Research on On-line Measurement and Prediction for Vehicle Motion State

The research on on-line measurement and prediction technology for vehicle motion state is developed in view of shortage that the existing active safety warning systems, which focus on monitoring and warning, lack prediction process for vehicle motion state. MIMU (Micro Inertial Measurement Unit) is designed independently in order to measure vehicle motion state parameters. Then vehicle attitude and velocity integration algorithms are presented and Kalman filter is designed to accomplish sensor signals fusion in order to achieve optimal estimation of vehicle motion state parameters in consideration of low precision of MEMS (Micro-Electro-Mechanical Systems) sensors. Auto-Regressive modeling method is discussed in detail. On-line measurement and prediction software for vehicle motion state is developed based on VB2005 and NI Measurement Studio as well as Matlab, NET Builder. The road test for on-line measurement and prediction of vehicle motion state is carried out based on vehicle on-board test platform. The test result receives good effect, which testifies the validity and feasibility of on-line measurement and prediction research for vehicle motion state.