Mohamad Wahbah, M. Sc.

Erstbetreuer: H. Alkahtib;  Co-Betreuer*in:

Determining the exact position of vehicles is not only crucial for autonomous driving, but also for many other applications. However, existing technologies such as global navigation satellite systems (GNSS) or inertial measurement units (IMU) reach their limits due to interference and inaccuracies, especially in urban areas.
The aim of the project is to develop a high-precision (< 10 cm) positioning system that enables autonomous vehicles to determine their position in their environment with high accuracy. State-of-the-art sensors collect environmental information, which is then compared with high-resolution 3D city models. The focus of study is on developing real-time data analysis for automatic object recognition. The system should be universally applicable and used in various traffic scenarios and environments.

The laser scan data of a vehicle is processed and methods are applied to improve data quality. A machine learning based algorithm is used to select a subset of the sensor data and then verify the quality through human judgement. Human interaction (human-in-the-loop) is expected to significantly improve the methodology. The processed data is then mapped to the 3D city model to achieve optimal results. Measurement deviations are reduced through the use of a special filter.