Learning Realistic Traffic Agents in Closed-loop

Learning Realistic Traffic Agents in Closed-loop

2 November 2023

Papers citing "Learning Realistic Traffic Agents in Closed-loop"

9 / 9 papers shown

Title
RIFT: Closed-Loop RL Fine-Tuning for Realistic and Controllable Traffic Simulation Keyu Chen Wenchao Sun Hao Cheng Sifa Zheng 30 0 0 06 May 2025
Promptable Closed-loop Traffic Simulation Shuhan Tan B. Ivanovic Yuxiao Chen Boyi Li Xinshuo Weng Yulong Cao Philipp Krahenbuhl Marco Pavone 18 5 0 09 Sep 2024
CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning Luke Rowe Roger Girgis Anthony Gosselin Bruno Carrez Florian Golemo Felix Heide Liam Paull Christopher Pal 36 4 0 29 Mar 2024
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 301 11,730 0 04 Mar 2022
AW-Opt: Learning Robotic Skills with Imitation and Reinforcement at Scale Yao Lu Karol Hausman Yevgen Chebotar Mengyuan Yan Eric Jang ... Ted Xiao A. Irpan Mohi Khansari Dmitry Kalashnikov Sergey Levine OffRL 85 60 0 09 Nov 2021
Learning to drive from a world on rails Di Chen V. Koltun Philipp Krahenbuhl 92 99 0 03 May 2021
Imagining The Road Ahead: Multi-Agent Trajectory Prediction via Differentiable Simulation Adam Scibior Vasileios Lioutas Daniele Reda Peyman Bateni Frank D. Wood VGen 40 36 0 22 Apr 2021
TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors Simon Suo S. Regalado Sergio Casas R. Urtasun 136 221 0 17 Jan 2021
Implicit Latent Variable Model for Scene-Consistent Motion Forecasting Sergio Casas Cole Gulino Simon Suo Katie Z Luo Renjie Liao R. Urtasun 145 135 0 23 Jul 2020