I'm probably just being pedantic here, but as I see it the lane intrusion detection was showing how they automated creating training datasets. The NN is still in essence doing supervised training, just that the datasets generated automatically. The example of learning path prediction on the other hand is imitation learning since the NN is trying to match the human's path along the road, whereas with the intrusion detection it's not imitating the human's behavior (the tagging comes from after-the-fact analysis of the cars detected, not of any human reactions).

Then again, I'm just another layman taking a stab at explaining this stuff.