| Abstrakt: |
It is undeniable that development is only possible with the help of technology. As a result, the advancement of autonomous technology has become the world's way of life. Robotic technology is rapidly expanding in intelligent cities and is now in full swing. Smart towns store and process all information effectively and efficiently by offering excellent service to all computer users via quality of service. So the offshoot of technological development is the ECAVS, the symbol of future growth. With the support of the most popular wireless network, VANET. The VANET is dynamic because of the movement of vehicles continuously from one place to another. These vehicles are purely autonomous or self-moving vehicles (Driverless vehicles) that are battery charged. But, one of the significant problems is traffic blocking or congestion on the roads. A situation comes where vehicles cannot move because of the lack of charging of the battery. V2V interaction becomes an obstacle for other vehicles with battery charging capacity in VANET, so their movement also gets obstructed. This situation is called starvation between the nodes results congestion. This paper proposes an algorithm to overcome this problem in self-balancing vehicles with more than two wheels, such as cars, buses, trucks, autos, and other ECAVTS vehicles. The proposed method is Collective Motion with a Finitely Generated Group (CMWFGG), which is a new hybrid optimization model that conceptually combines the Collective Motion algorithm (CM) with the Finitely Generated Groups (FGG) algorithm presented as a solution to this problem. The accepted CMFGG model's overall performance analysis was calculated using conventional schemes. [ABSTRACT FROM AUTHOR] |
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