STLP-OD: Spatial and Temporal Label Propagation for Traffic Outlier Detection
Type
ArticleKAUST Department
Computer ScienceComputer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Date
2019Permanent link to this record
http://hdl.handle.net/10754/655896
Metadata
Show full item recordAbstract
This paper focuses on the detection of non-recurrent traffic anomaly caused by unexpected or transient incidents, such as traffic accidents, celebrations, and disasters. Comparing to existing approaches, it considers the spatial and temporal propagation of traffic anomalies from one road to other neighbor roads by proposing an STLP-OD framework. The experimental results on a real data set show that the proposed approach can improve the accuracy of traffic outlier detection baselines significantly.Citation
Pu, J., Wang, Y., Liu, X., & Zhang, X. (2019). STLP-OD: Spatial and Temporal Label Propagation for Traffic Outlier Detection. IEEE Access, 7, 63036–63044. doi:10.1109/access.2019.2916853Sponsors
This work was supported in part by the National Key Research and Development Program of China under Grant 2017YFB1002000, Science Technology and Innovation Commission of Shenzhen Municipality JCYJ20180307123659504, and the State Key Laboratory of Software Development Environment.Journal
IEEE AccessAdditional Links
https://ieeexplore.ieee.org/document/8715411/https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8715411
ae974a485f413a2113503eed53cd6c53
10.1109/ACCESS.2019.2916853