16 citations · 27 across the 5 of their papers we have counts for
6 papers
Pictura: Perspective-View Self-Play at Scale for Driving
Yuan Yin, Elias Ramzi, Marc Lafon +8
Self-play in simulation produces robust driving policies at scale. Demonstrations of such behavior have been made using privileged vectorized observations such as exact poses and v…
Multiple-Frequencies Population-Based Training
Waël Doulazmi, Auguste Lehuger, Marin Toromanoff +3
Reinforcement Learning's high sensitivity to hyperparameters is a source of instability and inefficiency, creating significant challenges for practitioners. Hyperparameter Optimiza…
V-Max: A Reinforcement Learning Framework for Autonomous Driving
Valentin Charraut, Waël Doulazmi, Thomas Tournaire +1
Learning-based decision-making has the potential to enable generalizable Autonomous Driving (AD) policies, reducing the engineering overhead of rule-based approaches. Imitation Lea…
PLOP: Probabilistic poLynomial Objects trajectory Planning for autonomous driving
Thibault Buhet, Emilie Wirbel, Andrei Bursuc +1
To navigate safely in urban environments, an autonomous vehicle (ego vehicle) must understand and anticipate its surroundings, in particular the behavior and intents of other road…
Conditional Vehicle Trajectories Prediction in CARLA Urban Environment
Thibault Buhet, Emilie Wirbel, Xavier Perrotton
Imitation learning is becoming more and more successful for autonomous driving. End-to-end (raw signal to command) performs well on relatively simple tasks (lane keeping and naviga…
Imitation Learning for End to End Vehicle Longitudinal Control with Forward Camera
Laurent George, Thibault Buhet, Emilie Wirbel +2
In this paper we present a complete study of an end-to-end imitation learning system for speed control of a real car, based on a neural network with a Long Short Term Memory (LSTM)…