Vehicle Motion Forecasting Using Prior Information and Semantic-Assisted Occupancy Grid Maps
Rabbia Asghar,Manuel Diaz-Zapata,Lukas Rummelhard,Anne Spalanzani,Christian Laugier,Rabbia Asghar,Manuel Diaz-Zapata,Lukas Rummelhard,Anne Spalanzani,Christian Laugier
Motion prediction is a challenging task for autonomous vehicles due to uncertainty in the sensor data, the non-deterministic nature of future, and complex behavior of agents. In this paper, we tackle this problem by representing the scene as dynamic occupancy grid maps (DOGMs), associating semantic labels to the occupied cells and incorporating map information. We propose a novel framework that co...
