Application of the Hurst index to research the traffic flow intensity

Abstract

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.

Keywords

• traffic flow intensity
• time series
• rescaled range analysis
• hurst exponent