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20242026
most citedVisual Adversarial Attack on Vision-Language Models for Autonomous Driving

2 citations · 4 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective

Tianyuan Zhang, Xianglong Liu, Aishan Liu +6

Environmental illusions (eg., shadows, reflections, and tire marks) are naturally existing yet overlooked phenomena in real-world driving environments. They can disturb visual perc…

cs.CV2025

Bench2ADVLM: A Closed-Loop Benchmark for Vision-language Models in Autonomous Driving

Tianyuan Zhang, Ting Jin, Lu Wang +5

Vision-Language Models (VLMs) have recently emerged as a promising paradigm in autonomous driving (AD). However, current performance evaluation protocols for VLM-based AD systems (…

cs.CV2025

Black-Box Adversarial Attack on Vision Language Models for Autonomous Driving

Lu Wang, Tianyuan Zhang, Yang Qu +5

Vision-language models (VLMs) have significantly advanced autonomous driving (AD) by enhancing reasoning capabilities; however, these models remain highly susceptible to adversaria…

cs.CV2024★ 2 cited

Visual Adversarial Attack on Vision-Language Models for Autonomous Driving

Tianyuan Zhang, Lu Wang, Xinwei Zhang +7

Vision-language models (VLMs) have significantly advanced autonomous driving (AD) by enhancing reasoning capabilities. However, these models remain highly vulnerable to adversarial…

cs.LG2024

Attack End-to-End Autonomous Driving through Module-Wise Noise

Lu Wang, Tianyuan Zhang, Yikai Han +3

With recent breakthroughs in deep neural networks, numerous tasks within autonomous driving have exhibited remarkable performance. However, deep learning models are susceptible to…

cs.CV2024★ 1 cited

Module-wise Adaptive Adversarial Training for End-to-end Autonomous Driving

Tianyuan Zhang, Lu Wang, Jiaqi Kang +5

Recent advances in deep learning have markedly improved autonomous driving (AD) models, particularly end-to-end systems that integrate perception, prediction, and planning stages,…

cs.CV2024★ 1 cited

LanEvil: Benchmarking the Robustness of Lane Detection to Environmental Illusions

Tianyuan Zhang, Lu Wang, Hainan Li +5

Lane detection (LD) is an essential component of autonomous driving systems, providing fundamental functionalities like adaptive cruise control and automated lane centering. Existi…