Learning from All Vehicles

In this paper, we present a system to train driving policies from experiences collected not just from the ego-vehicle, but all vehicles that it observes. This system uses the behaviors of other agents to create more diverse driving scenarios without collecting additional data. The main difficulty in...

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Bibliographic Details
Main Authors: Chen, Dian, Krahenbuhl, Philipp
Format: Conference Proceeding
Language:English
Subjects:
Cognition
Computational modeling
Computer vision
Navigation
Navigation and autonomous driving
Pattern recognition
Task analysis
Training
Online Access:Request full text
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