Qi Alfred Chen
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A Comprehensive Study of Bug-Fix Patterns in Autonomous Driving Systems Open
As autonomous driving systems (ADSes) become increasingly complex and integral to daily life, the importance of understanding the nature and mitigation of software bugs in these systems has grown correspondingly. Addressing the challenges …
SLAMSpoof: Practical LiDAR Spoofing Attacks on Localization Systems Guided by Scan Matching Vulnerability Analysis Open
Accurate localization is essential for enabling modern full self-driving services. These services heavily rely on map-based traffic information to reduce uncertainties in recognizing lane shapes, traffic light locations, and traffic signs.…
Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives Open
Recent advancements in Vision-Language Models (VLMs) have sparked interest in their use for autonomous driving, particularly in generating interpretable driving decisions through natural language. However, the assumption that VLMs inherent…
Revisiting Physical-World Adversarial Attack on Traffic Sign Recognition: A Commercial Systems Perspective Open
Traffic Sign Recognition (TSR) is crucial for safe and correct driving automation. Recent works revealed a general vulnerability of TSR models to physical-world adversarial attacks, which can be low-cost, highly deployable, and capable of …
ControlLoc: Physical-World Hijacking Attack on Visual Perception in Autonomous Driving Open
Recent research in adversarial machine learning has focused on visual perception in Autonomous Driving (AD) and has shown that printed adversarial patches can attack object detectors. However, it is important to note that AD visual percept…
SlowPerception: Physical-World Latency Attack against Visual Perception in Autonomous Driving Open
Autonomous Driving (AD) systems critically depend on visual perception for real-time object detection and multiple object tracking (MOT) to ensure safe driving. However, high latency in these visual perception components can lead to signif…
SlowTrack: Increasing the Latency of Camera-Based Perception in Autonomous Driving Using Adversarial Examples Open
In Autonomous Driving (AD), real-time perception is a critical component responsible for detecting surrounding objects to ensure safe driving. While researchers have extensively explored the integrity of AD perception due to its safety and…
Towards Automated Driving Violation Cause Analysis in Scenario-Based Testing for Autonomous Driving Systems Open
The rapid advancement of Autonomous Vehicles (AVs), exemplified by companies like Waymo and Cruise offering 24/7 paid taxi services, highlights the paramount importance of ensuring AVs' compliance with various policies, such as safety regu…
View article: Invisible Reflections: Leveraging Infrared Laser Reflections to Target Traffic Sign Perception
Invisible Reflections: Leveraging Infrared Laser Reflections to Target Traffic Sign Perception Open
All vehicles must follow the rules that govern traffic behavior, regardless of whether the vehicles are human-driven or Connected Autonomous Vehicles (CAVs). Road signs indicate locally active rules, such as speed limits and requirements t…
View article: Invisible Reflections: Leveraging Infrared Laser Reflections to Target Traffic Sign Perception
Invisible Reflections: Leveraging Infrared Laser Reflections to Target Traffic Sign Perception Open
All vehicles must follow the rules that govern traffic behavior, regardless of whether the vehicles are human-driven or Connected Autonomous Vehicles (CAVs).Road signs indicate locally active rules, such as speed limits and requirements to…
View article: LiDAR Spoofing Meets the New-Gen: Capability Improvements, Broken Assumptions, and New Attack Strategies
LiDAR Spoofing Meets the New-Gen: Capability Improvements, Broken Assumptions, and New Attack Strategies Open
LiDAR (Light Detection And Ranging) is an indispensable sensor for precise long-and wide-range 3D sensing, which directly benefited the recent rapid deployment of autonomous driving (AD).Meanwhile, such a safety-critical application strong…
SlowTrack: Increasing the Latency of Camera-based Perception in Autonomous Driving Using Adversarial Examples Open
In Autonomous Driving (AD), real-time perception is a critical component responsible for detecting surrounding objects to ensure safe driving. While researchers have extensively explored the integrity of AD perception due to its safety and…
Intriguing Properties of Diffusion Models: An Empirical Study of the Natural Attack Capability in Text-to-Image Generative Models Open
Denoising probabilistic diffusion models have shown breakthrough performance to generate more photo-realistic images or human-level illustrations than the prior models such as GANs. This high image-generation capability has stimulated the …
Does Physical Adversarial Example Really Matter to Autonomous Driving? Towards System-Level Effect of Adversarial Object Evasion Attack Open
In autonomous driving (AD), accurate perception is indispensable to achieving safe and secure driving. Due to its safety-criticality, the security of AD perception has been widely studied. Among different attacks on AD perception, the phys…
Lateral-Direction Localization Attack in High-Level Autonomous Driving: Domain-Specific Defense Opportunity via Lane Detection Open
Localization in high-level Autonomous Driving (AD) systems is highly security critical. While the popular Multi-Sensor Fusion (MSF) based design can be more robust against single-source sensor spoofing attacks, it is found recently that st…
LiDAR Spoofing Meets the New-Gen: Capability Improvements, Broken Assumptions, and New Attack Strategies Open
LiDAR (Light Detection And Ranging) is an indispensable sensor for precise long- and wide-range 3D sensing, which directly benefited the recent rapid deployment of autonomous driving (AD). Meanwhile, such a safety-critical application stro…
Play the Imitation Game: Model Extraction Attack against Autonomous Driving Localization Open
The security of the Autonomous Driving (AD) system has been gaining researchers' and public's attention recently. Given that AD companies have invested a huge amount of resources in developing their AD models, e.g., localization models, th…
Towards Driving-Oriented Metric for Lane Detection Models Open
After the 2017 TuSimple Lane Detection Challenge, its dataset and evaluation based on accuracy and F1 score have become the de facto standard to measure the performance of lane detection methods. While they have played a major role in impr…
On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles Open
Trajectory prediction is a critical component for autonomous vehicles (AVs) to perform safe planning and navigation. However, few studies have analyzed the adversarial robustness of trajectory prediction or investigated whether the worst-c…