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Reduction of errors when estimating emissions based on static traffic model outputs
Linköpings Universitet.
Linköpings Universitet.
Swedish National Road and Transport Research Institute, Society, environment and transport, Traffic analysis and logistics.ORCID iD: 0000-0002-0336-6943
2017 (English)In: Transportation Research Procedia, ISSN 2324-9935, E-ISSN 2352-1465, Vol. 22, 440-449 p.Article in journal (Refereed) Published
Abstract [en]

The rapid growth of traffic congestion has led to an increased level of emissions and energy consumption in urban areas. Well designed infrastructure and traffic controllers along with more efficient vehicles and policy measures are required to mitigate congestion and thus reduce transport emissions. In order to evaluate how changes in the traffic system affect energy use and emissions, traffic analysis tools are used together with emission models. In large urban areas emission models mainly rely on aggregated outputs from traffic models, such as the average link speed and flow. Static traffic models are commonly used to generate inputs for emission models, since they can efficiently be applied to larger areas with relatively low computational cost. However, in some cases their underlying assumptions can lead to inaccurate predictions of the traffic conditions and hence to unreliable emission estimates. The aim of this paper is to investigate and quantify the errors that static modeling introduces in emission estimation and subsequently considering the source of those errors, to suggest and evaluate possible solutions. The long analysis periods that are commonly used in static models, as well as the static models' inability to describe dynamic traffic flow phenomena can lead up to 40 % underestimation of the estimated emissions. In order to better estimate the total emissions, we propose the development of a post processing technique based on a quasi-dynamic approach, attempting to capture more of the excess emissions created by the temporal and spatial variations of traffic conditions

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 22, 440-449 p.
Keyword [en]
Forecast, Emission, Fuel consumption, Mathematical model, Traffic flow, Fluctuation (traffic)
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:vti:diva-11884DOI: 10.1016/j.trpro.2017.03.040Scopus ID: 2-s2.0-85019408718OAI: oai:DiVA.org:vti-11884DiVA: diva2:1106751
Conference
19th EURO Working Group on Transportation Meeting, EWGT2016, 5-7 September 2016, Istanbul, Turkey
Available from: 2017-06-08 Created: 2017-06-08 Last updated: 2017-06-08Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf