Markov Chain Modelling and GIS Interface to Analyze Traffic Congestion
Madduri Swathikiran1, R. Archana Reddy2, G. Sahithi3, N. Prabhanjan4, G. Swamy Yadav5, D. Swetha6
1Madduri Swathikiran*, Assistant Professor, S R Engineering College, Warangal, Telangana, India.
2Dr. R. Archana Reddy, Professor, S R Engineering College, Warangal, Telangana, India.
3G. Sahithi, Assistant Professor, S R Engineering College, Warangal, Telangana, India.
4N. Prabhanjan, Assistant Professor, S R Engineering College, Warangal, Telangana, India.
5G. Swamy Yadav, Assistant Professor, S R Engineering College, Warangal, Telangana, India.
6D. Swetha, Assistant Professor, S R Engineering College, Warangal, Telangana, India.
Manuscript received on December 16, 2019. | Revised Manuscript received on December 28, 2019. | Manuscript published on January 10, 2020. | PP: 2921-2927 | Volume-9 Issue-3, January 2020. | Retrieval Number: C8642019320/2020©BEIESP | DOI: 10.35940/ijitee.C8642.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). 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 the major problem that major metropolitan cities are facing. From the study it is observed that the main cause of the delay is because of not following the actual design of the transportation rules of the particular area. There are many factors which are influencing the congestion are taken in the study like road density, road geometrics and traffic composition. Data is collected at Gochibowli, Kothagudem and Cyber towers intersection regarding road geometrics, road density and volume count using ArcGIS and manually. The Markov chain is a mathematical model is used. Markov chain is a transition probabilistic model which can be used in any stream to find out percentage of chances for an event to take place. Empirical model is developed for delay prediction by considering the values from data collection. Penetrating the values into the transition probabilistic method and linear equations to find out the factors influencing delay and calculating the delay errors.
Keywords: Traffic Congestion, Markov Chain Analysis, Transition Probability, Delay Studies.
Scope of the Article: Network Traffic Characterization and Measurements