交通信息与安全Issue(6)：48-53,6.DOI:10.3963/j.issn 1674-4861.2015.06.007
车路协同环境下行人目标信息融合算法研究∗
A Study of On-board Fusion and Extraction Algorithm of Pedestrian under the Environment of CVIS
摘要
Abstract
Due to its low accuracy of detection distance and occlusion,current on-board pedestrian recognition sys-tems are not suitable for implementation at curves and intersections.In order to enhance the warning effects of vehicle on-board system,this paper developed a fusion & extraction algorithm for pedestrian identification under the environment of cooperative vehicle infrastructure system (CVIS).Pedestrian is detected by roadside and on-board cameras,and pretrea-ted by a Kalman filter.The optimal position estimation of pedestrian is estimated through spatial and temporal alignment, fuzzy association and Kalman fusion.An actual vehicle experiment platform is set up to verify the effectiveness of the pro-posed fusion & extraction algorithm.Compared to errors from the pedestrian trajectory estimated before applying the fu-sion and extraction algorithm ,the maximum absolute error reduces by 5 0 .0 0 % and absolute average error reduces by 55.56% at the X direction .As to theY direction,the maximum absolute error reduces by 40.00%,and the absolute av-erage error reduces by 62.07%.Experimental results show that the proposed algorithm improves the detection accuracy of pedestrian trajectory and enhances the warning accuracy of the system significantly.关键词
交通安全/行人检测/车路协同(CVIS)/信息融合/轨迹关联Key words
traffic safety/pedestrian detection/cooperative vehicle infrastructure system(CVIS)/information fu-sion/track association分类
交通工程引用本文复制引用
李泽,吕能超,吴超仲,邓超,孟柯..车路协同环境下行人目标信息融合算法研究∗[J].交通信息与安全,2015,(6):48-53,6.基金项目
国家科技支撑计划项目(批准号:2014BAG01B0503)、中央高校基本科研业务费专项基金项目(批准号:133244003)资助 （批准号:2014BAG01B0503）
