Collision filtering based on segmentation data and object tracking

Abstract

Techniques for filtering candidate collisions with objects in an environment are discussed herein. A vehicle may receive sensor data representative of the environment. The vehicle can evaluate such sensor data and generate instance segmentation maps that represent the environment at a future time. The vehicle can determine instance prediction maps based on the instance segmentation maps and the velocity associated with the instances included therein. The vehicle can analyze such instance prediction maps to determine whether the vehicle is predicted to collide with any of the instances. Upon identifying a potential interaction, the vehicle can determine whether the instance is located, at a future instance prediction map that is prior to the map in which the potential interaction occurs, substantially behind the vehicle. Based on the instance being located behind the vehicle, the vehicle may filter out the potential interaction from further processing and control the vehicle accordingly.