Abstract
The necessity of intelligent driver assistance systems in every future car is inevitable with the increased of injuries and fatalities from road accidents. The implementation of a wide array of sensors in a car could be utilized to detect driver's behavior to improve safety. This paper presents an analysis of car driver's behavior pattern recognition in lane changes and turns behavior using context-free grammar in linguistic-based syntactic recognition approach. The driving data which consists of the driver's eye gaze; the car's speed, steering wheel angle, and signal indication; are represented in symbolic form thus forming sentences which represent a specific behavior. Grammars are formulated based on the sentences trained from training data. The grammars are then evaluated by parsing the testing data. The experimental results show that driving behaviors are correctly detected with an average of 84.3% recognition rate exactly before a driving maneuver commences, which gives time to caution the driver should there any danger ahead.
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