As traffic demand is growing rapidly, traffic congestion has become a severe problem everywhere in the world. Accurate prediction of traffic flow is therefore essential for the transport users to make smarter and effective decisions like route guidance, mode of transport, time of travel etc. Short term traffic flow prediction has become one of the important research fields in intelligent transportation system (ITS) and forms crucial base for the traffic management, traffic guidance and control strategy. This work suggests the application of a neuro-fuzzy hybrid system which brings together the complementary capabilities of both neural networks and fuzzy logic for short term traffic flow prediction application. The objective is to improve prediction accuracy. Data from highway of Chennai, India is used for the analysis. The use of hybrid system results in satisfactory improvement in the performance measure.
Short term traffic flow prediction based on neuro-fuzzy hybrid sytem
2016-01-01
343438 byte
Conference paper
Electronic Resource
English
Urban Short-Term Traffic Flow Prediction Based on Neuro-FDT
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