Entry capacity modelling of signalized roundabouts under heterogeneous traffic conditions
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{PATNAIK:2020:TL,
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author = "Ashish Kumar Patnaik and L. Ankit Agarwal and
Mahabir Panda and Prasanta Kumar Bhuyan",
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title = "Entry capacity modelling of signalized roundabouts
under heterogeneous traffic conditions",
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journal = "Transportation Letters",
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volume = "12",
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number = "2",
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pages = "100--112",
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year = "2020",
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ISSN = "1942-7867",
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DOI = "doi:10.1080/19427867.2018.1533160",
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URL = "https://www.sciencedirect.com/science/article/pii/S1942786722001722",
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keywords = "genetic algorithms, genetic programming, Roundabout,
capacity, signalize, regression, PCU, heterogeneous
traffic, sensitivity analysis, ALPS GP",
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abstract = "The primary objectives of this study are to develop
two signalized-based roundabouts entry capacity model
by employing regression-based multiple non-linear
regression model (MNLR) and artificial
intelligence-based age-layered population structure
genetic programming (ALPS GP) model under heterogeneous
traffic conditions. Based on the modified rank index
(MRI) values, the ALPS GP model is found to be most
suitable model under heterogeneous traffic conditions.
However, in a practical point of view, MNLR-based
signalized model is recommended for determining
roundabout entry capacity under heterogeneous traffic
conditions. Sensitivity analysis reports that weaving
length is the prime variable and sharing about 27.72
percent in the MNLR-based signalized roundabout entry
capacity model. These findings will be useful for
traffic planners and designers in the capacity
estimation of signalized roundabouts under
heterogeneous traffic conditions in developing
countries with similar traffic characteristics as
India",
- }
Genetic Programming entries for
Ashish Kumar Patnaik
L Ankit Agarwal
Mahabir Panda
Prasanta Kumar Bhuyan
Citations