ADAS ECU software development for a front camera system

This project focused on developing software for an Electronic Control Unit (ECU) for Advanced Driver Assistance Systems (ADAS), targeting ASIL-D and Level 3 autonomous driving capabilities.

The main goal was to enforce a structured development process according to ASPICE standards, review and revise the software architecture model and detailed design, as well as optimize the ECU performance in terms of stability, CPU usage, RAM utilization, and scheduling.

As part of the project, various automotive development standards and tools were used to ensure that the development process met all necessary requirements. The main tasks included identifying and resolving stability issues and optimizing ECU performance to meet the stringent requirements for advanced autonomous driving functions.

The developed software solutions aimed to enhance the capabilities of the front camera system in autonomous vehicles. By providing reliable and accurate data for the perception and decision-making processes of the vehicle, the project significantly contributed to the overall performance and safety of the autonomous vehicle system.

The technologies and tools used supported compliance with ASPICE standards and facilitated continuous improvement of the software architecture and design. This included implementing methods for stability verification and optimization, as well as efficiently managing the resources of the ECU.

The project team conducted extensive testing and validation to ensure that the developed software solutions were robust and reliable. This involved checking CPU usage, RAM utilization, and ECU scheduling to ensure optimal performance and stability.

By employing these advanced technologies and rigorous development processes, sensified ensured that the developed software significantly enhanced the capabilities of the autonomous vehicle system and met high standards for safety and performance. The project delivered robust and optimized software solutions that made a significant contribution to the efficiency and safety of autonomous vehicle systems.