Commercial vehicle operators and governments around the world are looking for ways to cut down on fuel consumption for economic and environmental reasons. Two main factors affecting the fuel consumption of a vehicle are the drive route and the driver behavior. The drive route can be specified by information such as speed limit, road grade, road curvature, traffic etc. The driver behavior, on the other hand, is difficult to classify and can be responsible for as much as 35% variation in fuel consumption. In this work, nearly 600,000 miles of drive data is utilized to identify driving behaviors that significantly affect fuel consumption. Based on this analysis, driving scenarios and related driver behaviors are identified that result in the most efficient vehicle operation. A driver assistance system is presented in this paper that assists the driver in driving more efficiently by issuing scenario specific advice. In addition, if need be, the system can limit the maximum throttle request based on the identified scenario. Such a system utilizes information obtained from on-board sensors, digital maps, vehicle-to-vehicle communication systems, and/or vehicle-to-infrastructure communication systems to identify driving scenarios. Simulation results are presented that demonstrate fuel savings in one specific scenario.