activity
20232026
most citedLLM-attacker: Enhancing Closed-loop Adversarial Scenario Generation for Autonomous Driving with Large Language Models

33 citations · 37 across the 7 of their papers we have counts for

collaborators

7 papers

cs.RO2026

OVPD: A Virtual-Physical Fusion Testing Dataset of OnSite Auton-omous Driving Challenge

Yuhang Zhang, Jiarui Zhang, Bowen Jian +6

The rapid iteration of autonomous driving algorithms has created a growing demand for high-fidelity, replayable, and diagnosable testing data. However, many public datasets lack re…

cs.AI2025★ 1 cited

Seeking to Collide: Online Safety-Critical Scenario Generation for Autonomous Driving with Retrieval Augmented Large Language Models

Yuewen Mei, Tong Nie, Jian Sun +1

Simulation-based testing is crucial for validating autonomous vehicles (AVs), yet existing scenario generation methods either overfit to common driving patterns or operate in an of…

cs.LG2025★ 33 cited

LLM-attacker: Enhancing Closed-loop Adversarial Scenario Generation for Autonomous Driving with Large Language Models

Yuewen Mei, Tong Nie, Jian Sun +1

Ensuring and improving the safety of autonomous driving systems (ADS) is crucial for the deployment of highly automated vehicles, especially in safety-critical events. To address t…

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…

cs.SE2024★ 1 cited

High-Dimensional Fault Tolerance Testing of Highly Automated Vehicles Based on Low-Rank Models

Yuewen Mei, Tong Nie, Jian Sun +1

Ensuring fault tolerance of Highly Automated Vehicles (HAVs) is crucial for their safety due to the presence of potentially severe faults. Hence, Fault Injection (FI) testing is co…

cs.LG2024

Flow to Rare Events: An Application of Normalizing Flow in Temporal Importance Sampling for Automated Vehicle Validation

Yichun Ye, He Zhang, Ye Tian +2

Automated Vehicle (AV) validation based on simulated testing requires unbiased evaluation and high efficiency. One effective solution is to increase the exposure to risky rare even…

math.OC2023

A Macro-Micro Approach to Reconstructing Vehicle Trajectories on Multi-Lane Freeways with Lane Changing

Xuejian Chen, Guoyang Qin, Toru Seo +2

Vehicle trajectories can offer the most precise and detailed depiction of traffic flow and serve as a critical component in traffic management and control applications. Various tec…