NDLI: Mining the spatio-temporal pattern using matrix factorisation: a case study of traffic flow

Content Provider	IET Digital Library
Author	Xu, Chenyang Xu, Changqing Truong, Trieu Kien
Abstract	Realising the spatio-temporal evolutionary pattern of urban traffic can give advice about making personal trip route planning and improving road construction. A novel pattern-discovering model is presented to identify the traffic regularity and characteristics from spatial and temporal dimensions. To unveil this new method, there are two main parts as follows: first, by employing the constrained projected gradient of the non-negative matrix factorisation algorithm, the original traffic data matrix is decomposed into the feature matrix and the weight matrix. Necessary constraints are newly added so that the resulting matrices are ensured to make practical sense for reflecting the traffic spatio-temporal regular pattern. Then, the self-organising maps network is further used to cluster the factorisation error into several classes representing the disparate traffic pattern of each time. In addition, the experiment is conducted on real historical data to verify the performance of the algorithm. The global urban traffic flow for a week is summarised through a set of basic patterns with related weight distribution. The well-visualised result demonstrates that the authors method can achieve significant improvement in terms of computational efficiency and accuracy when compared with other widely-used methods.
Starting Page	1328
Ending Page	1337
Page Count	10
ISSN	1751956X
Volume Number	14
e-ISSN	17519578
Issue Number	Issue 10, Oct (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-its/14/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-its.2019.0705
Journal	IET Intelligent Transport Systems
Publisher Date	2020-08-03
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra Basic Pattern Communication Network Design, Planning And Routing Computer Vision And Image Processing Technique Constrained Projected Gradient Data Handling Technique Data Mining Disparate Traffic Pattern Factorisation Error Feature Matrix Global Urban Traffic Flow Knowledge Engineering Technique Matrix Algebra Matrix Decomposition Nonnegative Matrix Factorisation Algorithm Novel Pattern-discovering Model Optimisation Technique Original Traffic Data Matrix Personal Trip Route Road Construction Road Traffic Self Organising Feature Maps Spatial Dimensions Spatio-temporal Evolutionary Pattern Spatio-temporal Pattern Spatiotemporal Phenomena Statistics Telecommunication Network Routing Telecommunication Traffic Temporal Dimensions Traffic Engineering Computing Traffic Regularity Traffic Spatio-temporal Regular Pattern Weight Matrix
Content Type	Text
Resource Type	Article
Subject	Law Transportation Environmental Science Mechanical Engineering

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