交通信息与安全Issue(3)：27-31,5.DOI:10.3963/j.issn1674-4861.2014.03.006
基于多源数据的城市道路网络行程时间预测模型
Development of A Travel Time Prediction Model for Urban Road Network using Multi-source Data
摘要
Abstract
In view of the deficiencies of traditional travel time prediction models developed based on Kalman filtering technique and single data source ,the multi-source data are used to improve such models and the prediction accuracy of travel time .Floating cars and loop detectors are common ways for collecting travel time ,and the two are complementary to each other in many ways .Therefore ,the real-time traffic data from the two sources are used as the inputs of the pre-diction model .Through Kalman filtering ,flow ,occupancy and travel time are used as inputs of the proposed travel time prediction model .Finally ,the model is verified through a simulation from Vissim .The simulation results show that the average absolute relative error of the estimated travel time based on the model developed based on the multi-source data is 5 .45% ,which is 14 .4% lower than those estimated based on the loop detector data only and 7 .5% lower than those esti-mated based on the floating car data alone .关键词
多源数据/卡尔曼滤波/行程时间预测/城市道路网络/Vissim仿真Key words
multi-source data/Kalman filtering/travel time prediction/urban road network/Vissim simulation分类
交通工程引用本文复制引用
江周,张存保,许志达,严凤祥,丁国飞..基于多源数据的城市道路网络行程时间预测模型[J].交通信息与安全,2014,(3):27-31,5.基金项目
国家自然科学基金项目（批准号51108361）、浙江省交通运输厅科技计划项目（批准号2012T21）资助 （）
