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Assessment of Traffic Environment using Fine-tuned Dynamic Vehicle Emission Models
Wuhan University of Technology.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Traffic Research, CTR.
Wuhan University of Technology.
2010 (English)In: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, 2010, 1237-1242 p.Conference paper, Published paper (Refereed)
Abstract [en]

In order to assess environmental impacts of local traffic flow, a two-stage parameter tuning approach is proposed for recalibration of the Comprehensive Modal Emission Model (CMEM) using on-road emission measurements collected in Chinese cities. Based on the procedure comprising of grid search and nonlinear simplex optimization, the fuel- and emission-related parameters in the model are estimated to minimize the Mean Square Error (MSE) between model outputs and real measurements. In addition, a regression-based emission model is calibrated using the same data samples to compare performance. It is shown from the numerical results that the tuning process is able of improving the model prediction accuracy, especially concerning the CO emission, when comparing with the original CMEM model and the regression-based model. In addition, the emission models are, after the tuning process, applied together with a traffic simulation model to evaluate dynamic environmental effects of traffic in a case study.

Place, publisher, year, edition, pages
2010. 1237-1242 p.
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:kth:diva-115913DOI: 10.1109/ITSC.2010.5625195Scopus ID: 2-s2.0-78650435895OAI: oai:DiVA.org:kth-115913DiVA: diva2:588494
Conference
13th International IEEE Conference on Intelligent Transportation Systems, ITSC 2010
Note

TSC import 1254 2013-01-15 QC 20130528

Available from: 2013-01-15 Created: 2013-01-15 Last updated: 2013-05-28Bibliographically approved

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  • Other locale
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