CAJ | 학술논문

针对 A ／D 转换精度高但速度慢而电压比较器速度快但精度低，提出了结合二者来对摄像头输出的道路视频信息进行采集的方法。每行分别可靠采集12个高精度点和132个二值点，去噪后采用最小二乘法拟合直线获得智能车控制所需要的路径信息。采用跟踪智能车偏离引导线中心的平均距离和引导线斜率的双指标改进 PID 算法实现对智能车的方向控制。较传统的路径识别与方向控制算法相比，该算法具有数据采集和方向控制精确、系统鲁棒性更好的特点。实验结果验证了所提出方法的可行性。
침대 A ／D 전환정도고단속도만이전압비교기속도쾌단정도저，제출료결합이자래대섭상두수출적도로시빈신식진행채집적방법。매행분별가고채집12개고정도점화132개이치점，거조후채용최소이승법의합직선획득지능차공제소수요적로경신식。채용근종지능차편리인도선중심적평균거리화인도선사솔적쌍지표개진 PID 산법실현대지능차적방향공제。교전통적로경식별여방향공제산법상비，해산법구유수거채집화방향공제정학、계통로봉성경호적특점。실험결과험증료소제출방법적가행성。
A combined method of A /D conversion and voltage comparator was proposed to improve the precision and speed of road video data collection.12 high-precision point data and 132 binary data per row were achieved.The necessary path information for the smart vehicle to steer automati-cally was acquired by using linear least squares fitting method after denoising the data.An improved proportion,integration and differentiation (PID)algorithm was implemented to control the direction of the vehicle,considering both the average distance between the smart vehicle and the center of the guide line and the slope of the line.The proposed algorithm can acquire the path information and control the steer more accurately and is more robust compared with the traditional path recognition and steering control algorithm.The experimental results demonstrate the feasibility of the proposed method.