205 citations · 213 across the 6 of their papers we have counts for
3 papers · 1 filter
DriverGym: Democratising Reinforcement Learning for Autonomous Driving
Parth Kothari, Christian Perone, Luca Bergamini +2
Despite promising progress in reinforcement learning (RL), developing algorithms for autonomous driving (AD) remains challenging: one of the critical issues being the absence of an…
Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients
Oliver Scheel, Luca Bergamini, Maciej Wołczyk +2
In this work we are the first to present an offline policy gradient method for learning imitative policies for complex urban driving from a large corpus of real-world demonstration…
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…