How to Identify Patterns of Citywide Dynamic Traffic at a Low Cost? An In-Depth Neural Network Approach with Digital Maps
The identification and analysis of the spatiotemporal dynamic traffic patterns in citywide road networks constitute a crucial process for complex traffic management and control. However, city-scale and synchronal traffic data pose challenges for such kind of quantification, especially during peak ho...
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Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
Wiley
2021-01-01
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Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2021/6648116 |
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