Genetic algorithm based microscale vehicle emissions modelling

Zhu, Sicong, Tey, LiSian and Ferreira, Luis (2015) Genetic algorithm based microscale vehicle emissions modelling. Mathematical Problems in Engineering, 2015 . doi:10.1155/2015/178490

Author Zhu, Sicong
Tey, LiSian
Ferreira, Luis
Title Genetic algorithm based microscale vehicle emissions modelling
Journal name Mathematical Problems in Engineering   Check publisher's open access policy
ISSN 1024-123X
Publication date 2015
Sub-type Article (original research)
DOI 10.1155/2015/178490
Open Access Status DOI
Volume 2015
Total pages 9
Place of publication New York, NY, United States
Publisher Hindawi Publishing Corporation
Collection year 2016
Language eng
Formatted abstract
There is a need to match emission estimations accuracy with the outputs of transport models. The overall error rate in long-term traffic forecasts resulting from strategic transport models is likely to be significant. Microsimulation models, whilst high-resolution in nature, may have similar measurement errors if they use the outputs of strategic models to obtain traffic demand predictions. At the microlevel, this paper discusses the limitations of existing emissions estimation approaches. Emission models for predicting emission pollutants other than CO2 are proposed. A genetic algorithm approach is adopted to select the predicting variables for the black box model. The approach is capable of solving combinatorial optimization problems. Overall, the emission prediction results reveal that the proposed new models outperform conventional equations in terms of accuracy and robustness.
Keyword Fuel Consumption
Traffic Emission
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Civil Engineering Publications
Official 2016 Collection
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