A significant amount of fossil fuel consumed and pollutants emitted worldwide can be linked to road transport. In addition, fuel has always been one of the main components concerning the pricing of cargo transport and, as a result, its economy has become one of the pillars for the development of new vehicle technologies. Eco-driving, which consists of driving a vehicle aiming at high energy efficiency conditions, has been widely studied in recent years due to its supposed benefits in reducing fuel consumption and pollutant emissions. One of the fronts of eco-driving studying is the optimization of speed profiles, which translates into, through an optimal control problem, minimizing the fuel consumption of a route having the vehicle speed as a control variable. A good part of the heavy vehicle automakers already have solutions that seek to save fuel through this strategy, however, such solutions are only introduced in the market through new vehicles. Due to the high average age of road vehicles in Brazil and its constant increase, methods that are also applicable to this existing fleet could help to increase its energy efficiency more quickly. In this work, a computational environment based on dynamic optimization and rigorous numerical simulation is proposed to minimize fuel consumption in heavy vehicles, through the optimization of speed profiles in road routes that is of general application, that is, applicable to any brand or model of vehicle and that does not require costly data to be obtained in its calibration, as the already existing solutions made available by some automakers do. The methodology used consists of defining a highly accurate and easily calibrated fuel consumption model, a vehicle dynamics model that covers the main movement parameters of the vehicle, elaborating and solving the optimal control problem, and, finally, verifying the performance of the solution in a dynamic simulation environment that addresses various dimensional and kinematic aspects of the vehicle and the path through the TruckSim software. The results showed, in the study scenarios, that such a solution is capable of reducing an average of 8.32% of the fuel consumption of a truck when compared to a constant speed profile.