Enzo Fabrizio Yacometti Idiaquez
Driving Style Estimation for Driver State Monitoring Truthful Data Acquisition via Driving Simulator.
Rel. Angelo Bonfitto. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2023
Abstract
Today's studies on Driving Style Estimation (DSE) provide valuable information on the subjectivity of different drivers behind the wheel, which directly impacts road safety, vehicle usability and component wear. The variety of use cases where this area of study is applied include impaired driving detection (e.g. distraction, drowsiness, aggressiveness), driver attitude profiling (e.g. theft situation, insurance), mission optimization (e.g. fuel reduction, battery wear reduction in case of electric vehicles), among many others. Due to the high cost of obtaining real driving data, the adoption of driving simulators has been the best alternative, even for big car manufacturers, to acquire realistic driving behavior data.
Such data gets processed to build an accurate driver model, which is considered a valuable asset to inform state-of-the-art Advanced Driver Assistance Systems (ADAS) about human driving subjectivity
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