Assessing traffic noise impact based on probabilistic and fuzzy approaches under uncertainty

Traffic noise can cause severe sound pollution for human communities. This paper proposes a hybrid approach to assess traffic noise impact under uncertainty. There are many factors influencing traffic noise level, but only three traffic parameters, namely, traffic flow, traffic speed and traffic component, are highly uncertain. These uncertain parameters are represented by probability distributions, and Monte Carlo simulations are performed to generate a noise distribution after considering about other certain influencing factors. Fuzzy set and binary fuzzy relations as well as probability analysis method are applied to identify the predicted traffic noise impacts in qualitatively and quantitatively. The applicability of this proposed technique is demonstrated using a case study.