基于车路协同的车辆状态估计方法

Vehicle State Estimation Based on V2I System

提出了一种基于车路协同的车辆质心侧偏角估计方法。该方法通过专用短程通信技术获取路侧基站的差分GPS信息,在车辆运动学模型的基础上,通过建立二次卡尔曼滤波器,融合差分GPS的航向角、车速和车载传感器的纵向加速度、横向加速度与横摆角速度信号,来估计车辆横摆角和质心侧偏角,并进行了实验验证。结果表明,即使在横向加速度较大的情况下,该方法仍具有较好的估计精度,可满足车路协同系统中车辆安全控制的要求。

A method for estimating the mass center sideslip angle of vehicle based on vehicle-to-infrastructure（ V2I） system is proposed,which uses dedicated short range communication（ DSRC） technique to acquire the difference information of GPS. Based on vehicle kinematics model and by setting up secondary Kalman filter and fusing the yaw angle and vehicle speed of difference GPS with the longitudinal and lateral accelerations and yaw rate signals of on-board sensors,the yaw angle and mass center sideslip angle of vehicle are estimated and verified by tests. The results show that the method proposed has good estimation accuracy and can meet the requirements of V2 I system on vehicle safety control even in a condition with larger yaw rate.