@article{Pandian_Devanayagam Sundaram_Sivaprakasam_2016, title={Development of Fuzzy Based Intelligent Decision Model to Optimize the Blind Spots in Heavy Transport Vehicles}, volume={28}, url={https://traffic.fpz.hr/index.php/PROMTT/article/view/1614}, DOI={10.7307/ptt.v28i1.1614}, abstractNote={<p>Statistics reveals that the visual problems are the prime<br />reasons for a larger number of road accidents. The blind spot<br />is the major problem related to vision. The aim of this study<br />is to develop a fuzzy-based multi criteria decision-making<br />model for optimizing the area of the blind spot in the front<br />and sides of a heavy transport vehicle. To achieve this, the<br />statistical tool ANOVA (Analysis of Variance) and multi criteria<br />optimization techniques like TOPSIS (Technique for Order<br />of Preference by Similarity to Ideal Solution), FAHP (Fuzzy<br />Analytical Hierarchy Process) and GRA (Grey Relational<br />Analysis) were also used in this problem This paper consists<br />of three modules: first, the blind spots of the existing body<br />structure dimension used in heavy vehicles were studied<br />and the optimal design parameters were determined by using<br />ANOVA and TOPSIS methodologies; next, the weights of<br />the design parameters were calculated using FAHP method.<br />Finally, GRA-based Multi Criteria Decision Making (MCDM)<br />approach has been used to rank the vehicle body structures.<br />The proposed model has been implemented in a transport<br />corporation to compare four different types of body structures<br />and concluded that the body structure which was built<br />by an outsourced body builder is having a smaller area of<br />blind spot and optimal design parameters as well.</p&gt;}, number={1}, journal={Promet - Traffic&Transportation}, author={Pandian, Pitchipoo and Devanayagam Sundaram, Vincent and Sivaprakasam, Rajakarunakaran}, year={2016}, month={Feb.}, pages={1-10} }