| Abstrakt: |
Global automotive arena has overshadowed by intense competition because customers nowadays being more selective about their preference towards car selection. In a different dimension, car's interior design promised maximum satisfaction for customers. For long distance drivers, comfort feeling influence by many factors, which one of them contributes by interacting with in-car environment. This paper primarily concentrated into the human comfort study which studying the driver in-car activity such as handling the steering, monitoring the driving and using the in-system. Ultimately, this paper proposed a knowledge based system framework of interaction of driver with in-car system. The current problem face by driver relates to car interior compartment (car seat, navigation system, signaling panel, instrument panel, gear knob, pedaling system, and mirror) can be understand and recommended for improvement. Also, this study helps to measure the satisfaction of drivers while cooperate with incar system. In order to measure in-car driver interaction, an intelligent system introduces a knowledge base system which using hybrid technique called neuro-fuzzy techniques. The neural network involve with developing the system in multi layer concept and the fuzzy basically using IF-THEN rule. This research explores the humanmachine interaction through a driver knowledge based system. The conceptual framework contributes on optimize the design process, decision making and analysis in assisting automotive productivity and quality. [ABSTRACT FROM AUTHOR] |
