Short Term Traffic Flow Prediction with Neighbor Selecting Gated Recurrent Unit

Chan, Yin-Hei, Lui, Andrew Kwok-Fai and Ng, Sin-Chun (2022) Short Term Traffic Flow Prediction with Neighbor Selecting Gated Recurrent Unit. In: 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Melbourne, Australia.

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Traffic flow prediction is an important component of a modern intelligent transport system. Building an effective model for short term traffic flow prediction model is challenging. Traffic is spatial temporal in nature. A traffic flow prediction model should consider an appropriate scope of neighbourhood of traffic. To address the needs of a dynamic scope of neighbourhood. We introduce a novel gated recurrent unit variant call Neighbor Selecting Gated Recurrent Unit(NSGRU). NSGRU feature a learn-able spatial kernel with distance based K-nearest neighbor trimming scheme. Embedded external traffic knowledge are used to aid with the learning of spatial kernel. The NSGRU was evaluated with a quantized real world dataset and observed consistent improvement over baseline models.

Item Type: Conference or Workshop Item (Paper)
Keywords: Traffic flow prediction, Intelligent transport system, Knowledge engineering, Visualization, Roads, Predictive models, Logic gates, Kernel, Conferences
Faculty: Faculty of Science & Engineering
SWORD Depositor: Symplectic User
Depositing User: Symplectic User
Date Deposited: 09 Jun 2022 10:52
Last Modified: 09 Jun 2022 10:52

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