You can increase the penalty for running a red or increasing the relative sample of red light stops present in the real and synthetic training data. You can use neural net analysis techniques to confirm that features like color and stoplights are being recognized.

You confirm it is fixed by ensuring your validation set also has sufficient data representing the failures (and that they now succeed).