Application of the wavelet analysis to research the traffic flow intensity

The relevance of the work is the specific properties of the wavelet analysis, which make it possible to identify not only the amplitude-scale (frequency) characteristics of the time series under consideration, but also the evolution of these characteristics during the observation time. As a result of the study, it is advisable to identify those indicators of the intensity of traffic flow that may turn out to be indicators of possible problematic situations (congestion, traffic accidents, etc.). It is advisable to use them in the future when regulating and controlling traffic on the basis of processing information about traffic flows that comes from stationary video recording complexes of traffic violations. The object of study is a road with intensive one-way traffic, equipped with a software and hardware complex that allows measuring the characteristics of the flow of motor transport. The subject of the study is the daily intensity of the flow of cars. The purpose of this study is to identify patterns in the indicators evolution obtained using wavelet analysis as a result of processing of the time series of the car traffic intensity on the road network. As a theoretical and methodological approach, the wavelet transforms using the MHat wavelet, and the Morlet wavelet is used. The approach used by the authors allowed us to establish the correspondence of some characteristics obtained during the wavelet analysis with the evolution of the traffic flow intensity function during the daily observation time, which is the scientific novelty of the study. The wavelet analysis of the data of the video surveillance software and hardware complexes obtained during the day allowed us to construct time dependences of amplitude-scale (frequency) indicators of the car traffic intensity on the road connecting the central and rear areas of the city of Perm. As a result of the study of time series, experimental three-dimensional distributions of wavelet images, scalograms, skeletons and scalegrams of the function of the daily intensity of the traffic flow were obtained. An explanation of the characteristic features of the obtained dependencies and their relationship with the initial function of the traffic flow intensity is proposed. The practical significance lies in obtaining amplitude-scale (frequency) characteristics as a result of wavelet analysis of the traffic intensity using MHat and Morlet wavelets, which is of practical interest from the point of view of predicting the movement of vehicles, controlling the operation of traffic lights, monitoring the operation of equipment, etc. The direction of further research is to obtain, process, analyze and generalize the results of performing amplitude-scale wavelet analysis for time series of traffic flow intensity on parts of the road network with different vehicle traffic intensity

Application of the Hurst index to research the traffic flow intensity

The relevance of the work is due to the predictive properties of the Hurst indicator (index), which make it possible to identify the presence/absence of a trend in the observed stochastic process, which it is advisable to use when regulating and controlling traffic to reduce congestion, traffic accidents based on processing information about traffic flows coming from stationary video recording complexes of traffic violations. The object of investigation is a section of road with intensive one-way traffic, equipped with a software and hardware complex that allows measuring the characteristics of the flow of motor transport. The subject of the study is the daily intensity of the cars flow during the week, from Monday to Sunday. The purpose of this study is to identify the patterns of evolution of the indicators included in the Hurst index, based on the processing of time series of the intensity of motor transport traffic on the road network. As a theoretical and methodological approach, the rescaled range analysis, or the definition of Hurst exponent, is used. The approach developed by the authors allowed us to establish the regularities of the evolution of mean values, standard deviations, accumulated and rescaled range, Hearst exponents, which is the scientific novelty of the performed analysis. Data processing of video surveillance software and hardware complexes made it possible to construct time-dependent indicators of the intensity of car traffic on a road with a consistently high flow of vehicles connecting the central and remote areas of the city of Perm, at various intervals of averaging by days of the week. As a result of the study of time series, dependences on the time of average values, standard deviations, accumulated and rescaled ranges, Hearst exponents were obtained. It is shown that the found characteristics of the traffic flow intensity on a road with a high traffic intensity differ significantly from similar characteristics obtained earlier for roads with a relatively low intensity. The practical significance lies in the use of predictive properties of the Hurst indicator in analyzing the intensity of the flow of vehicles for predicting the movement of vehicles, controlling the operation of traffic lights, monitoring the operation of equipment, etc. The direction of further research is to obtain, process and determine rescaled ranges and Hurst exponents for time series of traffic flow intensity on other sections of the road network