Penentuan Model Lajur pada Self-Driving Car menggunakan Hough Transform dan Kuantisasi Warna K-Means - Pupung Adi Prasetyo; Randy Cahya Wihandika; Candra Dewi (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Technology continues to develop to the phase where human daily activities can be carried out by artificial intelligence. Research on artificial intelligence keeps on competing to produce more advanced program to simplify things. Nowadays artifial intelligence tools can be found in various application, one of them is self-driving car. This topic is one of the most widely researched topic due to its various division of functionality. The most frequently discussed functionality is the defining of navigation lane model. The lane model which is the navigation direction of a self-driving car must be visually determined based on the road markings, which also the navigation direction directions of public vehicles. Therefore, this study will determine the lane model visually using image processing methods. By only using image processing, the resulting precision can reach an average value of 88.45% in various road conditions. Therefore, it can be concluded that the visual image processing can be used to determine the lane model in a self-driving car.