Since AVs would be the next generation’s most common type of commute, and Internet of Things invading the world, there exists a scope for coupling both to form a robust information grid and expose it to the AVs. Thus the aims and objectives of this study is to test the incorporation of an AV into a connected world via cellular automata (CA) and Ludo Cellular Automata along with a Dijkstra’s routing logic to help it find its best route in a dynamic environment. CA divides the path into cells and each one have a set of static and dynamic parameters. The route finding system in the AV, once navigating in the cells would collect information about the present state of the cells and updates the grid. A random AV trying to find a best route would be able to use this information to plan its route avoiding obstructions based on the information available on the CA grid. The LCA introduces a bias which regulates the acceleration of the AV. This causes the AV avoid erratic and useless acceleration and braking.
The expected result was an AV dynamically rerouting its path based on the actual condition or state of the cells in front of it. Optimized acceleration and braking which was found to saves energy. The path was optimized by driving on the cheapest route or the next cheapest route in case of obstructions. With this novel approach, the different autonomous transportation systems could be improved and integrated into a Ludo Cellular Automata grid to limit traffic jams as the system tries to diverge vehicles from an obstructed node.
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