Transportation systems are a key part of sustainable development, and they need to be carefully evaluated to show that they have a strong impact on the target area’s social, environmental, and economic sustainability. For this reason, involving the developed decision support systems helps to shed light on the users’ demand and provide unblemished policy decisions considering the existing situation. The “q-rung orthopair fuzzy set (q-ROFS)” is a generalization of the “intuitionistic fuzzy sets (IFSs)” and “Pythagorean fuzzy sets (PFSs)” that expresses vague and uncertain data more efficiently. In the interim, the notion of “dual hesitant q-rung orthopair fuzzy set (DHq-ROFS)” is presented to account for human hesitancy, which may be more applicable to genuine “multicriteria group decision-making (MCGDM)” situations. The main goal of this study is to address MCGDM problems using Heronian mean (HM) and DHq-ROF data. The first step is to introduce the Frank t-norm and t-conorm-based DHq-ROF HM (DHq-ROFFHM) operator. DHq-ROFFHM’s features are next described in depth. In addition, the DHq-ROF Frank weighted HM (DHq-ROFFWHM) operator is presented, which takes into account different degrees of liking for input arguments. The DHq-ROF Frank weighted power partitioned HM model is then used to come up with a way to solve models in MCGDM problems where individual arguments are grouped together and have relationships with each other. A final example shows how the established model can be implemented and how well it works.