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Optimization of Smart Traffic Governance System Using Artificial Intelligence

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Abstract

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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Authors and Affiliations

  1. Department of Computer Engineering, Gandhinagar Institute of Technology, Gandhinagar, Gujarat, India

    Aayush Sukhadia & Smit Shah

  2. Department of Computer Engineering, LDRP Institute of Technology and Research, Gandhinagar, Gujarat, India

    Khush Upadhyay

  3. Department of Electronics and Communications Engineering, Government Engineering College, Gandhinagar, Gujarat, India

    Meghashree Gundeti

  4. Department of Chemical Engineering, School of Technology, Pandit Deendayal Petroleum University, Gandhinagar, Gujarat, India

    Manan Shah

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  1. Aayush Sukhadia
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  2. Khush Upadhyay
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  3. Meghashree Gundeti
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  4. Smit Shah
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  5. Manan Shah
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Contributions

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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