Collision avoidance algorithm based on vehicle to vehicle (V2V) communication for autonomous vehicles.

Abstract

In Uganda, the accident severity index is 24 people killed per 100 road crashes. On average, ten people die per day in road traffic crashes which is the highest in East Africa. Many roads in Uganda are very unsafe with few opportunities of overtaking among other shortcomings, resulting into collisions that could otherwise be avoided. Autonomous (self-driving) cars promise to improve traffic safety especially by reducing the rate of car collisions among other safety measures. Autonomous cars depend on numerous sensing technologies to ensure the safety is achieved. Of recent Vehicle-to-Vehicle communication (V2V) built on the 5G network is an emerging technology of interest as it allows equipped vehicles to sense each other and infrastructure even where the other sensors fail. In this project, a collision avoidance algorithm is developed that benefits from the information shared between the leading vehicle and the following vehicle using V2V communication for autonomous vehicles. Using the information shared, the following car is able to detect a collision and consequently mitigate it. The project also studies the Signal-to-Interference-plus-Noise Ratio (SINR) distribution within the small cells for V2V, specifically ascertaining the effect of cell radius on the SINR levels. It is observed that the larger the cell radius, the higher the SINR levels hence the more reliable the communication link.