交通信息与安全2025，Vol.43Issue(2)：169-176,8.DOI:10.3963/j.jssn.1674-4861.2025.02.017
面向路域感知的路侧多传感器位置标定方法
A Roadside Multi-sensor Position Calibration Method for Wide-area Perception
摘要
Abstract
Accurate sensor calibration within the stake number coordinate system is essential for wide-area percep-tion in the development of intelligent highway infrastructure.However,traditional calibration methods still struggle to meet the required accuracy and involve low efficiency and safety concerns due to manual stake number record-ing.To address these limitations,this study proposes a calibration method of roadside multi-sensor position using a test vehicle equipped with real-time kinematic(RTK)devices.The vehicle conducts fixed-point measurements at each sensor location to obtain high-precision geographic coordinates(latitude and longitude),which are subsequent-ly aligned with manually recorded stake numbers to facilitate coordinate calibration.An engineering coordinate sys-tem is introduced as an intermediate reference,enabling a unified transformation from latitude and longitude coordi-nates to engineering coordinates and ultimately to stake number coordinates.To improve robustness and automation,the proposed method incorporates an enhanced random sample consensus(RANSAC)based algorithm,which lever-ages prior knowledge of road geometry and incorporates a parameter adaptation mechanism.Calibration accuracy is further optimized through an automatic threshold selection strategy guided by mean error metrics and inlier varia-tion rates,allowing for the detection of abnormal stake numbers and the exclusion of outliers.Experimental results show that the proposed method achieves a calibration error of 0.28 m,successfully identifying and correcting 5 outli-ers,significantly outperforming the traditional least squares method,which yields a 0.63 m error and fails to identify any outliers.In comparison,the truncated least squares method results in a 0.35 m error with 21 inliers,while the least median of squares method achieves a lower error of 0.19 m but retains only 14 inliers.The proposed method maintains 19 inliers,balancing calibration accuracy and data retention,and achieves a superior trade-off between ac-curacy and robustness.Based on the calibrated sensor positions,wide-area trajectory data aligned in the stake num-ber coordinate system can intuitively represent lane-level vehicle dynamics and stake number information,demon-strating the method's practical applicability and scalability in intelligent transportation systems.关键词
智能交通/路侧传感器/传感器位置标定方法/随机采样一致/轨迹数据/智慧高速公路Key words
intelligent transportation systems/roadside sensor/sensor position calibration method/random sample consensus/trajectory data/smart highways分类
交通工程引用本文复制引用
黎成民,王俊骅,傅挺,上官强强..面向路域感知的路侧多传感器位置标定方法[J].交通信息与安全,2025,43(2):169-176,8.基金项目
国家自然科学基金项目(52472364)、上海市2023年度"科技创新行动计划""一带一路"国际合作项目(23210750500)、中央高校基本科研业务费专项资金项目(22120250070)、上海市2024年度"科技创新行动计划"启明星项目(24YF2748100)资助 （52472364）
