Integrated model of assisted parking system and performance evaluation with entropy weight extended analytic hierarchy process and two-tuple linguistic information

Abstract

Evaluating comprehensive performance of assisted parking system has been a very important issue for car companies for years, because the overall performance of assisted parking system directly influences car intellectualization and customers’ degree of satisfaction. Therefore, this article proposes two-tuple linguistic analytic hierarchy process to evaluate assisted parking system so as to avoid information loss during the processes of evaluation integration. The performance evaluation attributes for assisted parking system are established initially. Subsequently, the information entropy theory is proposed to improve the evaluation attribute weight determined by analytic hierarchy process for the influencing factors of the randomness in parking test process. Furthermore, the evaluation attribute measure values of comprehensive performance are calculated and the assisted parking system evaluation results are obtained with ordered weighted averaging operator. Finally, numerical examples of vehicle types equipped with eight different assisted parking systems and computational results are presented.