activity
20172022
most citedINTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps

354 citations · 488 across the 35 of their papers we have counts for

collaborators

35 papers

cs.RO2022★ 1 cited

Outracing Human Racers with Model-based Planning and Control for Time-trial Racing

Ce Hao, Chen Tang, Eric Bergkvist +4

Autonomous racing has become a popular sub-topic of autonomous driving in recent years. The goal of autonomous racing research is to develop software to control the vehicle at its…

cs.RO2022★ 20 cited

Transferable and Adaptable Driving Behavior Prediction

Letian Wang, Yeping Hu, Liting Sun +3

While autonomous vehicles still struggle to solve challenging situations during on-road driving, humans have long mastered the essence of driving with efficient, transferable, and…

cs.RO2021★ 11 cited

Hierarchical Adaptable and Transferable Networks (HATN) for Driving Behavior Prediction

Letian Wang, Yeping Hu, Liting Sun +3

When autonomous vehicles still struggle to solve challenging situations during on-road driving, humans have long mastered the essence of driving with efficient transferable and ada…

cs.RO2021★ 1 cited

Safety Assurances for Human-Robot Interaction via Confidence-aware Game-theoretic Human Models

Ran Tian, Liting Sun, Andrea Bajcsy +2

An outstanding challenge with safety methods for human-robot interaction is reducing their conservatism while maintaining robustness to variations in human behavior. In this work,…

cs.RO2021★ 2 cited

Anytime Game-Theoretic Planning with Active Reasoning About Humans' Latent States for Human-Centered Robots

Ran Tian, Liting Sun, Masayoshi Tomizuka +1

A human-centered robot needs to reason about the cognitive limitation and potential irrationality of its human partner to achieve seamless interactions. This paper proposes an anyt…

cs.RO2021★ 1 cited

Iterative Imitation Policy Improvement for Interactive Autonomous Driving

Zhao-Heng Yin, Chenran Li, Liting Sun +2

We propose an imitation learning system for autonomous driving in urban traffic with interactions. We train a Behavioral Cloning~(BC) policy to imitate driving behavior collected f…