Our summer intern made a significant contribution by enhancing a robustness framework for one of our vehicle algorithms. The framework, designed to track anomalies in wheel speed signals and mitigate their impact on system performance, was significantly improved by the intern's work. They generalized an existing implementation to monitor multiple frequency disturbances, applying digital signal processing and change detection principles. The core algorithm was developed in C, with MATLAB used for auxiliary analysis tools. This enhancement significantly boosts the system's ability to detect and respond to signal anomalies, thereby contributing to the overall reliability of the vehicle's systems.
Languages/frameworks: C, C++, Python, Matlab, Bazel, Jenkins, Docker, k8s, Groovy
