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

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

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

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

Civil Engineering, Construction Management, and Environmental Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter

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 language	English (US)
Title of host publication	Proceedings of the Air & Waste Management Association's Annual Meeting & Exhibition
Editors	Anon
Publisher	Air & Waste Management Assoc
State	Published - 1997
Event	Proceedings of the 1997 Air & Waste Management Association's 90th Annual Meeting & Exhibition - Toronto, Can Duration: Jun 8 1997 → Jun 13 1997

Publication series

Name	Proceedings of the Air & Waste Management Association's Annual Meeting & Exhibition

Other

Other	Proceedings of the 1997 Air & Waste Management Association's 90th Annual Meeting & Exhibition
City	Toronto, Can
Period	6/8/97 → 6/13/97

ASJC Scopus subject areas

General Engineering

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 (Proceedings of the Air & Waste Management Association's Annual Meeting & Exhibition). Air & Waste Management Assoc.

Initial methodology for forecasting vehicle modes of activity as input to modal emissions models. / Washington, Simon P.; Leonard, John D.; Roberts, Craig A.
Proceedings of the Air & Waste Management Association's Annual Meeting & Exhibition. ed. / Anon. Air & Waste Management Assoc, 1997. (Proceedings of the Air & Waste Management Association's Annual Meeting & Exhibition).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Washington, SP, Leonard, JD & Roberts, CA 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. Proceedings of the Air & Waste Management Association's Annual Meeting & Exhibition, Air & Waste Management Assoc, Proceedings of the 1997 Air & Waste Management Association's 90th Annual Meeting & Exhibition, Toronto, Can, 6/8/97.

Washington, Simon P. ; Leonard, John D. ; Roberts, Craig A. / Initial methodology for forecasting vehicle modes of activity as input to modal emissions models. Proceedings of the Air & Waste Management Association's Annual Meeting & Exhibition. editor / Anon. Air & Waste Management Assoc, 1997. (Proceedings of the Air & Waste Management Association's Annual Meeting & Exhibition).

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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.",

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AB - 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.

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

Abstract

Publication series

Other

ASJC Scopus subject areas

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