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Genetic algorithm-based combinatorial parametric optimization for the calibration of microscopic traffic simulation models

Ma, T. / Abdulhai, B.

We introduce GENOSIM, genetic optimizer for traffic micro-simulation models. GENOSIM is developed as a pilot software, employing state of the art combinatorial parametric optimization to automate the tedious task of calibrating traffic microscopic simulation models. The employed global search technique, genetic algorithms, is integrated with a dynamic traffic microscopic simulation model for the City of Toronto, Canada using Paramics microsimulation suite. The output of GENOSIM is the near-optimal values of its car-following, lane changing and dynamic routing parameters. The results obtained are very encouraging.

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Genetic algorithm-based combinatorial parametric optimization for the calibration of microscopic traffic simulation models

Ma, T. / Abdulhai, B.

We introduce GENOSIM, genetic optimizer for traffic micro-simulation models. GENOSIM is developed as a pilot software, employing state of the art combinatorial parametric optimization to automate the tedious task of calibrating traffic microscopic simulation models. The employed global search technique, genetic algorithms, is integrated with a dynamic traffic microscopic simulation model for the City of Toronto, Canada using Paramics microsimulation suite. The output of GENOSIM is the near-optimal values of its car-following, lane changing and dynamic routing parameters. The results obtained are very encouraging.

Genetic algorithm-based combinatorial parametric optimization for the calibration of microscopic traffic simulation models

Ma, T. / Abdulhai, B.

We introduce GENOSIM, genetic optimizer for traffic micro-simulation models. GENOSIM is developed as a pilot software, employing state of the art combinatorial parametric optimization to automate the tedious task of calibrating traffic microscopic simulation models. The employed global search technique, genetic algorithms, is integrated with a dynamic traffic microscopic simulation model for the City of Toronto, Canada using Paramics microsimulation suite. The output of GENOSIM is the near-optimal values of its car-following, lane changing and dynamic routing parameters. The results obtained are very encouraging.

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Title:

Genetic algorithm-based combinatorial parametric optimization for the calibration of microscopic traffic simulation models

Contributors:

Ma, T. (author) / Abdulhai, B. (author)

Published in:

ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585) ; 848-853

Publication date:

2001-01-01

Size:

797139 byte

ISBN:

DOI:

https://doi.org/10.1109/ITSC.2001.948771

Type of media:

Conference paper

Type of material:

Electronic Resource

Language:

English

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