Development of Fuzzy Based Intelligent Decision Model to Optimize the Blind Spots in Heavy Transport Vehicles

Abstract

Statistics reveals that the visual problems are the primereasons for a larger number of road accidents. The blind spotis the major problem related to vision. The aim of this studyis to develop a fuzzy-based multi criteria decision-makingmodel for optimizing the area of the blind spot in the frontand sides of a heavy transport vehicle. To achieve this, thestatistical tool ANOVA (Analysis of Variance) and multi criteriaoptimization techniques like TOPSIS (Technique for Orderof Preference by Similarity to Ideal Solution), FAHP (FuzzyAnalytical Hierarchy Process) and GRA (Grey RelationalAnalysis) were also used in this problem This paper consistsof three modules: first, the blind spots of the existing bodystructure dimension used in heavy vehicles were studiedand the optimal design parameters were determined by usingANOVA and TOPSIS methodologies; next, the weights ofthe design parameters were calculated using FAHP method.Finally, GRA-based Multi Criteria Decision Making (MCDM)approach has been used to rank the vehicle body structures.The proposed model has been implemented in a transportcorporation to compare four different types of body structuresand concluded that the body structure which was builtby an outsourced body builder is having a smaller area ofblind spot and optimal design parameters as well.