Abstract: An intelligent Global Positioning System (GPS) based control system utilises information about the current vehicle position and upcoming terrain in order to reduce vehicle fuel consumption as well as improve road safety and comfort. The development of such in-vehicle control systems has provided static and dynamic road information. The vehicle running parameters have been mathematically defined whilst the engine control algorithms were derived from a custom-built engine test-rig. As the vehicle travelled over a particular route, road information such as gradient and position was stored with the past trajectory using a Neuro-Fuzzy technique. This road information was continuously updated and replaced by new data as the vehicle moved along, thereby adjusting the engine control parameters to reflect the actual current vehicle running data. The control system essentially used a fuzzy logic derived relief map of the test route and this was further validated and corrected based on the past trajectory from the in-vehicle GPS sensor. The simulation model demonstrated the feasibility and robustness of the control system for motor vehicle control applications.