The automation of vehicles has been widely recognized in measures for increasing safety and efficiency in driving. Of these technologies, Lane Keeping Assist systems (LKA), as part of Advanced Driver Assistance Systems (ADAS), are designed to improve road safety and also driver performance. However, reliance on their visual feedback presents barriers to drivers with partial impairments in vision. The present study tries to explore methods through which LKA systems can be optimized to improve usability, with a focus on the parameters of learnability and efficiency. A qualitative approach was used here that utilized secondary data from a total of 30 peer-reviewed articles. The Braun and Clarke (2022), six-phase thematic analysis framework applied to emphasis on key usability factors. The results show that adaptive feedback mechanisms involving auditory and haptic cues, with intuitive and user-centered interface designs, significantly improve learnability and efficiency. These enhancements reduce cognitive overload and learning time while enabling the effective performance of tasks by visually impaired drivers. The study introduces actionable insights into improving accessibility and also functionality in LKA systems by addressing existing usability gaps, thereby improving equitable independence of use by visually impaired drivers from such advanced systems.