Exploring Data Aggregation in Policy Learning for Vision-Based Urban Autonomous Driving

Data aggregation techniques can significantly improve vision-based policy learning within a training environment, e.g., learning to drive in a specific simulation condition. However, as on-policy data is sequentially sampled and added in an iterative manner, the policy can specialize and overfit to...

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Bibliographic Details

Published in:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) pp. 11760 - 11770
Main Authors:	Prakash, Aditya, Behl, Aseem, Ohn-Bar, Eshed, Chitta, Kashyap, Geiger, Andreas
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.01.2020
Subjects:	Autonomous vehicles Data aggregation Supervised learning Task analysis Training Trajectory Uncertainty
ISSN:	1063-6919
Online Access:	Get full text
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