Conference Proceedings

International Conference on Advances in Structural, Civil and Environmental Engineering - SCEE 2013

Traffic Forecasting for King Fahd Causeway: Comparison of Parametric Technique with Artificial Neural Networks

Author(s) : ASHAR AHMED   , UNEB GAZDER

Abstract

Traffic prediction involves forecasting traffic in terms of Annual Average Daily Traffic (AADT), Design Hour Volumes (DHV) and Directional Design Hour Volumes (DDHV). These forecasts are used for a wide variety of purposes from the planning to the design and operational stages of the highway network. The forecasting needs the historical traffic data as well as the systems characteristics, apart from that choice of an appropriate model or technique is also an important consideration. This paper gives an overview of the traffic forecasting process and the models that are used for this purpose with emphasis on the use of Artificial Neural Networks (ANNs) and other modern techniques. ANNs are being compared with the traditional Parametric techniques used in this regard by applying linear regression analysis and ANNs for daily traffic forecasting on King Fahd causeway. It was observed from the estimated error values of both techniques that ANNs have better accuracy than linear regression technique for predicting daily traffic.

Conference Title : International Conference on Advances in Structural, Civil and Environmental Engineering - SCEE 2013
Conference Date(s) : May 04-05, 2013
Place : Hotel Shangri-La, Kuala Lumpur, Malaysia
No fo Author(s) : 2
DOI : 10.15224/978-981-07-6261-2-81
Page(s) : 75 - 79
Electronic ISBN : 978-981-07-6261-2
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