Analysis of Self-similar Nature Vehicle Arrival Data Pattern on Arterial Roads

Abstract

Abstract Traffic congestion is a main criterion of increasing the disturbance of the movements of traffic on roads. In various metropolitan areas managing the traffic congestion is a difficult task, it was investigated that busy traffic reveals self-similarity, influenced by this aspect, realtime road traffic arrival data pattern proven as self-similar paradigm by means of disparate Hurst index methods. The current article furnishes various proficiency used to measure Hurst index which is popular demarcate of self-similar behavior traffic. In this paper, real time data is used to investigate the pattern of vehicular arrival data traffic flow at Mancherial Chowrasta intersection of Karimnagar City. Traffic arrival data patterns are recorded from location is processed and analyzed using Hurst index method named as correlogram. Quantitative results finally reveal that analysis shown in this study is supportive to manage the traffic signals at that junction, and to discover methods to avoid congestion traffic streams.