354 citations · 396 across the 23 of their papers we have counts for
4 papers · 1 filter
Learning Human Rewards by Inferring Their Latent Intelligence Levels in Multi-Agent Games: A Theory-of-Mind Approach with Application to Driving Data
Ran Tian, Masayoshi Tomizuka, Liting Sun
Reward function, as an incentive representation that recognizes humans' agency and rationalizes humans' actions, is particularly appealing for modeling human behavior in human-robo…
On complementing end-to-end human behavior predictors with planning
Liting Sun, Xiaogang Jia, Anca D. Dragan
High capacity end-to-end approaches for human motion (behavior) prediction have the ability to represent subtle nuances in human behavior, but struggle with robustness to out of di…
IDE-Net: Interactive Driving Event and Pattern Extraction from Human Data
Xiaosong Jia, Liting Sun, Masayoshi Tomizuka +1
Autonomous vehicles (AVs) need to share the road with multiple, heterogeneous road users in a variety of driving scenarios. It is overwhelming and unnecessary to carefully interact…
Interpretable Modelling of Driving Behaviors in Interactive Driving Scenarios based on Cumulative Prospect Theory
Liting Sun, Wei Zhan, Yeping Hu +1
Understanding human driving behavior is important for autonomous vehicles. In this paper, we propose an interpretable human behavior model in interactive driving scenarios based on…