On mining anomalous patterns in road traffic streams

Linsey Xiaolin Pang; Sanjay Chawla; Wei Liu; Yu Zheng

doi:10.1007/978-3-642-25856-5_18

On mining anomalous patterns in road traffic streams

Linsey Xiaolin Pang, Sanjay Chawla, Wei Liu, Yu Zheng

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

75 Scopus citations

Abstract

Large number of taxicabs in major metropolitan cities are now equipped with a GPS device. Since taxis are on the road nearly twenty four hours a day (with drivers changing shifts), they can now act as reliable sensors to monitor the behavior of traffic. In this paper we use GPS data from taxis to monitor the emergence of unexpected behavior in the Beijing metropolitan area. We adapt likelihood ratio tests (LRT) which have previously been mostly used in epidemiological studies to describe traffic patterns. To the best of our knowledge the use of LRT in traffic domain is not only novel but results in very accurate and rapid detection of anomalous behavior.

Original language	English
Title of host publication	Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Proceedings
Pages	237-251
Number of pages	15
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-25856-5_18
State	Published - 2011
Externally published	Yes
Event	7th International Conference on Advanced Data Mining and Applications, ADMA 2011 - Beijing, China Duration: Dec 17 2011 → Dec 19 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	7121 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	7th International Conference on Advanced Data Mining and Applications, ADMA 2011
Country/Territory	China
City	Beijing
Period	12/17/11 → 12/19/11

Keywords

Spatio-temporal outlier
emerging
persistent
upper-bounding

Access to Document

10.1007/978-3-642-25856-5_18

Cite this

Pang, L. X., Chawla, S., Liu, W., & Zheng, Y. (2011). On mining anomalous patterns in road traffic streams. In Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Proceedings (PART 2 ed., pp. 237-251). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7121 LNAI, No. PART 2). https://doi.org/10.1007/978-3-642-25856-5_18

Pang, Linsey Xiaolin ; Chawla, Sanjay ; Liu, Wei et al. / On mining anomalous patterns in road traffic streams. Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Proceedings. PART 2. ed. 2011. pp. 237-251 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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abstract = "Large number of taxicabs in major metropolitan cities are now equipped with a GPS device. Since taxis are on the road nearly twenty four hours a day (with drivers changing shifts), they can now act as reliable sensors to monitor the behavior of traffic. In this paper we use GPS data from taxis to monitor the emergence of unexpected behavior in the Beijing metropolitan area. We adapt likelihood ratio tests (LRT) which have previously been mostly used in epidemiological studies to describe traffic patterns. To the best of our knowledge the use of LRT in traffic domain is not only novel but results in very accurate and rapid detection of anomalous behavior.",

keywords = "Spatio-temporal outlier, emerging, persistent, upper-bounding",

author = "Pang, {Linsey Xiaolin} and Sanjay Chawla and Wei Liu and Yu Zheng",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Proceedings",

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Pang, LX, Chawla, S, Liu, W & Zheng, Y 2011, On mining anomalous patterns in road traffic streams. in Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 7121 LNAI, pp. 237-251, 7th International Conference on Advanced Data Mining and Applications, ADMA 2011, Beijing, China, 12/17/11. https://doi.org/10.1007/978-3-642-25856-5_18

On mining anomalous patterns in road traffic streams. / Pang, Linsey Xiaolin; Chawla, Sanjay; Liu, Wei et al.
Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Proceedings. PART 2. ed. 2011. p. 237-251 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7121 LNAI, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Pang LX, Chawla S, Liu W, Zheng Y. On mining anomalous patterns in road traffic streams. In Advanced Data Mining and Applications - 7th International Conference, ADMA 2011, Proceedings. PART 2 ed. 2011. p. 237-251. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-25856-5_18

On mining anomalous patterns in road traffic streams

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Keywords

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