[1]聂庆慧,夏井新,张韦华.基于多源ITS数据的行程时间预测体系框架及核心技术[J].东南大学学报(自然科学版),2011,41(1):199-204.[doi:10.3969/j.issn.1001-0505.2011.01.039]
 Nie Qinghui,Xia Jingxin,Zhang Weihua.Framework and key technologies for travel time prediction based on multiple ITS data sources[J].Journal of Southeast University (Natural Science Edition),2011,41(1):199-204.[doi:10.3969/j.issn.1001-0505.2011.01.039]
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基于多源ITS数据的行程时间预测体系框架及核心技术()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
41
期数:
2011年第1期
页码:
199-204
栏目:
交通运输工程
出版日期:
2011-01-20

文章信息/Info

Title:
Framework and key technologies for travel time prediction based on multiple ITS data sources
作者:
聂庆慧夏井新张韦华
(东南大学教育部智能运输系统工程研究中心,南京 210096)
Author(s):
Nie QinghuiXia JingxinZhang Weihua
(Intelligent Transportation System Institute, Southeast University, Nanjing 210096, China)
关键词:
行程时间体系框架预测数据融合可靠性分析
Keywords:
travel time framework prediction data fusion reliability analysis
分类号:
U491
DOI:
10.3969/j.issn.1001-0505.2011.01.039
摘要:
针对当前城市道路行程时间预测系统性不强等问题,构建基于多源数据的行程时间预测体系框架,阐述预测过程涉及的关键技术.框架的构建以固定式和移动式2类采集方式获得的交通数据为出发点,将预测过程划分为估计和预测两个阶段.提出固定式采集方式获取的速度数据用于行程时间的间接估计和预测的关键技术为空间平均速度的估计; 移动式采集方式获得的行程时间数据用于行程时间的直接估计和预测的关键技术为浮动车最优样本量的确定.考虑单一数据源估计和预测精度不高,提出对2类数据源的估计和预测结果进行数据融合,以提高估计和预测的精度,同时引入GARCH模型来分析预测结果的可靠性,以提高预测结果的可信度.
Abstract:
Aiming at the weakly systematicness in existing travel time prediction studies of urban roadway, a framework of travel time prediction is established, and the involved key techniques are presented. Based on the two types of traffic data sources collected from fixed-location and mobile modes, the prediction procedure is divided into two phases, the estimation phase and the prediction phase. The key technologies, proposed in this paper, of estimating and predicting travel time indirectly by speed data collected from fixed-location mode and directly by travel time data collected from mobile mode are average space-speed estimation and floating car sample size determination. Considering low accuracy of estimation and prediction from single data source, a data fusion technique is presented to improve the accuracy by fusing the estimated or predicted travel time from two types of data sources. Meanwhile, the GARCH model is introduced to guarantee the reliability of travel time prediction.

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备注/Memo

备注/Memo:
作者简介:聂庆慧(1986—),女,硕士生;夏井新(联系人),男,博士,副教授,jingxinxia@yahoo.com.cn.
科研项目:交通综合信息平台建设方案研究资助项目(D101106049710006)、北京市科委2010交通重点资助项目.
引文格式: 聂庆慧,夏井新,张韦华.基于多源ITS数据的行程时间预测体系框架及核心技术[J].东南大学学报:自然科学版,2011,41(1):199-204.[doi:10.3969/j.issn.1001-0505.2011.01.039]
更新日期/Last Update: 2011-01-20