A Review of Traffic Congestion Prediction Using Artificial Intelligence

Table 2

Traffic congestion prediction studies in shallow machine learning.

Methodology	Road type	Data source	Input parameters	Target domain	No. of congestion state levels	Reference
Artificial neural network	Road network	Sensor	Occupancy	Congestion factor	3	Xu et al. [31]
		Simulation	Density
	Highway corridor	Sensor	Distance	Speed	2	Nadeem and Fowdur [11]
			Speed
		Simulation	Speed	Traffic congestion state	2	Ito and Kaneyasu [60]
			Throttle opening
			Steering input angle
Regression model	Highway corridor	Sensor	Temperature	Traffic congestion score	—	Jiwan et al. [27]
			Humidity
			Rainfall
			Traffic speed
			Time
	Arterial road	Camera	Volume	Congestion Index	4	Jain et al. [33]
	Subarterial road		Speed
Decision tree	Ring road	Probe	Average speed	Traffic predictability	—	Wang et al. [9]
	Road network		Speed	Moran index	5	Chen et al. [16]
			Trajectory
Support vector machine	Highway corridor	Sensor	Speed	Travel speed	—	Tseng et al. [13]
			Density
			Traffic volume difference
			Rainfall volume