A Fuzzy Logic Module to Estimate a Driver’s Fuel Consumption for Reality-Enhanced Serious Games

In this project, the authors have explored an application in the automotive field, estimating driver performance in terms of fuel consumption, based on three key vehicular signals, that are directly controllable by the driver: throttle position sensor (TPS), engine rotation speed (RPM) and car speed.

The Fuzzy Logic, models can be easily plugged into a reality-enhanced gaming architecture.Four models have been studied with all the possible combinations of the chosen variables (TPS and RPM; RPM and speed; TPS and speed; TPS, speed and RPM).
Input data were taken from the enviroCar database, and our fuel consumption predictions compared with their estimated values.

Results indicate that the model with the three inputs outperforms the other models giving a higher coefficient of determination (R2), and lower error. Our study also shows that RPM is the most important fuel consumption predictor, followed by TPS and speed


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