Prediction and environmental appraisal of traffic noise intensity by auto-regressive integrated moving average technique

Abstract

Auto-regressive integrated moving average (ARIMA) assessment of traffic noise was conducted on different routes in Port Harcourt, Nigerian metropolis. This was achieved by measuring the traffic noise on the various routes of asphalt flexible and concrete rigid pavement structures with a meter for sound measurement with regards to the volume of traffic, vehicle movement rate, and location away from the midpoint of the highway. The average peak noise of traffic was obtained at selected distances of 5m, 10m, and 15m from the middle of the highway, for locations 1, 2, 3 and their mean average case 4 (Trunk A flexible pavement), for location 5 (Trunk C flexible pavement), and for location 6 (Trunk C rigid pavement). The results of the investigation show that the values of traffic noise at locations 1 to 3 and their mean average case 4 had the same range of high noise intensity as Trunk A flexible pavement and classified as heavy-traveled roads; while conversely, location 5 (Trunk C) had the same range of lower noise intensity, which was classified as light-traveled road. For Trunk C, the noise generated in a flexible pavement was less than that from a rigid pavement. Generally, the R2 values of the ARIMA models showed very good performance along selected travel routes. For case-specific distances, the ARIMA models performed very efficiently and had very high R2 values.