Analysis And Validation of Traffic Noise Under Dynamic Condition Near Roundabout Using Madm Approach

Abstract

The problem of roundabout traffic noise measurement has been of concern to Traffic Management for many years. The measurement and prediction process has become more and more difficult due to the availability of large variety of traffic noise prediction models. The models proposed so far consider only physical parameters (Traffic Volume, Traffic Composition, Average Speed etc). The aim of this work is to propose a methodology by which identification of traffic noise can be made easy. A cause and effect diagram is developed for the attributes identification, those are sufficient to describe the traffic noise. Attribute based coding of traffic noise has been done to convert the information into useful form. Information developed from the quantification of attributes is useful to the designer, traffic management and the user in traffic noise system. The identification and codification of attributes based on alpha numeric code is presented for roundabout traffic noise. The roundabout traffic noise measurement procedure allows rapid convergence from a very large number to controllable shortlist of potentially suitable attributes using “elimination search”. Subsequently, the identification procedure proceeds to evaluate them by a multiple attributes decision making (MADM) method using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach. It helps the user‟s to organize the problem to be solved, and carrying out analysis, comparison and ranking of the roundabouts. Three critical roundabouts (Fountain roundabout, Thikri roundabout, and YPS roundabout) have been studied at Patiala city, Punjab, India. Equivalent sound level and traffic parameters (traffic volume, percentage of heavy vehicles, average speed, acceleration, and deceleration) have been measured. Noise environment have been compared, worst and best roundabout have been identified. The conclusion arrived from the hypothetical approach MADM has been validated through experimental investigation.