Assistant Professor Qian Zhang has received an OASIS award for enhancing the robustness of ADS systems in the Inland Empire. 

This project enhances the robustness of autonomous driving systems in the Inland Empire by applying mutation-based test generation from software engineering to augment datasets. By simulating environmental conditions like high solar exposure, it aims to improve training effectiveness and reduce the need for resource-intensive re-training. This approach has the potential to strengthen model performance while lowering energy consumption, and promoting sustainable ADS deployment.