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	—	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	—	Ban et al. [19]
			Road traffic state cluster
			Last congestion index
			Road type
			Number of adjacent roads