A Roadside Precision Monocular Measurement Technology for Vehicle-to-Everything (V2X)

Autor: Peng Sun, Xingyu Qi, Ruofei Zhong
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Sensors, Vol 24, Iss 17, p 5730 (2024)
Druh dokumentu: article
ISSN: 24175730
1424-8220
DOI: 10.3390/s24175730
Popis: Within the context of smart transportation and new infrastructure, Vehicle-to-Everything (V2X) communication has entered a new stage, introducing the concept of holographic intersection. This concept requires roadside sensors to achieve collaborative perception, collaborative decision-making, and control. To meet the high-level requirements of V2X, it is essential to obtain precise, rapid, and accurate roadside information data. This study proposes an automated vehicle distance detection and warning scheme based on camera video streams. It utilizes edge computing units for intelligent processing and employs neural network models for object recognition. Distance estimation is performed based on the principle of similar triangles, providing safety recommendations. Experimental validation shows that this scheme can achieve centimeter-level distance detection accuracy, enhancing traffic safety. This approach has the potential to become a crucial tool in the field of traffic safety, providing intersection traffic target information for intelligent connected vehicles (ICVs) and autonomous vehicles, thereby enabling V2X driving at holographic intersections.
Databáze: Directory of Open Access Journals
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