Producing the location information with the Kalman filter on the GPS data for autonomous vehicles

In today's vehicles, nearly 70% of driver-vehicle interaction takes place through digital systems. This interaction, which is increasing day by day, is provided by many intelligent applications running at the bottom. Applications such as lanecontrol, emergency brake assist, adaptive cruise control, which become standard equipment on vehicles, can be listed as a few of them. Vehicles providing autonomous driving support with the autopilot feature have begun to be used on developed country roads. In this study, correction of the GPS data, which is the main source of the vehicle location information, was done with the Kalman filter. The study began with the extraction of the vehicle model, which was entered into MATLAB environment and tested. Then, in MATLAB environment, the KALMAN fitler was implemented through this vehicle model and coefficient matrices were determined. Finally, the determined coefficient matrices and method are adapted to the real vehicle and field tests are performed.