We are developing a visual SLAM approach for highly automated vehicles, mainly using monocular cameras, which makes it independent of other sensors and allows for redundant solutions. Furthermore, it simplifies extrinsic calibration and time synchronization issues. Therefore, we target a single-shot and real-time capable algorithm, which is deterministic, robust to environment structures, and complemented by confidence levels. Our cost-effective solution generates a 3D map of the environment, in which the vehicle can precisely determine its position. In the future, this can be used to supplement LiDAR systems in highly automated vehicles or even replace them in parts. In this paper, we present our recent progress in developing a robust single-shot monocular SLAM system.