4 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.RO2021
SafetyNet: Safe planning for real-world self-driving vehicles using machine-learned policies
Matt Vitelli, Yan Chang, Yawei Ye +7
In this paper we present the first safe system for full control of self-driving vehicles trained from human demonstrations and deployed in challenging, real-world, urban environmen…
cs.RO2021★ 4 cited
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…