Abstract
by 2050, 70% of the world population is estimated to migrate toward the city, covering just 2% of the earth’s surface. This leads to many issues, and traffic congestion is one among them. To continue to serve and improve the life of the growing population, it is mandatory to develop an advanced medium to avoid risks which are likely to occur as a result of overcrowded traffic. Our motive is to develop an autonomous vehicle to free human drivers and thus increasing their safety. The Self-driving autonomous vehicles have intensely become one of the great discovery in the field of technology. Different technologies like deep learning, Artificial Intelligence (AI), etc. are merged with each other and with the smart sensors (SS) to develop this self-driven autonomous vehicle. Computer Vision and Deep Learning techniques are applied to build an automotive related algorithm. This project uses Computer Vision Techniques to identify lane lines on a road and also able to identify 40+ different traffic signals. In this project, we will explore the smart city (SMC) concept and propose a strategy development model that will mitigate the traffic concern issues by implementing traffic management system (TMS) using SS network in a SMC context.
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