In this paper, we consider multi-objective bilevel optimization problems in the context of transportation policy formulation. In such problems, an authority managing a network of roads is the leader that tries to solve the problem by taking into account the possible actions of the network users who are considered as the followers. In the presence of multiple objectives, the resulting solution set is a Pareto-optimal frontier that consists of optimal decisions of the leader and corresponding optimal responses from the follower. The authority's objectives are to maximize its revenues through tolls and minimize the pollution levels. The network users' objectives are to minimize travel cost and travel time. In addition to accommodating multiple objectives at both levels, the benefits of the proposed formulation is that it allows incorporating various real-world complexities, like admitting complex road network topologies and allowing the modelling of several road user classes with different preferences. A recently proposed algorithm for multi-objective bilevel optimization is used to solve the problem.