A Comparative Study Of Road Traffic Forecasting Models
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Date
2022-01-24
Journal Title
Journal ISSN
Volume Title
Publisher
University of Eloued جامعة الوادي
Abstract
In the context of Intelligent Transport Systems (ITS), the behaviour of
road traffic has been the subject of many theoretical and experimental researches.
In the last decade, road prediction is placed as the first line of
research in this field. The problem has been solved with a variety of models
to assist the traffic control, this includes, improving the efficiency of transport,
guidance in the road, and smart coordination signals. This paper tries
to synthesize the carried out, on three main approaches, namely based on
statistical methods, time series and deep learning.A comparatives synthesis
in terms quantitative and qualitative index of is provided in order to evaluate
the performance and potential of the three forecasting approaches.
Description
Forum Intervention of Artificial Intelligence and Its Applications. Faculty of Exat science. University of Eloued
Keywords
Intelligent Transportation System, Traffic Forecasting, Artificial Neural Network, Deep Learning
Citation
Benabdallah Benarmas, Redouane, Beghdad, Kadda. A Comparative Study Of Road Traffic Forecasting Models. Forum of Artificial Intelligence and Its Applications. 24-26 Jan 2022. Faculty of Exat science. University of Eloued. [visited in ../../….]. available from [copy the link here]