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Vehicle Collision Warning System for Blind Zone in Curved Roads Based on the Spatial-Temporal Correlation of Coordinate

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Web and Big Data (APWeb-WAIM 2023)

Abstract

Traffic safety has been an important research topic in intelligent transportation, especially the special terrain of mountainous areas, which increases the traffic accident rate. The main contribution of this paper is to propose a warning system for vehicles meeting in blind zones of mountain roads with low-cost, stable and reliable communication, and high accuracy data prediction. Among them, a corner-matched tracking algorithm based on special blocks and a bidirectional traffic estimation strategy based on coordinate correlation in spatiotemporal space were designed for the first time, providing reliable judgment information for the warning system. Moreover, communication methods without network environment is applied to the proposed system, solving the problem of weak network infrastructure in mountainous areas. Finally, the application performance shows that our system and its algorithm have sufficient robustness under complex weather conditions.

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Acknowledgments

This research was funded by Natural Science Foundation of Qinghai Province, grant number: 2023-ZJ-989Q.

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Correspondence to Qiao Meng .

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Meng, Q., Li, X., Zhang, Y., Huangfu, J. (2024). Vehicle Collision Warning System for Blind Zone in Curved Roads Based on the Spatial-Temporal Correlation of Coordinate. In: Song, X., Feng, R., Chen, Y., Li, J., Min, G. (eds) Web and Big Data. APWeb-WAIM 2023. Lecture Notes in Computer Science, vol 14332. Springer, Singapore. https://doi.org/10.1007/978-981-97-2390-4_17

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  • DOI: https://doi.org/10.1007/978-981-97-2390-4_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-2389-8

  • Online ISBN: 978-981-97-2390-4

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