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Detailed longitudinal dynamics simulations may be used to predict the energy performance of road vehicles. However, including uncertainty in the operating conditions often implies high computational costs. Model-based formulations, in conjunction with statistical methods, may obviate this limitation by directly accounting for stochasticity, thus eliminating the need for simulating large population
