Traffic Management for Smart Cities using Traffic Density and Swarm Algorithm to Inform Diversion Route
Mary N Peter1, M. Pushpa Rani2
1Mary N Peter, Research Scholar-Mother Theresa Women’s University Faculty, Department of Computer Science, Kristu Jayanti College, Bangalore.
2Dr. M. Pushpa Rani, Professor & Head, Department of Computer Science, Mother Theresa Women’s University, Kodaikkanal.
Manuscript received on January 26, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 3166-3171 | Volume-9 Issue-3, February 2020. | Retrieval Number: C5929029320/2020©BEIESP | DOI: 10.35940/ijeat.C5929.029320
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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: Number of vehicles increasing day by day in the world which results in traffic, air pollution, delay in reaching designation. Traffic density is increased in the roads, especially in the signals. The traffic congestion has negatively affected the efficiency, aggressiveness, and financial development of a nation. Thus, congestion control of traffic has become a significant zone of research, and a substantial number of answers for this issue left different research endeavors in the said field in recent decades. The traffic volume changing after some time, and in this way, long traffic lines are produced at the street intersections. Consequently, the Intelligent Transport System answers these related issues. It has incredible possible and ability to make transportation systems safe and smart efficiently. ITS provides the accessing and driving services of effortlessly participating transportation systems in a smart city. Traffic congestion can be managed in a proper manner by using time estimation and other route diversion in a pre-informed way. For this, we have to calculate the values of traffic congestion density and find the neighboring route. Density algorithm and distance measure algorithm were used to find the traffic density, and the Swarm algorithm was used to find the nearby path.
Keywords: IoT, Traffic analysis, Congestion control, Density Algorithm, and Swarm Intelligence