Comprehensive Mapping and Simulation Approaches for Urban Scenarios for Autonomous Vehicles Operation

Autonomous driving has been one of the most popular and challenging topics in recent years. Researchers striving for full autonomy have employed a variety of sensors, such as Light Detection and Ranging (LiDAR), cameras, inertial measurement units (IMU), and GPS, along with developing intelligent algorithms for their effective application. In addition to these advancements, the creation of high-precision maps has gained significant attention. These maps play a crucial role in localization using point clouds and in detailing the operational environment by generating routes and identifying traffic elements. As a result, they have become critical components of autonomous driving systems. This paper explores a modern method for map generation specifically oriented towards autonomous driving and examines its evolution through simulations conducted on the Autoware software platform. Additionally, the limitations of current map generation technologies are discussed to inspire future research and development in this rapidly advancing field. Through these discussions, the paper aims to contribute to the ongoing progress in autonomous vehicle technology.