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Vehicle Relative Positioning System Based on Vision and V2X

Libo Cao, Leqi Zhang, Lingbo Yan, Zheng Chen, Guoliang Xiang


Obtaining the accurate position information of the vehicle is of great significance for the intelligent driving assistance system. Due to the relative positioning accuracy based on Global Positioning System is not high enough and the signal is unstable, and the positioning system based on wireless communication needs to lay a large number of roadside units, a relative positioning method based on vision and V2X is proposed. The error distribution of the positioning method is analyzed, and the positioning result is Kalman filtering. The results show that the relative positioning system can achieve positioning accuracy within 0.38m of the smooth straight road and 0.35m of the curved and large undulating road, and its positioning stability can be improved after Kalman filtering.


Intelligent Transportation Systems; Relative Positioning; V2X; Vision

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DOI: http://dx.doi.org/10.18686/mt.v8i1.2005