This paper proposes an approach that characterizes a driver's driving behavior and style in real-time during car-following drives. It uses an online learning of the evolving Takagi-Sugeno fuzzy model combined with the Markov model. The inputs fed into the proposed algorithm are from the measured signals of on-board sensors equipped with current vehicles, including the relative distance sensors for Adaptive Cruise Control feature and the accelerometer for Electronic Stability Control feature. The approach is verified using data collected using a test vehicle from several car-following test trips. The effectiveness of the proposed approach has been shown in the paper.
Real-time Determination of Driver's Driving Behavior during Car Following
Sae International Journal of Passenger Cars- Electronic and Electrical Systems
Sae Int. J. Passeng. Cars – Electron. Electr. Syst
SAE 2015 World Congress & Exhibition ; 2015
14.04.2015
8 pages
Aufsatz (Konferenz)
Englisch
Real-time Determination of Driver's Driving Behavior during Car Following
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