Algorithm testing for radar and camera sensors

The project focused on developing and conducting comprehensive test cases for various radar and camera sensor functions used in automotive applications.

The goal was to ensure the reliability and accuracy of the sensors critical for advanced driver assistance systems (ADAS) and autonomous driving applications.

Key tasks included developing observers using Python scripts and conducting plausibility checks of performance signals in Software-in-the-Loop (SIL) environments. Another crucial part of the project was comparing Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL), and ECU systems to ensure consistency and accuracy. Furthermore, the simulation environment was enhanced to validate algorithms used in radar and camera sensors.

The technologies and tools used in this project included MATLAB, Python, MKS Integrity, DOORS, SQL, C++, and MTS (Measurement and Test Software). These tools supported the creation and management of test cases, as well as the analysis and documentation of results.

The development process included detailed documentation of test cases and results to ensure a thorough validation process for the radar and camera sensor algorithms. The rigorous testing methods applied in the project ensured that the sensors reliably operated and provided accurate data under various conditions.

One of the main tasks of the project was the development of observers using Python scripts to monitor and analyze sensor signals. The plausibility checks of performance signals in Software-in-the-Loop (SIL) environments helped ensure the correctness and reliability of the algorithms. Comparing results from Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL), and ECU systems ensured that the developed algorithms operated consistently and accurately.

Another important aspect was the further development of the simulation environment. This allowed testing and validating the algorithms in a controlled environment before integrating them into real systems.

The project delivered comprehensive test reports and validated algorithms that met the highest performance and reliability standards. The rigorous validation processes and detailed documentation ensured that the developed sensor functionalities met the requirements of advanced driver assistance systems and autonomous driving applications. Through these thorough testing and validation processes, sensified ensured that the end products were reliable and efficient, contributing to the safety and efficiency of the vehicles.