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.
作者
邴其春
杨兆升
曲大义
陈秀锋
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)
出处
《北京工业大学学报》
CAS
CSCD
北大核心
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)
