基于道路特征的车载相机标定动态补偿算法

Dynamic Compensation Algorithm for Vehicle Camera Calibration Based on Road Characteristics

车载相机标定是基于机器视觉的车道偏离报警系统关键技术之一,通过相机透视投影原理和针孔成像模型,采用三线标定法获取相机静态外部参数。根据车辆行驶过程中颠簸振动的特点,通过数学模型分析相机标定精度的影响因素。提出一种基于道路特征的动态补偿算法,根据道路中两条车道线互相平行以及宽度不变的固有特征,对车载相机俯仰角及高度进行动态补偿。利用补偿后的俯仰角和高度值计算车辆在车道线中的横向位置及航偏角。设计一种独立于当前车载相机系统的测试平台,对该补偿算法进行动态测试。仿真和实车试验结果表明,该补偿算法可以明显减小因车辆颠簸而造成的标定误差,从而有效减少车辆横向位置和航偏角的测量误差。

The vehicle camera calibration is one of the key technologies of lane departure warning system（LDWS） based on machine vision.In according with perspective projection principle and pinhole imaging model,the external static parameters of the camera are obtained by using trilinear calibration method.Based on the characteristics of vehicle jolt during traveling,the influence factor of camera calibration precision is analyzed via the mathematical model.A dynamic compensation algorithm based on the road characteristics is proposed.The pitching angle and height of vehicle camera is dynamically compensated on the basis of the inherent characteristic that two lane lines of the road are parallel and the width is invariable.The lateral position of the vehicle in the lane and the yaw angle of vehicle running in the lane are calculated by using the pitch angle and height values after compensation.A test platform independent from the current vehicle camera system is designed and used to carry out dynamic test of the compensation algorithm.The results of simulation and real vehicle test show that the compensation algorithm can reduce the calibration error caused by vehicle jolt obviously,thus effectively reducing the measurement errors of lateral position and yaw angle of vehicle.