Dynamics-Aware Spatiotemporal Occupancy Prediction in Urban Environments
Maneekwan Toyungyernsub,Esen Yel,Jiachen Li,Mykel J. Kochenderfer,Maneekwan Toyungyernsub,Esen Yel,Jiachen Li,Mykel J. Kochenderfer
Detection and segmentation of moving obstacles, along with prediction of the future occupancy states of the local environment, are essential for autonomous vehicles to proactively make safe and informed decisions. In this paper, we propose a framework that integrates the two capabilities together using deep neural network architectures. Our method first detects and segments moving objects in the s...
