A Vehicle to Vehicle Communication Model for Collision Avoidance in Autonomous Cars
Isanga, Nadia Hanifa
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This project proposes a Vehicle-to-Vehicle (V2V) communication-based collision avoidance algorithm by delivering warning signals to the autonomous vehicle and controlling the driving wheel for the self-governed (autonomous) driving mode. The proposed algorithm benefits from the information exchange between the vehicles to calculate the safe distance and distance-tocollision between the host vehicle and leading vehicle to guarantee the avoidance of collision. The proposed system gives advisory and imminent warnings according to the different types of scenarios. For the implementation of this project, Newton’s laws of motion were used to model each of the three scenarios. A traffic inter-vehicle communication collision algorithm was proposed to prevent collisions for the three scenarios. Simulation of the scenarios was done in MATLAB and the proposed algorithms were used to see how the collision will be avoided. A Vehicular Ad-hoc Network (VANET) communication infrastructure based on the 5G Technology was modelled using software showing how the communication will occur between vehicles. The vehicles in the vehicular network can receive warning messages when a collision is about to occur and take necessary action. Using Vehicle-to-Vehicle communication based on 5G guarantees that the low latency requirement is met thus ensuring reliable communication between the cars and collision avoidance promptly. The proposed algorithms were tested for different scenarios to ensure the ability to avoid the collision in all these scenarios using MATLAB. Autonomous vehicles and vehicle to vehicle communication are both fields that will revolutionize the sector of transportation, making it safer and more ecofriendly. The exploration of this method of collision avoidance for other more complex collision safety scenarios that may not be as obvious as intersection movement assist and blind-spot is recommended.