An intelligent driver assistance system for improving commercial vehicle fuel economy

Abstract

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 behaviour. The drive route can be specified by information such as speed limit, road grade, road curvature, traffic, etc. The driver behaviour, on the other hand, is difficult to classify and can be responsible for as much as 35% variation in fuel consumption. In this work, an intelligent driver assistance system is presented that utilises upcoming road information to minimise vehicle fuel consumption. This system processes information obtained from on-board sensors, digital maps, vehicle-to-vehicle communication systems, and/or vehicle-to-infrastructure communication systems to identify driving scenarios. A component of this system is a unique scenario identification algorithm that either advises the driver or actively limits the engine torque based on the specific driving scenario. Simulation and experimental results are presented that demonstrate fuel savings in a scenario where the system modulates the vehicle speed as a function of upcoming road grade. The intelligent driver assistance system is subject to a pending patent application.