2018 |
Volume 2 |
Issue Issue 1
Short Term Traffic Flow Prediction Methodologies: A Review
1.
Pregya Poonia
– Research Scholar, Dept. Cse, Mody University Of Science And Tech., Lakshmangarh, Rajasthan, India.
2.
V K Jain
– Research Scholar, Dept. Cse, Mody University Of Science And Tech., Lakshmangarh, Rajasthan, India.
3.
Anil Kumar
– Research Scholar, Dept. Cse, Mody University Of Science And Tech., Lakshmangarh, Rajasthan, India.
Received
04-Jul-2018
|
Accepted
-
|
Published
04-Jul-2018
|
Abstract
Successful traffic speed forecasting is an intact component for traffic management agencies. It has great grandness for benefit of road users. Intelligent traffic management system provides time based traffic flow information, so that travellers can reach their destination at an estimated time. In previous few years a series of traffic speed prediction applications have been formulated, in which most of the approaches are relied on short-term speed prediction which includes some traditional models and machine learning techniques. The traffic flow has greatly increased due to the current system and existing methods are still unsatisfying. This composition examined few of the current short-term traffic speed methods.
Keywords Machine Learning, Speed Prediction Methods, Deep Learning.
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