97 citations · 106 across the 7 of their papers we have counts for
9 papers
NeSy-CSA: A Neuro-Symbolic Framework for Open-Ended Critical Scenario Attribution
Qitong Chu, Xunjie He, Chen Deng +2
Understanding why discovered scenarios become critical in scenario-based testing is essential for effectively leveraging them in decision-making systems. Reasoning about such criti…
Intelligent Resilience Testing for Decision-Making Agents with Dual-Mode Surrogate Adaptation
Jingxuan Yang, Weichao Xu, Yuchen Shi +3
Testing and evaluating decision-making agents remains challenging due to unknown system architectures, limited access to internal states, and the vastness of high-dimensional scena…
Fault-Tolerant MARL for CAVs under Observation Perturbations for Highway On-Ramp Merging
Yuchen Shi, Huaxin Pei, Yi Zhang +1
Multi-Agent Reinforcement Learning (MARL) holds significant promise for enabling cooperative driving among Connected and Automated Vehicles (CAVs). However, its practical applicati…
DiCriTest: Testing Scenario Generation for Decision-Making Agents Considering Diversity and Criticality
Qitong Chu, Yufeng Yue, Danya Yao +1
The growing deployment of decision-making agents in dynamic environments increases the demand for safety verification. While critical testing scenario generation has emerged as an…
Exploring Critical Testing Scenarios for Decision-Making Policies: An LLM Approach
Weichao Xu, Huaxin Pei, Jingxuan Yang +3
Recent advances in decision-making policies have led to significant progress in fields such as autonomous driving and robotics. However, testing these policies remains crucial with…
Towards Fault Tolerance in Multi-Agent Reinforcement Learning
Yuchen Shi, Huaxin Pei, Liang Feng +2
Agent faults pose a significant threat to the performance of multi-agent reinforcement learning (MARL) algorithms, introducing two key challenges. First, agents often struggle to e…
Synthetic Datasets for Autonomous Driving: A Survey
Zhihang Song, Zimin He, Xingyu Li +8
Autonomous driving techniques have been flourishing in recent years while thirsting for huge amounts of high-quality data. However, it is difficult for real-world datasets to keep…
Optimal Cooperative Driving at Signal-Free Intersections with Polynomial-Time Complexity
Huaxin Pei, Yuxiao Zhang, Yi Zhang +1
Cooperative driving at signal-free intersections, which aims to improve driving safety and efficiency for connected and automated vehicles, has attracted increasing interest in rec…
Distributed Cooperative Driving in Multi-Intersection Road Networks
Huaxin Pei, Yi Zhang, Qinghua Tao +2
Cooperative driving at isolated intersections attracted great interest and had been well discussed in recent years. However, cooperative driving in multi-intersection road networks…