Modeling stream speed in heterogeneous traffic environment using ANN‐lessons learnt
DOI: https://doi.org/10.3846/16484142.2006.9638077Abstract
In order to model traffic stream speed resulting from complex interactions among different vehicle types in a heterogeneous/mixed traffic volume, an Artificial Neural Networks (ANN) approach is exploited. Two different categories of ANN model are attempted based on input vectors used. The performance of both categories of ANN model is evaluated using traditional evaluation framework. In addition, relevant logical test is carried out with both categories of ANN model. It is shown that selection of suitable input vectors and carrying out of relevant logical test are the two essential components for ANN model development process.
First Published Online: 27 Oct 2010
Keywords:
heterogeneous/mixed traffic, stream speed, Artificial Neural Networks (ANN)How to Cite
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Copyright (c) 2006 The Author(s). Published by Vilnius Gediminas Technical University.
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Copyright (c) 2006 The Author(s). Published by Vilnius Gediminas Technical University.
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This work is licensed under a Creative Commons Attribution 4.0 International License.