Truck platooning involves a series of trucks virtually linked to achieve energy savings through reduced aerodynamic drag. However, each truck bears a different position cost due to aerodynamics, with the leading truck incurring higher costs. This paper focuses on the cost allocation problem in scheduled truck platooning, which, aiming to maximize the cost allocation under the condition of minimizing system-wide fuel costs while considering platoon constraints on a general network.
We first model the character function of truck platoon game on network with platoon limitation as 0-1 integer programming problem. Then we reformulate and decompose it to two type sub-games by Lagrangian relaxation method. We prove that sub-game 1 has nonempty core and design a column generation method with platoon limitation valid inequality to solve the optimal coat allocation problem of sub-game 2. In addition, we present a hybrid algorithm framework including linear-programming-based (LPB) method, Lagrangian-relaxation-based method (LRB) and link reduction method to solve the large-scale cost allocation problem.
Finally, we examine the efficiency of the proposed method through numerical experiments. The results show that LRB is exact in small and medium scales, and the hybrid algorithm is applicable.