Fidelma Tbili - Federal University of Technology, Akure
Adebayo O.Owalabi - Professor of Transportion Engineering, Civil Engineering, Federal University of Technology, Akure

Traffic noise prediction models are required as aids in the design of roads and sometimes in the assessment of existing, or envisaged changes in, traffic noise conditions. In this research, traffic noise and other key parameters (traffic composition, traffic volume and speed) critical to traffic noise at the Central Business District of Ondo town were investigated. Data on traffic composition, traffic volume, speed and traffic noise levels were obtained and fitted into the Calculation of Road Traffic Noise (CoRTN) model which is a standard traffic noise prediction model. Data collected showed that the measured noise levels in equivalent noise level (Leq) for the study locations ranged between ۶۸ dB(A) and ۷۶ dB(A); these traffic noise levels exceed World Health Organization (WHO) and Federal Highway Administration (FHWA) permissible limit of ۵۵ dB(A) and ۶۰ dB(A) respectively. Results revealed that the (CoRTN) model showed efficient predictive capability when compared to measured noise levels with an acceptable coefficient of determination (R۲) value of ۰.۹۴۳.

CoRTN, Central Business District, Traffic noise, Ondo town