Measuring traffic

被引：58

作者：

Bickel, Peter J. ^{[1
]}

Chen, Chao ^{[2
]}

Kwon, Jaimyoung ^{[3
]}

Rice, John ^{[1
]}

van Zwet, Erik ^{[4
]}

Varaiya, Pravin ^{[5
]}

机构：

[1] Univ Calif Berkeley, Dept Stat, Berkeley, CA 94720 USA

[2] TFS Capital, W Chester, PA 19380 USA

[3] Calif State Univ Hayward, Dept Stat, Hayward, CA 94542 USA

[4] Leiden Univ, Inst Math, NL-2300 RA Leiden, Netherlands

[5] Univ Calif Berkeley, Dept Elect Engn & Comp Sci, Berkeley, CA 94720 USA

来源：

STATISTICAL SCIENCE | 2007年 / 22卷 / 04期

关键词：

ATIS; freeway loop data; speed estimation; malfunction detection;

D O I：

10.1214/07-STS238

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 [统计学]; 070103 [概率论与数理统计]; 0714 [统计学];

摘要：

A traffic performance measurement system, PeMS, currently functions as a statewide repository for traffic data gathered by thousands of automatic sensors. It has integrated data collection, processing and communications infrastructure with data storage and analytical tools. In this paper, we discuss statistical issues that have emerged as we attempt to process a data stream of 2 GB per day of wildly varying quality. In particular, we focus on detecting sensor malfunction, imputation of missing or bad data, estimation of velocity and forecasting of travel times on freeway networks.

引用

页码：581 / 597

页数：17

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