Road geometry estimation for vehicles

A system for determining a representation of one or more road objects of a road for a vehicle traveling on the road, the vehicle having one or more cameras, the system comprising one or more memory storage areas comprising program code, the one or more memory storage areas and the program code being configured to, with the one or more processors, cause the system to at least:

• for each time step out of a plurality of consecutive time steps:
• encode one or more images output from the one or more cameras using one or more machine-learning algorithms trained to output image features of one or more road objects depicted in an image provided as input to the one or more machine-learning algorithms;
• transform a plurality of image features comprised in the one or more encoded images to a Bird's Eye View (BEV) representation of the plurality of image features;
• decode the BEV representation in order to extract a set of object embeddings from the BEV representation using one or more transformer-based machine-learning algorithms trained to output the set of object embeddings based on an input comprising the BEV representation, a set of object queries, and a set of transformed prior object embeddings extracted at a preceding time step;
• output a position and class of each road object of the one or more road objects by decoding the extracted set of object embeddings.