Review Article
A Review of Traffic Congestion Prediction Using Artificial Intelligence
Table 3
Traffic congestion prediction studies in deep machine learning.
| Methodology | Road type | Data source | Input parameters | Target domain | No. of congestion state levels | Reference |
| Convolutional neural networks | Road network | Probe | Average traffic speed | Speed | 3 | Ma et al. [80] | Average traffic speed | 5 | Sun et al. [45] | Camera | Congestion level | Congestion level | 3 | Chen et al. [68] | Highway corridor | Sensor | Traffic flow | Traffic flow | ā | Zhang et al. [93] | Recurrent neural network | Road section | Probe | Weather data | Congestion time | 5 | Zhao et al. [12] | Congestion time | Arterial road | Online | Congestion level | Congestion level | 3 | Yuan-Yuan et al. [79] | Road network | Camera | Spatial similarity feature | Speed | Lee et al. [69] | Sensor | Speed | Survey | Peak hour | Highway corridor | Sensor | Speed | Congestion level | 4 | Zhang et al. [83] | Travel time | Volume | Road network | Probe | Congestion state | Congestion state | 2 | Ma et al. [85] | Extreme learning machine | Current time | Congestion Index | ā | Ban et al. [19] | Road traffic state cluster | Last congestion index | Road type | Number of adjacent roads |
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