Fuzzy Logic System for Risk and Energy Efficiency Estimation of Driving Maneuvers

This paper presents a Soft Computing based system to identify risky driving maneuvers on conventional two-lane roads. Road design and vehicle dynamics are considered. Specifically, a fuzzy rule-based Mamdani-type inference system is applied. The vehicle dynamics features are measured by smartphone inertial sensors. The real data obtained from the GPS, accelerometer, and gyroscope are used to identify the driving maneuvers. A conventional two-lane road located in the Madrid Region, Spain is used for this research. The results obtained with the fuzzy system are promising and suggest that this intelligent system can be used to warn drivers of a risky maneuver in real time for a safer, more ecological and comfortable driving.