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.