The Effect of Speed Factors and Horn Sound to The RLS 90 Model Reliability on The Visum Program in Predicting Noise of Heterogeneous Traffic

Abstract

This study aimed to predict the noise generated by heterogeneous traffic using RLS 90 model on the Visum program, evaluating and looking for correction factor. Points of observation were taken at 37 points on the road side at 06.00 - 18.00 and 06.00 - 21.00 with research object are motorcycle, light vehicle and heavy vehicle. The observed data are traffic volume, vehicle speed, number of horn and traffic noise by using Sound Level Meter Tenmars TM-103. The result shows the prediction model of RLS 90 Visum program produces an average noise level value of 69.3 dB with Pearson’s correlation and RMSE of 0.71 and 9.97, the prediction model RLS 90 vehicle correction produces an average noise level value of 77.9 dB with Pearson’s correlation and RMSE of 0.75 and 2.02, whereas the prediction model RLS 90 vehicle and horn correction produces an average noise level value of 79.1 dB with Pearson’s correlation and RMSE of 0.83 and 1.29. So that, prediction model RLS 90 with vehicle and horn correction quite good which has a relationship of Y = 0.71 X + 29.65 to the prediction model RLS 90 with Visum program.