Outlier trajectory detection: a trajectory analytics based approach

Zhongjian Lv, Jiajie Xu*, Pengpeng Zhao, Guanfeng Liu, Lei Zhao, Xiaofang Zhou

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

12 Citations (Scopus)

Abstract

Trajectories obtained from GPS-enabled devices give us great opportunities to mine out hidden knowledge about the urban mobility, traffic dynamics and human behaviors. In this paper, we aim to understand historical trajectory data for discovering outlier trajectories of taxis. An outlier trajectory is a trajectory grossly different from others, meaning there are few or even no trajectories following a similar route in a dataset. To identify outlier trajectories, we first present a prefix tree based algorithm called PTS, which traverses the search space on-the-fly to calculate the number of trajectories following similar routes for outlier detection. Then we propose two trajectory clustering based approaches PBOTD and DBOTD to cluster trajectories and extract representative routes in different ways. Outlier detection is carried out on the representatives directly, and the accuracy can be guaranteed by some proven error bounds. The evaluation of the proposed methods on a real dataset of taxi trajectories verifies the high efficiency and accuracy of the DBOTD algorithm.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications
Subtitle of host publication22nd International Conference, DASFAA 2017, Proceedings, Part I
EditorsSelçuk Candan, Lei Chen, Torben Bach Pedersen, Lijun Chang, Wen Hua
PublisherSpringer, Springer Nature
Pages231-246
Number of pages16
ISBN (Electronic)9783319557533
ISBN (Print)9783319557526
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event22nd International Conference on Database Systems for Advanced Applications (DASFAA) - Suzhou
Duration: 27 Mar 201730 Mar 2017

Publication series

NameLecture Notes in Computer Science
PublisherSPRINGER INTERNATIONAL PUBLISHING AG
Volume10177
ISSN (Print)0302-9743

Conference

Conference22nd International Conference on Database Systems for Advanced Applications (DASFAA)
CitySuzhou
Period27/03/1730/03/17

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