Every day driving involves several types of distractions in modern times. Some of the distractions can hinder visual attention which might affect the driving perfor- mance. Visual distractions like texting are very evi- dent but there are no practical tools available to detect non-visual distractions automatically while driving. Eye tracking technology has promising capability to detect a persons state of mind and there is possibility to re- late the driving performance under mental distractions. Identification of eye movement patterns can reveal char- acteristics such as fixation and saccade under all kinds of distractions. Present study make use of I-DT algorithm to derive fixations and saccades for 26 participants for 4 driving conditions. Using eye tracking and driving re- sponse data, normal driving is compared with driving under three distractions i.e. cognitive, emotional, and texting. When compared to driving with no distrac- tions, results show a significant increase in fixation du- ration along with decrease in number of fixations while texting. For cognitive and emotional distractions, re- strictive eye movements were seen by utilizing visual- ization techniques. Statistical techniques were used to verify these results.