Conference Paper

Collision detection of real-time autonomous vehicles is a cumbersome task due to the underlying point-cloud computations. To address this, we present an agile and efficient algorithm that is capable of detecting collisions between an ego-vehicle and other obstacles on the road. The proposed algorithm consists of a generalized spherical representation for the objects, which allows for a swift response from the ego-vehicle before an actual collision can occur. Experimental results were simulated using CARLA, Autoware and ROS 2 bridges. They indicate that the proposed approach is at least 200 times faster than Obstacle Collision Checker, a point cloud based algorithm in Autoware. Consistent mean elapsed times for collision detection are observed in the runs and its maximum dispersion is about $1/500 extsuperscript{th}$ of a microsecond.