2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.LG2025
An Evolving Scenario Generation Method based on Dual-modal Driver Model Trained by Multi-Agent Reinforcement Learning
Xinzheng Wu, Junyi Chen, Shaolingfeng Ye +2
In the autonomous driving testing methods based on evolving scenarios, the construction method of the driver model, which determines the driving maneuvers of background vehicles (B…
cs.AI2025
Make Full Use of Testing Information: An Integrated Accelerated Testing and Evaluation Method for Autonomous Driving Systems
Xinzheng Wu, Junyi Chen, Jianfeng Wu +3
Testing and evaluation is an important step before the large-scale application of the autonomous driving systems (ADSs). Based on the three level of scenario abstraction theory, a…
cs.AI2024★ 2 cited
LAMBDA: Covering the Multimodal Critical Scenarios for Automated Driving Systems by Search Space Quantization
Xinzheng Wu, Junyi Chen, Xingyu Xing +4
Scenario-based virtual testing is one of the most significant methods to test and evaluate the safety of automated driving systems (ADSs). However, it is impractical to enumerate a…