside tunnels. Therefore, this article innovatively proposes to spray QR codes on the road surface inside the tunnel, combined with the use of a specially optimized on-board driving recorder, and with the help of RViz, a powerful computer visualization tool, to achieve accurate identification and positioning of vehicles. During the experiment, three different variable factors were selected, namely vehicle speed (50km/h, 80km/h, 120km/h), asphalt grading type (AC, SMA, OGFC), and lighting conditions (5Lx, 10Lx, 15Lx), to investigate their effects on QR code recognition. In the process of experimental data processing and analysis, the visualization function of RViz is utilized to display the QR code recognition data under different variable conditions in an intuitive graphical interface, helping researchers gain clearer insights into the trend of data changes. The experimental results show that the highest recognition rates for vehicle speed, asphalt gradation type, and light intensity are between 50 to 80km/h for vehicle speed, and around 10Lx for AC asphalt gradation and light intensity control. We hope that the methods and research results proposed in this article can provide valuable references for the further development of intelligent transportation tunnel scenarios.

Tongji University (CN), Chongqing Construction Engineering Investment Holding (China) (CN), Shanghai Construction Group (China) (CN)
Sustainable cities and communities
Openalex Percentile: Top 89%
Technology and Security Systems
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