摘要
Continuous vehicle tracking as well as monitoring driving behaviour, is significant services that are needed by manyindustries including insurance and vehicle rental companies. The main goal of this paper is to provide methods to model the quality ofthe driving behaviour based on FIS （fuzzy inference systems）. The models consider vehicle dynamics as long as the human behaviourparameters, expressed by a set of raw measurements which are obtained from various environmental sensors. In addition,assessment-driving behaviour model is simulated and tested by two different FISs： Mamdani and Sugeno-TSK. The simulation resultsillustrate the critical distinctions between the two FISs using the proposed driving behaviour models. These differences are based onvarious processing times, robust behaviour of the FISs, outputs MFs （membership functions）, fuzzification-techniques, flexibility inthe systems design and computational efficiency.
