Abstract

Population growth and development of activities in Denpasar City have a great influence on the development of transportation sector. The increase of population has been followed by high growth rate of private vehicles. This condition has increased environmental degradation, not only in terms of fuel consumption but also in terms of air pollution and traffic noise produced by motor vehicles. Traffic noise has caused negative effects such as communication difficulty, increase of stress, sleep disturbance, and also hearing problem. In order to overcome these problems, in the first instance, it is required to be able estimate the level of traffic noise produced by certain traffic volume. Therefore, it is important to understand factors that influence traffic noise. The objective of this study is to develop model estimation of traffic noise, in particular for collector roads. Traffic data collected included traffic volume (classified by vehicle types), speed, and road geometric. Data were analysed by using multiple linear regression method. This study found that as the proportion of motor cycle dominates the road traffic (about 75%), motor cycle volume was found to be the most significant traffic noise predictor. Holding other factors constant, the increase of 100 motor cycle will increase traffic noise LAeq for about 0.3dB. The increase in LA10, LA50 and LA90 are 0.4, 0.4 and 06, respectively. The average error of the predicted value from the measured value for Leq is -2.33%. Average error for L10, L50 and L90 is +0.39%, -1.04% and +0.002%, respectively. This model of traffic noise level can be used to predict vehicle noise level for collector road with an average speed of vehicles between 23-49km/hour.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.