Wavelet Analysis as a Tool for Studying the Road Traffic Characteristics in the Context of Intelligent Transport Systems with Incomplete Data

Golovnin, Oleg; Stolbova, Anastasia

doi:10.15622/sp.18.2.326-353

Cited by 6 publications

(4 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Временные ряды случайных процессов представляют собой особый класс функций, которые проявляют свойства фрактальности. Аппроксимация мультифракталами контактных поверхностей оказалось целесообразной при контроле и оценке шероховатости поверхностей рессор и полимерных вкладышей шаровых опор [13]. С помощью показателя Хёрста установлено [47], что закономерность появлениями автомобилей на магистралях проявляет фрактальные свойства.…”

Section: обзор литературыunclassified

Traffic Congestion Characteristics Based on Data of the Photo and Video Recording System

Boyarshinov,

Vavilin

2023

I.I.I

View full text Add to dashboard Cite

The relevance of the present paper is justified by the need to search for a scientifically based criterion for the formation, development and elimination of traffic congestion using modern highly efficient mathematical methods of information processing. It seems necessary to study the results of using the rescaled range, statistical, fractal, harmonic, and wavelet analysis of time series formed by the time (duration) of the movement of cars in a stream along a road section in the absence and presence of traffic congestion. The object of study is a section of the road network equipped with a software and hardware complex that allows measuring the characteristics of any car in the flow of transport. The subject of the study is the patterns of changes in the duration of movement of individual cars in the absence and presence of a congestion situation. The purpose of this study is a quantitative indicator of the formation, evolution, and elimination of traffic congestion. The basis of the theoretical and methodological approach is the use of modern highly efficient mathematical methods for processing information about traffic flows received from stationary complexes of photo and video recording of traffic violations. As a result of the study of time series, decompositions of the analyzed time series by harmonics and wavelets are constructed, statistical and fractal characteristics of the time series under consideration are determined. The analysis of the obtained results is carried out, the features of the obtained dependencies are revealed. The theoretical and practical significance of the work lies in the scientific substantiation of the quantitative characteristics of traffic congestion, which is of practical interest from the point of view of predicting anomalies in the movement of vehicles on the road network, making decisions on managing the operation of traffic lights, etc. The direction of further research is an in-depth analysis of the identified indicator and determination on its basis of a criterion for determining the stages of formation, evolution, and elimination of traffic congestion at intersections of the street and road network of a large industrial city.

show abstract

Section: обзор литературыunclassified

Traffic Congestion Characteristics Based on Data of the Photo and Video Recording System

Boyarshinov,

Vavilin

2023

I.I.I

View full text Add to dashboard Cite

show abstract

“…В [7] предлагается подход к автоматическому обнаружению и классификации дефектов дороги по изображениям, основанный на анализе особенностей формы и текстуры. В [8,9,10]…”

Section: детектирование локальных нарушений ровности покрытия автодор...unclassified

Detection of Local Irregularities in the Road Pavement on the Basis of Wavelet Transform of Ultrasonic Profiling Data

Stolbova¹,

Prokhorov²,

Golovnin³

2021

Journal of Dynamics and Vibroacoustics

View full text Add to dashboard Cite

The paper presents an approach to the detection of road pavement defects on the streets and highways based on wavelet analysis of data obtained from an ultrasonic profilometer. The approach makes it possible to determine the location of pavement defects in relation to the road lane. The results of implementing the approach using the complex Morlet wavelet and the first derivative of the Gaussian function are presented. Implementation of the approach reduces the influence of interference arising during ultrasonic diagnosis.

show abstract

“…Внедрение и использование технических средств видеофиксации нарушений правил дорожного движения [17,28] позволило собирать и анализировать в режиме реального времени огромные массивы информации («big data» [27]) о развитии во времени основных показателей движения транспортных потоков по улично-дорож-ной сети для различных временных интервалов, на отдельных участках дорог и их пересечений, формировать матрицы корреспонденций и проч. Одним из инструментов исследования потоков транспорта может оказаться вейвлет-анализ [6].…”

Section: Introductionunclassified

Fourier Analysis of the Traffic Flow Intensity

Boyarshinov¹,

Vavilin²,

Shumkov³

2021

I.I.I

View full text Add to dashboard Cite

The relevance of this work is determined by the need to find modern ways to process the information about traffic flows for regulating and controlling the movement of transport and pedestrians, to reduce congestion, road accidents, etc. The object of study is a part of road with heavy two-way traffic, equipped with a software and hardware complex that allows to measure the characteristics of the transport flow. 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 analyze the amplitudes, frequencies, and periods of harmonic functions obtained by decomposing the time series of road traffic intensities to identify the main patterns of traffic flow formation. As a theoretical and methodological approach, the decomposition of the function of the traffic flow intensity in the Fourier series with respect to harmonic functions is used. The approach developed by the authors using the fast Fourier transform procedure made it possible to determine the amplitude-frequency characteristics of the time series under consideration, which is a scientific novelty of the analysis. It is proposed to use the «period-amplitude» characteristics as physically more meaningful instead of the «frequency-amplitude» dependencies traditionally used for the analysis. The processing of data obtained from software and hardware complexes allowed us to determine dependences of the car flow intensity on the road of the Perm city at different averaging intervals, to describe the features of the motor transport movement on the road under consideration. As a result of the study, the amplitude-frequency characteristics of time series are obtained. It is shown that the individual harmonics of the Fourier series expansion of the traffic flow intensity, which exhibits the properties of a random function, duplicate the periodicity of the global, local, and intermediate extremes of the original function and have similar periods. The practical significance consists in the use of the decomposition of the function of the traffic flow intensity in the Fourier series of harmonic functions for predicting traffic flows, controlling the operation of traffic lights, monitoring the operation of equipment, as well as in the reconstruction, design and construction of roads and road objects. The study will continue in the direction of obtaining, processing and determining the «period-amplitude» characteristics for time series of traffic flow intensity for other road networks.

show abstract

Wavelet Analysis as a Tool for Studying the Road Traffic Characteristics in the Context of Intelligent Transport Systems with Incomplete Data

Cited by 6 publications

References 0 publications

Traffic Congestion Characteristics Based on Data of the Photo and Video Recording System

Traffic Congestion Characteristics Based on Data of the Photo and Video Recording System

Detection of Local Irregularities in the Road Pavement on the Basis of Wavelet Transform of Ultrasonic Profiling Data

Fourier Analysis of the Traffic Flow Intensity

Contact Info

Product

Resources

About