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Smart Traffic Management System for Traffic Control using Automated Mechanical and Electronic Devices
Mamata Rath 1
Published under licence by IOP Publishing Ltd IOP Conference Series: Materials Science and Engineering , Volume 377 , International Conference on Mechanical, Materials and Renewable Energy 8–10 December 2017, Sikkim, India Citation Mamata Rath 2018 IOP Conf. Ser.: Mater. Sci. Eng. 377 012201 DOI 10.1088/1757-899X/377/1/012201
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1 Dept. of I.T, C.V.Raman College of Engineering, Bhubaneswar, India
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In the current context of smart city, specifically in the industrial and market zones, the traffic scenario is very congested most of the time particularly at the peak time of business hours. Due to increasing growth of population and vehicles in smart and metropolitan cities people face lot of problem at the major traffic points of the business towns. Not only it causes travelling delays, it also contributes to environmental pollution as well as health hazards due to pollution caused by vehicle fuels.To keep away from such severe issues many radiant urban communities are right now implementing smart traffic control frameworks that work on the standards of traffic automation with prevention of the previously mentioned issues. The fundamental concept lies in collection of traffic congestion information quickly and passing the alternate strategy to vehicles as well as passengers with on-line traffic information system and effectively applying it to specific traffic stream. In this context, an enhanced traffic control and monitoring framework has been proposed in the present article that performs quick information transmission and their corresponding action. In the projected approach, under a Vehicular Ad-hoc Network (VANET) scenario, the mobile agent based controller executes a congestion control algorithm to uniformly organize the traffic flow by avoiding the congestion at the smart traffic zone. It exhibits other unique features such as prevention of accidents, crime, driver flexibility and security of the passengers. Simulation carried out using Ns2 simulator shows encouraging results in terms of better performance to control the delay and prevent any accident due to profound congestion up to a greater extent.
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Optimization of Smart Traffic Governance System Using Artificial Intelligence
- Original Paper
- Published: 29 March 2020
- Volume 5 , article number 13 , ( 2020 )
Cite this article
- Aayush Sukhadia 1 ,
- Khush Upadhyay 2 ,
- Meghashree Gundeti 3 ,
- Smit Shah 1 &
- Manan Shah 4
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35 Citations
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Traffic system shows a great scope of trade with the environment and is directly connected to it. Manual traffic systems are proving to be insufficient due to rapid urbanization. Central monitoring systems are facing scalability issues as they process increasing amounts of data received from hundreds of traffic cameras. Major traffic problems include congestion, safety, pollution (leading to various health issues) and increased need for mobility. A solution to most of them is the construction of newer and safer highways and additional lanes on existing ones, but it proves to be expensive and often not feasible. Cities are limited by space, and construction cannot keep up with ever-growing demand. Hence, a need for an improved system with a minimal manual interface is persisting. One of such methods is introduced and discussed in this paper; smart traffic governance system here used artificial intelligence to regulate and govern the course of transport and automated administration and implementation to make a difference in face of travel scenarios in urban cities suffering from such major traffic issues.
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Acknowledgements
The authors are grateful to School of Technology, Pandit Deendayal Petroleum University, Gandhinagar Institute of Technology, LDRP Institute of Technology, Government Engineering College for the permission to publish this research.
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Department of Computer Engineering, Gandhinagar Institute of Technology, Gandhinagar, Gujarat, India
Aayush Sukhadia & Smit Shah
Department of Computer Engineering, LDRP Institute of Technology and Research, Gandhinagar, Gujarat, India
Khush Upadhyay
Department of Electronics and Communications Engineering, Government Engineering College, Gandhinagar, Gujarat, India
Meghashree Gundeti
Department of Chemical Engineering, School of Technology, Pandit Deendayal Petroleum University, Gandhinagar, Gujarat, India
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All the authors make substantial contribution in this manuscript. AS, KP, MG, SS, and MS participated in drafting the manuscript. AS, KU, MG and SS wrote the main manuscript, and all the authors discussed the results and implication on the manuscript at all stages.
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Correspondence to Manan Shah .
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Sukhadia, A., Upadhyay, K., Gundeti, M. et al. Optimization of Smart Traffic Governance System Using Artificial Intelligence. Augment Hum Res 5 , 13 (2020). https://doi.org/10.1007/s41133-020-00035-x
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Received : 15 November 2019
Revised : 28 January 2020
Accepted : 12 March 2020
Published : 29 March 2020
DOI : https://doi.org/10.1007/s41133-020-00035-x
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The proposed work focuses on Smart Traffic management. System using RFID which will eliminate th e drawbacks of the. existing system such as high implementation cost, dependency. on the environm ...
Introduction Despite all the research carried out in the field of traffic management, road congestion remains a real headache for managers and road users alike. The main reason behind this is the continuous and faster increase in the number of * Corresponding author. Tel.: +212 6 43 12 13 77.
PDF | On Dec 1, 2019, Abubakar M. Miyim and others published Smart Traffic Management System | Find, read and cite all the research you need on ResearchGate
In addition to traffic signal lightings, the system alarms on any false vehicle activities such as crossing the red signals. In another research, an IoT based smart traffic management system is proposed [29] to manage real-time traffic through both central and local servers. The data collection layer uses sensors, cameras, and RFIDs.
In this way, focusing on preventing traffic congestion and improving the overall traffic efficiency, large cities rely on traffic management systems (TMSs), 1-3 which aim to reduce traffic congestion and its related problems. To this end, TMSs are composed of a set of applications and management tools to integrate communication, sensing and processing technologies. 1 In summary, TMSs collect ...
Traffic Clog is the main issue of the fast and evolving world. Due to the rise in the use of more private vehicles and low road network capacity managing traffic with the traditional approach is cumbersome. Pollution and productivity of individuals are highly affected due to traffic. The use of mundane methods may not be an efficient and significant solution for varying traffic congestion ...
IOP Conference Series: Materials Science and Engineering. Paper • The following article is Open access. A Review on Smart Traffic Management System. P Indhiradevi1, P Saravanakumar2, R Varsha3, S Shahithya3 and S Naveen Prabhu3. Published under licence by IOP Publishing Ltd IOP Conference Series: Materials Science and Engineering , Volume ...
This paper presents a comprehensive overview of a Smart Traffic Management System (STMS) designed to optimize traffic flow, enhance safety, and minimize congestion in urban areas. The STMS leverages advanced technologies such as artificial intelligence, sensor networks, and data analytics to create a dynamic and adaptive traffic control ...
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The proposed control system uses cameras and sensors for a smart traffic management system. This includes automated detection, analysis, and data representation, as depicted in Fig. 1. First, sensors and cameras will be installed at strategic locations such as traffic signals or railway gates, where they will gather information about traffic flow, particularly regarding vehicles.
The emergence of smart cities has addressed many critical challenges associated with conventional urbanization worldwide. However, sustainable traffic management in smart cities has received less attention from researchers due to its complex and heterogeneous nature, which directly affects smart cities' transportation systems. The study aimed at addressing traffic-related issues in smart ...
Millions of vehicles pass via roads and cities every day. Various economic, social and cultural factors affect growth of traffic congestion. The effect of traffic congestion has major impacts on accidents, loss of time, cost, delay of emergency, etc. Due to traffic congestions there is a loss in productivity from workers, people lose time, trade opportunities are lost, delivery gets delayed ...
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Paper • The following article is Open access. Smart Traffic Management System for Traffic Control using Automated Mechanical and Electronic Devices ... caused by vehicle fuels.To keep away from such severe issues many radiant urban communities are right now implementing smart traffic control frameworks that work on the standards of traffic ...
The implementation of a Smart Traffic Control Management System utilizing AI yields significant and multifaceted results, bringing about transformative changes in urban transportation dynamics. This section discusses the key outcomes and implications of integrating AI into traffic control.
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