同济大学学报（自然科学版）2013，Vol.41Issue(1)：60-65,6.DOI:10.3969/j.issn.0253-374x.2013.01.010
面向行程时间预测准确度评价的数据融合方法
Data Fusion Method for Accuracy Evaluation of Travel Time Forecast
摘要
Abstract
A BP neural network model was brought forward, which was composed by the initial data generated module, the BP network-based data fusion module and the result analysis module. Four variables such as link average density, traffic volume, link average travel time based on floating car data (FCD) and floating car sampling size were taken as input variables. Link average density and traffic volume could be obtained by the data of loop detectors, while link average travel time and floating car sampling size could be acquired with FCD. Then, the reasons to choose those four variables were given with the support of a statistical analysis. At last, an arterial road in Hangzhou was chosen as an object link, 406 groups of data were utilized to verify the model. The results show that the mean absolute error (MAE) of the proposed model is only 4.86%.关键词
行程时间估计值/准确度评价/BP神经网络/浮动车数据/线圈数据Key words
estimated travel time/ accuracy evaluation/ BP neural network/ floating car data(FCD)/ loop detector data分类
通用工业技术引用本文复制引用
李慧兵,杨晓光..面向行程时间预测准确度评价的数据融合方法[J].同济大学学报（自然科学版）,2013,41(1):60-65,6.基金项目
国家"八六三"高技术研究发展计划(SS2012AA112306) （SS2012AA112306）
