The Fuel-Efficient Platooning of Heavy Duty Vehicles by Mathematical Programming and Genetic Algorithm

As fuel accounts for a significant proportion of the total operational cost of heavy duty vehicles (HDVs) and to alleviate the environmental impacts, companies are seeking for novel practical methods to reduce fuel consumption. Platooning is an effective approach in which a string of HDVs driving close behind each other is formed. This reduces the aerodynamic drag leading to a reduction in the overall resistive force on vehicles which can provide an amount of fuel-saving in each of the following vehicles. These trivial reductions result in a considerable decrease in the total fuel consumption corresponding to all the vehicles. In this paper, we propose a mathematical model for the fuel-efficient platooning problem with a deadline for each vehicle (truck) to reach its destination by then. We create a graph partly based on the German road network considering only 20 important cities and solve 50 instances including 10 to 50 trucks. The small samples are solved by the LINDO solver in real time but as the problem has a high computational complexity, a Genetic Algorithm is applied to obtain fast solutions of a good quality for larger instances. The final results show a satisfactory fuel-saving in all of the cases.