Non-stationary Road Research Articles

A predication method of probability distribution for nonstationary road traffic noise controlled by signals

A predication method of probability distribution for nonstationary road traffic noise controlled by signals

Multivariate probability expression of quantized state variables for a non-stationary system and its application to an acoustic environment

First, unified expressions of the joint probability function with quantized state variables for a non-stationary stochastic system and the joint factorial moments are found in a general form, including previous well-known results. These expressions are used in the development of a new method for estimating a level distribution over a long time interval on the basis of statistics obtained over a relatively short time interval, for linear vibratory systems. The validity of the theory is confirmed experimentally by applying it to non-stationary road traffic noise level fluctuation data.

A prediction theory of random level distribution based on a generalized difference type of Fokker-Planck equation and its application to environmental noise and vibration, II: Experimental study

In a companion paper [1], a procedure for solving the short time prediction problem in terms of the transition probability distribution has been theoretically derived, for discrete time-sampled data. Explicit algorithms for estimating the non-stationary moment statistics of arbitrary order also have been derived, based on a generalized difference equation of Fokker-Planck type for the conditional probability distributed function, which is central to the theory. In this paper, evidence for the validity and effectiveness of the proposed method is presented, as obtained not only by means of digital simulation but also by using road traffic noise data obtained experimentally in Hiroshima. For several non-stationary random processes simulated by means of random numbers, the theoretical and experimental conditional probability functions are compared. For non-stationary road traffic noise data the theoretically predicted and experimentally determined confidence intervals are compared; in these comparisons several types of conditional probability function and various values of weighting parameter are used in the algorithm. All of the theoretical results show good agreement with the experimental results.

An evaluation method for nonstationary random noise in view of temporal change of statistical moments (general theory and its application to probabilistic estimation problem of road traffic noise)

A unified statistical treatment of the probability distribution function is theoretically proposed in the case when a general random noise of arbitrary distribution type exhibits various type nonstationary properties due to the temporal change of statistical moments. For the purpose of finding the effect of nonstationarity caused by the temporal change of moments on the resultant probability distribution form, the explicit expression of the probability density function is derived in a general form of statistical expansion series taking the stationary term into the first term of series expansion. Next, a new trial of estimating a noise level distribution over a long time interval on the basis of level distribution within a short time interval is discussed, by using the above theoretical probability expression. The validity of the theoretical result is confirmed experimentally by applying it to the actual level data of the nonstationary road traffic noise observed in a large city.

A Unified Expression of the Multivariate Joint Probability Function of Quantized State Variables for a Non-Stationary Stochastic System and its Application to a Prediction Problem of Environmental Noise and Vibration Over a Long Time Interval

Initially the unified expressions of the joint probability function with quantized state variables for a non-stationary stochastic system and the joint factorial moments are ascertained in the general form. Next, by using the above expression, a new trial for estimating the level distribution over a long time interval, on the basis of a level distribution within a short time interval by the digital level measurement of the environmental noise or vibration system, is given from the theoretical viewpoint. The validity of this theory is confirmed by application to experimentally observed data of non-stationary road traffic noise level fluctuations.