The design of an efficient techno-economic autonomous fuel cell hybrid electric vehicle (FCHEV) is a crucial challenge. This paper investigates the design of a near optimal PI controller for an automated FCHEV, where autonomy is expressed as efficient and robust tracking of a given reference speed trajectory without driver's intervention. An impartial comparison is introduced to illustrate the effectiveness of the proposed metaheuristic-based optimal controllers in enhancing the system dynamic performance. The comprehensive optimization performance indicator is considered as a function of the vehicle dynamic characteristics while determining the optimal controller gains. In this paper, the proposed effective up-to-date metaheuristic techniques are the grey wolf optimization (GWO) as well as the artificial bee colony (ABC). Using MATLABTM/Simulink, numerical simulations clearly illustrate the efficiency of near-optimal gains in the optimized tuning methodologies and the fixed manual one in realizing adequate velocity tracking. The simulation results demonstrate the superiority of both ABC and GWO rather than the manual controller for driving cycles of high acceleration and deceleration levels. In absence of these latter, the manual defined gain controller is considered sufficient. Through a comprehensive sensitivity analysis, the robustness of both metaheuristic-based controllers is verified under diverse driving cycles of different operation features and nature. Despite GWO results in better dynamic characteristics, the ABC provides more economical feature with about 1.5% compared to manual system in extra urban driving cycle. However, manual-controller has the minimum fuel cost under the United States driving cycle developed by the environmental protection agency as a New York city cycle (US EPA NYCC) and urban driving cycle (ECE). Ecologically, electric vehicles have an environmentally friendly effect especially when driven with green hydrogen. Autonomous vehicles, involving velocity control systems, would raise car share and provide more comfort.