18 citations · 23 across the 13 of their papers we have counts for
8 papers · 1 filter
Behavioral Safety Assessment towards Large-scale Deployment of Autonomous Vehicles, Part II: Assessment Results
Henry X. Liu, Tinghan Wang, Xintao Yan +6
Third-party evaluations of autonomous vehicle (AV) safety can play a vital role in improving public acceptance, building consumer confidence, and establishing effective safety stan…
Behavioral Safety Assessment towards Large-scale Deployment of Autonomous Vehicles, Part I: Methodology
Henry X. Liu, Tinghan Wang, Xintao Yan +6
Autonomous vehicles (AVs) have significantly advanced in real-world deployment in recent years, yet safety continues to be a critical barrier to widespread adoption. Traditional fu…
Human Behavior-Informed Crash Scenario Generation with Real-World Crash Priors for Autonomous Vehicle Safety Evaluation
Mingxing Peng, Xusen Guo, Long Chen +3
Reliable safety evaluation of autonomous vehicles (AVs) is essential to improving road safety, yet it depends critically on realistic simulation of rare crashes. Existing crash sce…
Copper-Policy: Focus on the Representation for Robust Robot Manipulation
Zexin Feng, Yixu Feng, Lingyu Xiao +6
World Action Models (WAMs) acquire behavioral priors by modeling future scene evolution, but predicting detailed futures in pixel or latent space incurs substantial cost. Recent ev…
Bridging Local Observation and Global Simulation in Closed-Loop Traffic Modeling
Ziyan Wang, Tan Xiang, Peng Chen +1
A local-to-global context mismatch arises when autoregressive traffic simulators trained on ego-centric driving logs are deployed in globally observable closed-loop environments. I…
Long-term Traffic Simulation via Structured Autoregressive Modeling
Lingyu Xiao, Zexin Feng, Xintao Yan
Interactive traffic simulation is a vital world model for autonomous driving. A central challenge in long-horizon simulation is modeling sustained multi-agent interactions, which i…
Horizon Adaptive Offline Policy Learning via Value Stitching
Kexin Zheng, Xianyuan Zhan, Xintao Yan
Learning accurate value functions plays a decisive role for reinforcement learning (RL) agents to solve long-horizon, complex tasks. Conventional temporal-difference (TD) learning…
Learning Responsibility-Attributed Adversarial Scenarios for Testing Autonomous Vehicles
Yizhuo Xiao, Haotian Yan, Ying Wang +5
Establishing trustworthy safety assurance for autonomous driving systems (ADSs) requires evidence that failures arise from avoidable system deficiencies rather than unavoidable tra…