Earticle

In order to overcome the limitations on human accidents and reduce experimental costs during autonomous driving, studies using virtual simulator is conducted. In addition, by using open source-based frameworks and middleware, we develop a module that can be applied immediately to a real vehicle using a model developed for autonomous driving that has been studied in a virtual environment. In this paper, we use autonomous driving environment using a game engine-based CARLA simulator, and propose a model predictive control module by interlocking open-source ROS (Robot Operating System) and Autoware with the simulator. In addition, ROS manages vehicle information and sensor data and transmits them to the Autoware. In order to control autonomous driving, the control end part is implemented using MPC (Model Predictive Control) among Autoware APIs, which provides necessary functions such as 3D map generation and NDT matching algorithm for autonomous driving, location identification, object recognition, and vehicle control.