UFLD enhancements: New loss function and image masking

In the field of autonomous driving, lane detection plays a crucial role in ensuring safety and accuracy in navigation. This paper presents enhancements to the Ultra Fast Lane Detection (UFLD) model by introducing a new loss function that ensures smoother and more continuous lane lines, and incorporating image masking techniques to simulate real-world occlusions. These modifications improve the models robustness, particularly in scenarios with degraded lane markings. Through extensive experimentation on the TuSimple dataset, we demonstrate that the proposed enhancements lead to more accurate and realistic lane detection, especially in challenging environments.