I assume that you are talking about a discrete choice model (not an aggregate one). If you propose a set of dummy variables for the sub-categories (student, senior, etc.), you must know who they are (which observation corresponds to a student's choice, a semior's choice, etc.).

If I get this right, then you apply the appropriate price for that individual (full or discounted).

The next issue is then whether you assume the same coefficient for price independently from the individual's category, and the same mathematical form (I prefer to use Box-Cox and let the data decide on the form). I would start with the same coefficient and functional form and test this, especially for the coefficient, across different categories.

Marc Gaudry

Well, in modeling it is often preferable to use a variable like price in level form so that it will be possible to capture as much heterogeneity as possible. Given your case, I believe using both price and an interaction variable (price multiplied by discount dummy) would allow to see the effect of price. I hope this helps.

Given that the variable price always takes only 4 categories with scale aspect, I think you may transform this variable to be equivalent for all observations. Thus the new price variable takes the values  (1, 2, 3 , 4 ) instead of (10,20,30,40) and  (1, 2, 3 , 4 ) instead of (5,10,15,20) for students. If the fact that being student may have effect on your dependant variable you should think about adding an explanatory dummy variable indicating this fact but take care about multicollinearity.