Enhance the routing in self-driving cars using artificial and swarm intelligence algorithms

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This thesis paper concentrates on the analysis of the benefits of using swarm intelligence in the self-driven cars. Due to the large amount of data which must be processed and need more intelligence and cooperative way to find the best solution among many solutions to apply this technology and make it in practise. In this thesis IoT technologies and development which enable self-driven car listed, the communication methods have been reviewed and most common swarm intelligence algorithms has been discussed with the basic knowledge about the mathematical background for each algorithm. As the result of this thesis which focus on comparison between three swarm algorithms; Ant colony system, Elitist and Max-Min which based on swarm and cooperative between the vehicles to calculate the shortest path among different solution by this swarm way we will get shortest distance and less traffic which will cooperate in organizing the traffic and enhance the routing in self-driven car which led for more efficient way. By using Python to make benchmark between those algorithms we got 2D and 3D figures which disclose the idea behind some parameters which can make the algorithms more efficient with the same number of cooperated vehicles to calculate this distance.

Vehicle to vehicle communications using swarm intelligence, swarm intelligence, smart vehicle, self-driven cars