Advances in sensor solutions in the automotive sector make it possible to develop better ADAS and autonomous driving functions. One of the main tasks of highway chauffeur and highway pilot automated driving systems is to keep the vehicle between the lane lines while driving on a predefined route. This task can be achieved by using camera or GPS to localize the vehicle between the lane lines. However, both sensors have shortcomings in certain scenarios. While the camera does not work when there are no lane lines to be detected, an RTK GPS can localize the vehicle accurately. On the other hand, GPS requires at least 3 satellite connections to be able to localize the vehicle and more satellite connections and real time over-the-air corrections for lane level positioning accuracy. If GPS localization fails or is not accurate enough, lane line information from the camera can be used as a backup. In this paper, a vision based lane keeping system is fused with a GPS based path following application to overcome the shortcomings of the GPS and camera sensors in highway driving path following applications. The developed system has a parameter space based robust steering controller which can handle lateral motion control of the vehicle based on path tracking error detected using the GPS and camera sensors fusion. The designed control system works for both low speed and high-speed driving scenarios and is robust to changes in vehicle mass and changes in road friction coefficient. The results are demonstrated using the validated model of our 2017 Ford Fusion Hybrid research automated driving vehicle in our hardware-in-the-loop simulator. Experimental verification is also planned.