Before revision:  Since human driving behavior is inherently multimodal, models which allow for multimodal output tend to outperform single-prediction models on standard metrics ; the proposed loss function benefits such models , as all predicted modes must follow the same expected driving rules  .
After revision:  Since human driving behavior is inherently multimodal, models which allow for multimodal output tend to outperform single-prediction models on standard metrics . We propose a loss function which enhances such models by enforcing expected driving rules .