A Kalman filtering algorithm to improve CACC data accuracy in V2X environment

Hongzhuan Zhao; Ningning Lu; Jianpeng Chen; Yuming Zhang; Lina Zheng; Dan Zhou

doi:10.1117/12.2627776

14 March 2022 A Kalman filtering algorithm to improve CACC data accuracy in V2X environment

Hongzhuan Zhao, Ningning Lu, Jianpeng Chen, Yuming Zhang, Lina Zheng, Dan Zhou

Proceedings Volume 12165, International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2021); 121651E (2022) https://doi.org/10.1117/12.2627776
Event: 2021 International Conference on Intelligent Traffic Systems and Smart City, 2021, Zhengzhou, China

Abstract

The problem of noise in obtaining CACC vehicles cruises data through technologies of automatic control and wireless communication, e.g., V2X communication. Based on the Kalman Filter theory of the speed and azimuth angle between vehicles is proposed, this method analyzes the characteristics of the CACC vehicles driving in a curve. This model only considers the relationship between the previous moment and the current moment, and it applies the iterative method to deal with Kalman filtering, simplifying the calculation process. This method analyzes the characteristics of the vehicles driving in a curve, uses the Kalman filter to process the noise of the acquired data, and analyzes the influence of the presence or absence of data noise on the CACC vehicles motion law. The simulation of CarSim and Simulink shows that the proposed data processing method can improve the accuracy of the data, e.g., MSE increased by 81.03% and RMSE increased by 56.36%. The model make the CACC platoon more in line with the current situation, helping improve the efficiency of vehicles in the curved area and improve the level of traffic safety.

Citation Download Citation

Hongzhuan Zhao, Ningning Lu, Jianpeng Chen, Yuming Zhang, Lina Zheng, and Dan Zhou "A Kalman filtering algorithm to improve CACC data accuracy in V2X environment", Proc. SPIE 12165, International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2021), 121651E (14 March 2022); https://doi.org/10.1117/12.2627776

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