Autonomous vehicles are aimed to reduce accidents and traffic congestion. Since hybrid electric vehicles offer feasible solutions to reduce energy consumption and emission to the environment, it is expected that autonomous vehicles will be powered through a hybrid electric system compared to other alternatives. In this paper, a hybrid electric autonomous vehicle is studied under significant amount of uncertainty and ambiguity in the road environment and driver behavior. A Type 1 fuzzy logic controller is constructed here to address the uncertainties of driving conditions. The design involves building an intelligent energy management system for the hybrid electric autonomous vehicle. We have also examined the potentials of the Interval Type 2 fuzzy logic control, especially for energy consumption management. Two simulations are implemented, to demonstrate that the intelligent system, proposed trough Type 1 and Interval Type 2 fuzzy logic control, decreases the fuel usage of the vehicle from 6.74 to 6.58 L/100km, respectively. It is also demonstrated that the Interval Type 2 fuzzy logic controller saves more battery life compared to the Type-1 when the vehicle works under uncertain and ambiguous road conditions. Finally, Interval Type-2 fuzzy logic controller facilitates a reduction of carbon footprint in the autonomous vehicle as desired by the automotive industry stakeholders.