Effects of using average annual daily traffic (AADT) with exogenous factors to predict daily traffic

Nedal T. Ratrout*, Uneb Gazder, El Sayed M. El-Alfy

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

Traffic demand can be highly correlated to the exogenous factors that exist outside the road system under study. Factors like day of week, presence of vacation or salary disbursement or economic parameters are readily available and may affect traffic flow between two countries. Collection of traffic data on a consistent basis is a cumbersome process in terms of time and resources. Considering these two factors in mind, this paper investigated the feasibility of using exogenous factors with Average Annual Daily Traffic (AADT). It was found that inclusion of AADT for traffic prediction is beneficial and further analysis will be done in the future with detailed traffic data.

Original languageEnglish
Pages (from-to)325-330
Number of pages6
JournalProcedia Computer Science
Volume32
DOIs
StatePublished - 2014

Bibliographical note

Funding Information:
This study is funded by Deanship of Research, King Fa hd University of Petroleum and Minerals, under the project entitled “Mode Choice Modeling and Modal Tr affic Forecasting over King Fahd Causeway using Computational Intelligence Techniques” (Referenced: IN121065). The authors also acknowledge the support of Prof. Hashim Al-Madani (University of Ba hrain) for providing data for this study.

Keywords

  • Average Annual Daily Traffic
  • Exogenous Factors
  • Traffic Forecasting

ASJC Scopus subject areas

  • General Computer Science

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