Metro Vancouver’s Smart Drive Challenge (SDC), pilot program was intended to develop an understanding of how driver feedback could be used to reduce greenhouse gas emissions through both better driving habits and reduced reliance on automobiles. This study used three regression models: pooled ordinary least squares (OLS), fixed effects and first difference regression modelling techniques, on data collected via onboard data loggers during the SDC program. By using regression models, the effects directly attributable to the SDC can be quantified while accounting for confounding factors such as weather, fuel price and hours spent driving.
Partner: Metro Vancouver
Keywords: transportation
2017