The international community is making significant efforts to face climate changes related to substantial greenhouse gas (GHG) emissions. Among all the sectors, transport is responsible for almost a quarter of global GHG emissions, 72% of which is imputable to road vehicles. It’s also expected that, without significant measures, these emissions may grow at a faster rate than other sectors. Furthermore, rising fuel costs and availability concerns have made the electrification of road transportation an attractive option to reduce oil dependency. However, this solution produces an electricity demand increase, causing significant overload conditions that could affect the reliability of the distribution sector. For this reason, road transport electrification urges the implementation of smart charging strategies to optimize the interaction between electric vehicles (EVs) and the electric grid to reduce load uncontrolled fluctuation and peaks, avoiding significant investments into grid infrastructure. This solution can be more helpful if the EVs diffusion grows along with the renewable energy penetration in the grid. In this work, the effects of an optimal charging schedule on a fleet composed of thermal and electric vehicles performance have been analyzed in terms of the charging process's costs and emissions, considering hybrid and full electric configurations. A stochastic approach accounts for uncertainties in fleet operation and scenario parameters (such as fuel and electricity costs). The analysis was carried out for different locations in Europe to evaluate the effect of geographical position on the vehicle's performances considering a set of possible missions obtained from actual data. Results show that key performance parameters, such as the operating costs, and GHG emissions, are strongly affected by the studied locations' weather and traffic conditions and the advanced control logic implementation. Indeed, with the introduction of an optimal charged EVs fleet, savings of up to 49% and 97% can be achieved for GHG emissions respectively in the hybrid and full electric configuration.