Stereo vision based navigation for driverless cars and obstacle avoidance

By combining autonomous driving technology with stereo vision systems, progress towards fully autonomous vehicles is becoming increasingly evident. The main goal of this project is to develop an advanced control system for a driverless car. The system is trained in this way it identifies different obstacles in the surroundings. System robustness and reliability are assessed through rigorous testing in various settings as part of an experimental setup, such as inclement weather and challenging terrain. Traffic safety is a serious issue that can be navigated through the navigation system of driverless car by reducing accidents caused by human mistakes, which is a major global contributor to traffic accidents. On the base of an algorithm, the system can detect anything and path planning. It shows how navigation systems based on stereo vision have the potential to transform the autonomous industry and increase traffic efficiency.