[1]陆振波,夏井新,焦恬恬,等.城市道路交通流监测数据最优汇集时间间隔分析[J].东南大学学报(自然科学版),2012,42(5):1000-1005.[doi:10.3969/j.issn.1001-0505.2012.05.036]
 Lu Zhenbo,Xia Jingxin,Jiao Tiantian,et al.Analysis of optimal temporal aggregation interval of traffic flow data for urban road traffic monitoring[J].Journal of Southeast University (Natural Science Edition),2012,42(5):1000-1005.[doi:10.3969/j.issn.1001-0505.2012.05.036]
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城市道路交通流监测数据最优汇集时间间隔分析()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
42
期数:
2012年第5期
页码:
1000-1005
栏目:
交通运输工程
出版日期:
2012-09-20

文章信息/Info

Title:
Analysis of optimal temporal aggregation interval of traffic flow data for urban road traffic monitoring
作者:
陆振波 夏井新 焦恬恬 时幸飞 黄卫
东南大学智能运输系统研究中心,南京 210096
Author(s):
Lu Zhenbo Xia Jingxin Jiao Tiantian Shi Xingfei Huang Wei
Intelligent Transportation System Center, Southeast University, Nanjing 210096, China
关键词:
交通流监测 最优汇集时间间隔 交叉验证均方差 t检验
Keywords:
traffic flow monitoring optimal temporal aggregation interval cross-validated mean-square error t-test
分类号:
U491
DOI:
10.3969/j.issn.1001-0505.2012.05.036
摘要:
针对传统的交叉验证均方差模型在确定交通流监测数据最优汇集时间间隔研究方面存在的不足,以交通流量、时间平均速度、占有率等3个交通流基本参数来表征城市道路交通流运行状态.在传统的交通状态交叉验证均方差估计方法的基础上,提出了一种改进的基于交通状态矢量的交叉验证均方差模型,以估计不同汇集时间间隔时交通流监测数据的波动性.然后,构建了基于交通状态矢量的均差值假设检验,并采用t检验方法寻找交叉验证均方差值变化的拐点,以确定交通流监测数据的最优汇集时间间隔.以昆山市城市道路车辆检测器实际采集的交通流数据为例,对不同等级城市道路交通流监测数据的最优汇集时间间隔进行了量化分析.结果表明,在实际应用中,城市道路交通流监测数据的最优汇集时间间隔可以选取为5 min.
Abstract:
To overcome the shortcomings of the traditional cross-validated mean-square error model in determining the optimal temporal aggregation interval for traffic flow monitoring data, three fundamental traffic flow parameters, traffic volume, time-mean speed, and occupancy, were used to represent traffic flow operating states for urban road. Based on the traditional model for estimating the cross-validated mean-square error of traffic state, an improved cross-validated mean-square error model for traffic state vector was proposed to estimate the fluctuations of traffic flow monitoring data at different temporal aggregation intervals. Then, a hypothesis test was established for the traffic state vector mean difference, and the t-test method was applied to find the inflection point of the changes in the cross-validated mean-square errors to determine the optimal temporal aggregation interval for traffic monitoring data. Taking the real traffic flow data collected by vehicle detectors on the urban roads of Kunshan City as an example, the optimal temporal aggregation intervals of traffic flow monitoring data for different types of urban roads were quantitatively analyzed. The results show that in practical applications, an optimal temporal aggregation interval of 5 min can be selected for the traffic flow monitoring data for urban roads.

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备注/Memo

备注/Memo:
作者简介: 陆振波(1975—),男,博士,讲师; 夏井新(联系人),男,博士,副教授,jingxinxia@yahoo.com.cn.
基金项目: 国家自然科学基金资助项目(51108079).
引文格式: 陆振波,夏井新,焦恬恬,等.城市道路交通流监测数据最优汇集时间间隔分析[J].东南大学学报:自然科学版,2012,42(5):1000-1005. [doi:10.3969/j.issn.1001-0505.2012.05.036]
更新日期/Last Update: 2012-09-20