This paper proposes an optimization-based formulation of the decarbonization problem for the transportation sector, one of the main sources of CO \(_2\) emissions. An important feature of the proposed approach is that a detailed model is considered i.e., with different transportation modes and compositions of the associated fleets of vehicles. Using real data, this optimization problem is solved numerically under monetary and CO \(_2\) emissions constraints, but also constraints ensuring the feasibility of the transition. The obtained control actions provide insights into the transition from existing transportation modes to more sustainable ones. A discussion is made on the complexity of this problem: the dependency of resolution time on the budget values is in particular numerically assessed.