CAJ | 학술논문

进行道路前方车辆探测预警系统设计时，通常采用红外测距仪来获取道路前方车距信息，并以此作为前车探测的基础数据。为了消除系统状态误差和测量误差对车距信息数据精度的影响，可根据车距信息和相对车速不会突变的特性建立预测模型，基于此预测模型，应用Kalman滤波理论准确预测相对车速，并利用车距信息和相对车速计算安全距离报警阈值。试验证明该探测及预警方法可大大提高车辆探测的准确性和鲁棒性。
진행도로전방차량탐측예경계통설계시，통상채용홍외측거의래획취도로전방차거신식，병이차작위전차탐측적기출수거。위료소제계통상태오차화측량오차대차거신식수거정도적영향，가근거차거신식화상대차속불회돌변적특성건립예측모형，기우차예측모형，응용Kalman려파이론준학예측상대차속，병이용차거신식화상대차속계산안전거리보경역치。시험증명해탐측급예경방법가대대제고차량탐측적준학성화로봉성。
In design of detecting and pre-warning system for vehicles ahead of road, usually infrared distance meter is adopted to acquire information on vehicle distance ahead of road as basic data for detection of front cars. In order to eliminate influences of system status error and measurement error on accuracy of distance information data, a prediction model can be established according to the characteristic that distance information and relative speed will not change suddenly, and based on this prediction model, this paper applies Kalman filter theory to predict relative speed accurately, and calculates alarm threshold of safety distance by means of distance information and relative speed. The test proves that this detecting and pre-warning method can greatly improve accuracy and robustness of vehicle detection.