INTEGRATION Framework for Modeling Eco-routing Strategies: Logic and Preliminary Results
The paper presents the INTEGRATION microscopic traffic assignment and simulation framework for modeling eco-routing strategies. Two eco-routing algorithms are developed: one based on vehicle sub-populations (ECO-Subpopulation Feedback Assignment or ECO-SFA) and another based on individual agents (EC...
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doaj-c520e43fe3ca415896ffb98e7fab40382020-11-25T01:00:20ZengElsevierInternational Journal of Transportation Science and Technology2046-04302012-09-011325927410.1260/2046-0430.1.3.259INTEGRATION Framework for Modeling Eco-routing Strategies: Logic and Preliminary ResultsHesham A. RakhaThe paper presents the INTEGRATION microscopic traffic assignment and simulation framework for modeling eco-routing strategies. Two eco-routing algorithms are developed: one based on vehicle sub-populations (ECO-Subpopulation Feedback Assignment or ECO-SFA) and another based on individual agents (ECO-Agent Feedback Assignment or ECO-AFA). Both approaches initially assign vehicles based on fuel consumption levels for travel at the facility free-flow speed. Subsequently, fuel consumption estimates are refined based on experiences of other vehicles within the same class. The proposed framework is intended to evaluate the network-wide impacts of eco-routing strategies. This stochastic, multi-class, dynamic traffic assignment framework was demonstrated to work for two scenarios. Savings in fuel consumption levels in the range of 15 percent were observed and potential implementation challenges were identified.http://www.sciencedirect.com/science/article/pii/S2046043016301629 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hesham A. Rakha |
spellingShingle |
Hesham A. Rakha INTEGRATION Framework for Modeling Eco-routing Strategies: Logic and Preliminary Results International Journal of Transportation Science and Technology |
author_facet |
Hesham A. Rakha |
author_sort |
Hesham A. Rakha |
title |
INTEGRATION Framework for Modeling Eco-routing Strategies: Logic and Preliminary Results |
title_short |
INTEGRATION Framework for Modeling Eco-routing Strategies: Logic and Preliminary Results |
title_full |
INTEGRATION Framework for Modeling Eco-routing Strategies: Logic and Preliminary Results |
title_fullStr |
INTEGRATION Framework for Modeling Eco-routing Strategies: Logic and Preliminary Results |
title_full_unstemmed |
INTEGRATION Framework for Modeling Eco-routing Strategies: Logic and Preliminary Results |
title_sort |
integration framework for modeling eco-routing strategies: logic and preliminary results |
publisher |
Elsevier |
series |
International Journal of Transportation Science and Technology |
issn |
2046-0430 |
publishDate |
2012-09-01 |
description |
The paper presents the INTEGRATION microscopic traffic assignment and simulation framework for modeling eco-routing strategies. Two eco-routing algorithms are developed: one based on vehicle sub-populations (ECO-Subpopulation Feedback Assignment or ECO-SFA) and another based on individual agents (ECO-Agent Feedback Assignment or ECO-AFA). Both approaches initially assign vehicles based on fuel consumption levels for travel at the facility free-flow speed. Subsequently, fuel consumption estimates are refined based on experiences of other vehicles within the same class. The proposed framework is intended to evaluate the network-wide impacts of eco-routing strategies. This stochastic, multi-class, dynamic traffic assignment framework was demonstrated to work for two scenarios. Savings in fuel consumption levels in the range of 15 percent were observed and potential implementation challenges were identified. |
url |
http://www.sciencedirect.com/science/article/pii/S2046043016301629 |
work_keys_str_mv |
AT heshamarakha integrationframeworkformodelingecoroutingstrategieslogicandpreliminaryresults |
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