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

Year: 2013

Type: conference-paper

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.

Source: Procedia - Social and Behavioral Sciences

DOI: 10.1016/j.sbspro.2013.11.170

Authors: Kranti Kumar, M. Parida, V.K. Katiyar

Institutions: Vellore Institute of Technology University, Indian Institute of Technology Roorkee

Language: English

Topic: Traffic Prediction and Management Techniques

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

Open Access status: diamond

Funder: Council of Scientific and Industrial Research, India

OpenAlex ID: W2012051283

FWCI: 9.292

Cites: 28

Cited by: 293

Related to: 10