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== Abstract ==
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The knowledge of traffic health status is essential to the general public and urban traffic management. To identify congestion cascades, an important phenomenon of traffic health, we propose a Bus Trajectory based Congestion Identification (BTCI) framework that explores the anomalous traffic health status and structure properties of congestion cascades using bus trajectory data. BTCI consists of two main steps, congested segment extraction and congestion cascades identification. The former constructs path speed models from historical vehicle transitions and design a non-parametric Kernel Density Estimation (KDE) function to derive a measure of congestion score. The latter aggregates congested segments (i.e., those with high congestion scores) into traffic congestion cascades by unifying both attribute coherence and spatio-temporal closeness of congested segments within a cascade. Extensive evaluations on 11.8 million bus trajectory data show that (1) BTCI can effectively identify congestion cascades, (2) the proposed congestion score is effective in extracting congested segments, (3) the proposed unified approach significantly outperforms alternative approaches in terms of extended precision, and (4) the identified congestion cascades are realistic, matching well with the traffic news and highly correlated with vehicle speed bands.
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== Original document ==
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The different versions of the original document can be found in:
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* [https://ink.library.smu.edu.sg/sis_research/3971 https://ink.library.smu.edu.sg/sis_research/3971] under the license cc-by-nc-nd
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* [http://xplorestaging.ieee.org/ielx7/8241556/8257893/08258039.pdf?arnumber=8258039 http://xplorestaging.ieee.org/ielx7/8241556/8257893/08258039.pdf?arnumber=8258039],
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: [http://dx.doi.org/10.1109/bigdata.2017.8258039 http://dx.doi.org/10.1109/bigdata.2017.8258039]
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* [https://dblp.uni-trier.de/db/conf/bigdataconf/bigdataconf2017.html#ChiangLLK17 https://dblp.uni-trier.de/db/conf/bigdataconf/bigdataconf2017.html#ChiangLLK17],
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: [https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=4973&context=sis_research https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=4973&context=sis_research],
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: [https://ink.library.smu.edu.sg/sis_research/3971 https://ink.library.smu.edu.sg/sis_research/3971],
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: [https://pennstate.pure.elsevier.com/en/publications/btci-a-new-framework-for-identifying-congestion-cascades-using-bu https://pennstate.pure.elsevier.com/en/publications/btci-a-new-framework-for-identifying-congestion-cascades-using-bu],
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: [https://core.ac.uk/display/155250029 https://core.ac.uk/display/155250029],
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: [https://academic.microsoft.com/#/detail/2783937577 https://academic.microsoft.com/#/detail/2783937577]
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Published on 01/01/2018

Volume 2018, 2018
DOI: 10.1109/bigdata.2017.8258039
Licence: Other

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