Truck platooning consists of one or several trucks driving very closely behind the platoon leader with the help of technology. Platooning reduces fuel consumption, carbon emissions and congestion while increasing road safety and the productivity of trucks and drivers.However, platooning requires collaboration between different actors and synchronization imposes delays on some of the trucks. In this work, we consider a model where delays are compensated, and we focus (1) on the problem of identifying which trucks should cooperate for system-wide optimization and (2) on the question of how to `fairly’ redistribute costs among the different actors to guarantee adoption of the corresponding solution. We will show some connections to lot-sizing problems and games, and we will discuss the challenges of the corresponding problems. We will propose polynomial time algorithms for some special cases of the optimization problem, some efficient MIP formulation for small- to mid-size instances and fast and efficient heuristics for large-size instances. Then we will propose a cost-sharing rule that builds upon the solution of the heuristic and that exhibits attractive properties regarding stability (one of the most desirable properties of a cost-sharing mechanism). This is joint work with Behzad Hezarkhani and Yann Bouchery