1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.RO2021★ 1 cited
What data do we need for training an AV motion planner?
Long Chen, Lukas Platinsky, Stefanie Speichert +6
We investigate what grade of sensor data is required for training an imitation-learning-based AV planner on human expert demonstration. Machine-learned planners are very hungry for…
cs.RO2021
SimNet: Learning Reactive Self-driving Simulations from Real-world Observations
Luca Bergamini, Yawei Ye, Oliver Scheel +6
In this work, we present a simple end-to-end trainable machine learning system capable of realistically simulating driving experiences. This can be used for the verification of sel…
cs.CV2018
End-to-end driving simulation via angle branched network
Qing Wang, Long Chen, Wei Tian
Imitation learning for end-to-end autonomous driving has drawn attention from academic communities. Current methods either only use images as the input which is ambiguous when a ca…