Autonomous vehicle tracking location with satellite data

Autonomous vehicles play an important role in the future of transportation. Thanks to the developments in artificial intelligence, it is predicted that smart cars and trucks will become driverless, accidents will decrease and they will become more efficient in the future. They also provide safe travel by reducing reaction time delay, increasing the likelihood of safe lane changes, and eliminating human driving errors. Automakers have invested in research areas relevant to current challenges. This thesis study explores a programming language used for processing satellite data and location tracking. Within the scope of the research, subjects such as analysis of satellite data, analysis of satellite signals, position estimation and verification methods are discussed. In addition, practical applications can be realized on an autonomous vehicle prototype that can track location with satellite data. This thesis aims to design and implement a working language developed for the effective use of satellite data in position tracking of autonomous vehicles. This working language aims to be a tool for more accurate and reliable location detection by contributing to the development of autonomous vehicle technologies. The thesis covers modeling of vehicle dynamics, design of lane change controller, working principle of lane change planner, metric evaluation, visualization, scenario and environmental conditions, plan parameters in detail. This comprehensive study is an important step towards achieving results similar to real- world scenarios and clarifying the issues under investigation.