Driving in Real Life with Inverse Reinforcement Learning

no code implementations • 7 Jun 2022 • Tung Phan-Minh, Forbes Howington, Ting-Sheng Chu, Sang Uk Lee, Momchil S. Tomov, Nanxiang Li, Caglayan Dicle, Samuel Findler, Francisco Suarez-Ruiz, Robert Beaudoin, Bo Yang, Sammy Omari, Eric M. Wolff

In this paper, we introduce the first learning-based planner to drive a car in dense, urban traffic using Inverse Reinforcement Learning (IRL).

Autonomous Driving Imitation Learning +2

Failure-Tolerant Contract-Based Design of an Automated Valet Parking System using a Directive-Response Architecture

no code implementations • 24 Mar 2021 • Josefine Graebener, Tung Phan-Minh, Jiaqi Yan, Qiming Zhao, Richard M. Murray

Increased complexity in cyber-physical systems calls for modular system design methodologies that guarantee correct and reliable behavior, both in normal operations and in the presence of failures.

Counter-example Guided Learning of Bounds on Environment Behavior

1 code implementation • 20 Jan 2020 • Yuxiao Chen, Sumanth Dathathri, Tung Phan-Minh, Richard M. Murray

There is a growing interest in building autonomous systems that interact with complex environments.

CoverNet: Multimodal Behavior Prediction using Trajectory Sets

2 code implementations • CVPR 2020 • Tung Phan-Minh, Elena Corina Grigore, Freddy A. Boulton, Oscar Beijbom, Eric M. Wolff

We instead frame the trajectory prediction problem as classification over a diverse set of trajectories.

regression Trajectory Prediction