This study presents a novel benchmarking methodology for Data Acquisition System (DAS) types to support industrial community characteristics in designing and implementing the advanced driver assistance systems within vehicles, which is considered multicriteria decision-making (MCDM) problems. Four issues support this claim. Multiple criteria need to be considered in the evaluation, data variation, trade-off and conflict. Thus, an MCDM solution is essential to overcome problem complexity. In the last years, MCDM developed methods have been studied and criticised from different theoretical aspects. The most recent method, fuzzy decision by opinion score method (FDOSM), has proven its power in solving other methods challenges. However, the FDOSM technique and its extension were based on traditional fuzzy set theory, which is limited and unable to deal with the membership and non-membership hesitation simultaneously and that affect the accuracy of final decision especial among the group of decision-makers. Therefore, this study extended FDOSM into an intuitionistic fuzzy environment that considers the hesitation index in the membership definition, then discuss the power of such membership in evaluating and benchmarking the DAS systems. The proposed methodology comprises two consecutive phases. In the first phase, a decision matrix is formulated based on the crossover of the ‘DAS systems’ and ‘multiple evaluation criteria’. In the second phase, the new method (the intuitionistic FDOSM method) has two main stages (i.e. data transformation unit and data processing). The dataset was used to prove the concept. A total of 39 DASs were evaluated based on 14 DASs criteria, involving seven sub-criteria for “comprehensive complexity assessment” purpose and eight sub-criteria for “design and implementation” purpose, which highly affected the design of DAS when implantation occurred by industrial communities. The results of this study are as follows: (1) Individual results of benchmarking, which used three decision-makers are broad, with consensus on the DAS#1 system ranked as the best. (2) The results of the proposed GDMs proved quality in DASs benchmarking, and the DAS#1 system is also the best. (3) Intuitionistic FDOSM can deal with hesitation and uncertainty problems properly. (4) Significant differences were indicated among the groups’ scores, which proves the validity of the intuitionistic FDOSM results.

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