Does driving behavior matter? An analysis of fuel consumption data from heavy-duty trucks

In a case study of a Norwegian heavy-duty truck transport company, we analyzed data generated by the online fleet management system Dynafleet. The objective was to find out what influenced fuel consumption. We used a set of driving indicators as explanatory variables: load weight, trailer type, route, brake horsepower, average speed, automatic gearshift use, cruise-control use, use of more than 90% of maximum torque, a dummy variable for seasonal variation, use of running idle, use of driving in highest gear, brake applications, number of stops and rolling without engine load. We found, via multivariate regression analysis and corresponding mean elasticity analysis, that with driving on narrow mountainous roads, variables associated with infrastructure and vehicle properties have a larger influence than driver-influenced variables do. However, we found that even under these challenging infrastructure conditions, driving behavior matters. Our findings and analysis could help transport companies decide how to use fleet management data to reduce fuel consumption by choosing the right vehicle for each transportation task and identifying environmentally and economically benign ways of driving.