基于多时间尺度的城市轨道交通短时OD估计.docVIP

基于多时间尺度的城市轨道交通短时OD估计 陈志杰 毛保华 柏赟 许奇 张桐 北京交通大学城市交通复杂系统理论与技术教育部重点实验室 X 关注成功！ 加关注后您将方便地在 我的关注中得到本文献的被引频次变化的通知！ 新浪微博 腾讯微博 人人网 开心网 豆瓣网 网易微博 摘????要： 基于状态空间模型构建了城市轨道交通短时OD估计的多模型组合方法, 估计早晚高峰期间15 min内进站客流的去向目的站.组合模型以不同时间尺度下的进站客流分流率为状态变量, 并利用历史数据预估其中通勤客流的分流率, 然后通过交互多模型算法加权融合不同时间尺度下的分流率估计结果.以北京地铁为案例, 研究表明:早高峰期间的15 min分流率估计误差的平均值和最大值分别为16.4%和21.8%, 晚高峰期间分别为22.7%和24.6%, 比既有文献的估计误差减小了约一半.本文的研究成果可为实时的线网客流分布预测提供更准确的输入数据, 以辅助运营管理部门实现客流预警和应急响应. 关键词： 交通工程; 短时OD估计; 多时间尺度; 城市轨道交通; 状态转移; 作者简介：陈志杰 (1989-) , 男, 浙江宁波人, 博士生. 作者简介：毛保华, bhmao@bjtu.edu.cn 收稿日期：2017-06-02 基金：国家自然科学基金 3) Short-term Origin-destination Estimation for Urban Rail Transit Based on Multiple Temporal Scales CHEN Zhi-jie MAO Bao-hua BAI Yun XU Qi ZHANG Tong MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University; Abstract： To estimate the destinations of the entrance passenger flows at urban rail transit stations in each15 minutes at rush hours, based on state-space models, a multi-model composition approach of short-term origin-destination estimation is proposed. Firstly, the split rates of the entrance passenger flows under different temporal scales are used as the state variables for the composition model. Then the split rates of the commuter entrance passenger flows are estimated based on the historical data. Secondly, the results of the estimated split rates under different temporal scales are weightily fused by the interacting multiple model algorithm. The research of the Beijing subway demonstrates that the average and maximum estimation errors of the split rates at morning rush hours are 16.4% and 21.8% respectively. And those of evening rush hours are 22.7% and 24.6% respectively. The result reduces the estimation errors by nearly one half in comparison with those in present literatures. The results of this paper can provide more accurate input data for the realtime prediction of network traffic distribution to assist the