Experimental System to Support Real-Time Driving Pattern Recognition

This work proposes an advanced driving information system that, using the acceleration signature provided by low cost sensors and a GPS receiver, infers information on the driving behaviour. The proposed system uses pattern matching to identify and classify driving styles. Sensor data are quantified in terms of fuzzy concepts on the driving style. The GPS positioning datum is used to recognize trajectory (rectilinear, curving) while the acceleration signature is bounded within the detected trajectory. Rules of inference are applied to the combination of the sensor outputs. The system is real-time and it is based on a low-cost embedded lightweight architecture which has been presented in a previous work.