Quantification of Traffic Congestion Based on Vehicular Speed under Heterogeneous Flow Conditions using Fuzzy Inference Model
S Varada Rajan1, N Pavan2, V Chitti Babu3
1S Varada Rajan, Assistant Professor, Department of Civil Engineering, Aditya Institute of Technology and Management (AITAM), Tekkali, Andhra Pradesh, India.
2N Pavan, M.Tech student, Department of Civil Engineering, Aditya Institute of Technology and Management (AITAM), Tekkali, Andhra Pradesh, India.
3V Chitti Babu, Professor, Department of Mechanical Engineering, Aditya Institute of Technology and Management (AITAM), Tekkali, Andhra Pradesh, India.
Manuscript received on 04 May 2021 | Revised Manuscript received on 07 May 2021 | Manuscript Accepted on 15 May 2021 | Manuscript published on 30 May 2021 | PP: 21-27 | Volume-1 Issue-1, May 2021 | Retrieval Number: 100.1/ijte.A2302051121
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© The Authors. Published by Lattice Science Publication (LSP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Traffic congestion is a condition on transport networks that occurs as use increases, and is characterized by slower speeds, longer trip times, and increased vehicular queuing. In simple words, “the ability of a vehicle to move forward in a traffic state” defines congestion. Traffic congestion has become a serious problem in the urban districts. In heterogeneous flow like India, congestion impacts the movement of people both in perception and in reality that leads to consumption of time, energy and also leads to the pollution. In order to save precious human life, eliminate road accidents and the essence factor called time, it is essential to ensure a proper measure for traffic congestion. Earlier there were several attempts made to develop different approaches for congestion analysis. At present the congestion levels of ten different road stretches of Visakhapatnam city within the Central Business District (CBD) area. The main aim of this study is to introduce a versatile fuzzy logic traffic flow model that is capable of making optimal traffic prediction to identify the congestion levels of the city by considering the factors like vehicle volume, average speed and road speed limits by using MATLAB and to generate the desired congestion index of the specified study stretches. This study lays the foundation for traffic congestion prediction, early warning & proactive alleviation of traffic congestion.
Keywords: Level of Service, MATLAB, Membership Functions, Fuzzy Logic, Linguistic Variables.