Abstract
To improve the vehicle state estimation accuracy under V2V system, the vehicle state estimation method which uses the multiple information fusion is presented. Through the establishment of the automobile kinematics mode and state equation of vehicle state parameter estimation, the method uses extended kalman filter method to realize the accurately estimation of vehicle real-time state parameters. Based on Matlab/Simulink the vehicle state estimation simulation platform of constant speed circular motion is built, The simulation results show that this method can achieve the accurate state estimation of vehicle.
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Acknowledgements
This paper is supported by the Opening Project of Key Laboratory of Intelligent Transportation Systems Technologies, Ministry of Communications, P.R.China and the special fund project of central university basic scientific research business expenses (No. 2014G1321040) and the national college students’ innovative entrepreneurial training program(No. 201510710036).
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Pan, Y., Tang, Z., Gong, X., Tang, C. (2015). Vehicle State Estimation Based on V2V System. In: Hsu, CH., Xia, F., Liu, X., Wang, S. (eds) Internet of Vehicles - Safe and Intelligent Mobility. IOV 2015. Lecture Notes in Computer Science(), vol 9502. Springer, Cham. https://doi.org/10.1007/978-3-319-27293-1_27
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DOI: https://doi.org/10.1007/978-3-319-27293-1_27
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