Initial methodology for forecasting vehicle modes of activity as input to modal emissions models

Simon P. Washington, John D. Leonard, Craig A Roberts

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Researchers at Georgia Tech, UC Davis, San Jose University, and the California Polytechnic University in San Luis Obispo developed a method to forecast modes of vehicles activity. A general framework used to link forecasted vehicle activity with forecasted emissions of CO, NOX and HCC from light-duty motor vehicles is presented. Algorithms are then developed to estimate modal activity on freeways using a statistical modeling procedure called hierarchical tree-based regression (HTBR). To generate traffic data for the statistical analysis, a full factorial data set containing 1600 observations is developed using a modification of the FRESIM simulation modeling software.

Original languageEnglish (US)
Title of host publicationProceedings of the Air & Waste Management Association's Annual Meeting & Exhibition
Editors Anon
PublisherAir & Waste Management Assoc
StatePublished - 1997
Externally publishedYes
EventProceedings of the 1997 Air & Waste Management Association's 90th Annual Meeting & Exhibition - Toronto, Can
Duration: Jun 8 1997Jun 13 1997

Other

OtherProceedings of the 1997 Air & Waste Management Association's 90th Annual Meeting & Exhibition
CityToronto, Can
Period6/8/976/13/97

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Washington, S. P., Leonard, J. D., & Roberts, C. A. (1997). Initial methodology for forecasting vehicle modes of activity as input to modal emissions models. In Anon (Ed.), Proceedings of the Air & Waste Management Association's Annual Meeting & Exhibition Air & Waste Management Assoc.