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Abstract
Correlation analysis was performed to investigate the effects of drive cycle characteristics on
distance-specific emissions (g/mile) and fuel economy (mpg) and consequently determine the most
influential cycle metrics for modeling. A detailed analysis of linear and non-linear correlations
was performed among cycle metrics to avoid collinearity and reduce the number of variables. The
order of importance of the selected cycle metrics was determined. Results show that average speed
with idle, number of stops per mile, percentage idle, and kinetic intensity were the most important
cycle metrics affecting emissions and fuel economy. Preliminary regression analysis reinforced their
importance for emissions modeling purposes.