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Short Term Traffic Flow Prediction for a Non Urban Highway Using Artificial Neural Network

Procedia - Social and Behavioral Sciences · 2013 · Vol. 104 · pp. 755–764
Kranti KumarManoranjan ParidaV. K. Katiyar

Abstract

This study applies Artificial Neural Network (ANN) for short term prediction of traffic flow using past traffic data. The model incorporates traffic volume, speed, density, time and day of week as input variables. Speed of each category of vehicles was considered separately as input variables in contrast to previous studies reported in literature which consider average speed of combined traffic flow. Results show that Artificial Neural Network has consistent performance even if time interval for traffic flow prediction was increased from 5 minutes to 15 minutes and produced good results even though speeds of each category of vehicles were considered separately as input variables.

Traffic Prediction and Management TechniquesTraffic control and managementTransportation Planning and OptimizationTraffic flow (computer networking)Artificial neural networkTerm (time)Traffic volumeComputer scienceFlow (mathematics)Volume (thermodynamics)Interval (graph theory)StatisticsArtificial intelligence

Funding

  • Council of Scientific and Industrial Research, India
Citations
280
FWCI
11.41
field-weighted impact
References
30
Percentile
98%
vs. same field & year
Citations per year
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References
SHORT-TERM TRAFFIC FLOW PREDICTION: NEURAL NETWORK APPROACH
Transportation Research Record Journal of the Transportation Research Board · 1994 · 311 citations
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