<p>Many theoretical and experimental models have effectively implemented controllers based on the Hedge-Algebras theory. However, these controllers are often in the form of two-input state variables to determine the control variables. Therefore, this study proposes a novel approach to designing multi-input Hedge-Algebras-based controllers and applications in the motion control of autonomous vehicles. First, the multi-input Hedge-Algebras-based controllers are divided into sub-controllers with different numbers of inputs. Next, the sub-controllers are appropriately set up with the corresponding input number to determine the sub-output control variables. The sub-outputs are combined using a weighted average formula to calculate the unique output for each control action. The sub-controllers’ parameters and the sub-output weights can be optimized to improve the efficiency of the proposed controllers. Simulation results show higher control efficiency and faster computation time of the proposed controllers compared to controllers based on fuzzy set theory when navigating autonomous vehicles. The proposed approach demonstrates the potential application of the Hedge-Algebras theory in designing complex and multi-input controllers for different industrial objects.</p>