Domain adaptation for autonomous driving provides the ability for models to generalize knowledge across datasets and conditions. Due to domain discontinuity and distribution shift, a model trained on one dataset may lose accuracy in new environments. The use of transfer learning methods and feature alignment strategies improves cross-data generalization, reducing