城市快速路多尺度交通数据融合方法  

Multi-scale Traffic Data Fusion Method for Urban Expressway

作　　者：邴其春[1] 杨兆升[2] 曲大义[1] 陈秀锋[1] BING Qichun YANG Zhaosheng QU Dayi CHEN Xiufeng(School of Automobile and Transportation, Qingdao University of Technology, Qingdao 266520, China School of Transportation, Jilin University, Changchun 130022, China)

机构地区：[1]青岛理工大学汽车与交通学院,青岛266520 [2]吉林大学交通学院,长春130022

出　　处：《北京工业大学学报》2017年第6期935-941,共7页Journal of Beijing University of Technology

基　　金："十二五"国家科技支撑计划资助项目(2014BAG03B03)

摘　　要：为了从原始数据层面保证动态交通数据的质量,针对多检测器异步采样中非等采样率同时采样的情况,首先构建快速路多检测器动态系统,并对多检测器动态系统进行小波变换,提出基于小波和卡尔曼滤波的多尺度交通数据融合方法.最后,采用上海市南北高架快速路实测数据进行实验验证和对比分析.实验结果表明:对于添加噪声强度为2.5%、5.0%、7.5%和10.0%随机噪声的观测数据,该方法的数据融合效果均优于对比方法.In order to guarantee the quality of dynamic traffic data on the original data level, by simultaneous sampling with different sampling rates, the multi-detector dynamic system of urban expressway was constructed and the multi-detector dynamic system was analyzed by using wavelet transform. Then, the multi-scale traffic data fusion method based on wavelet transform and Kalman filter was proposed. Finally, validation and comparative analysis were carried out by using actual data measured from the north-south viaduct in Shanghai. Experiment results indicate that when the stochastic noise intensity is 2.5%, 5.0%, 7.5% and 10.0% respectively, the data fusion effects of the proposed method are superior to that of the compared methods.

关 键 词：城市快速路 数据融合 多尺度 小波变换 卡尔曼滤波 

分 类 号：U491[交通运输工程—交通运输规划与管理]