226 citations · 372 across the 11 of their papers we have counts for
14 papers
Towards Driving-Oriented Metric for Lane Detection Models
Takami Sato, Qi Alfred Chen
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 det…
Too Afraid to Drive: Systematic Discovery of Semantic DoS Vulnerability in Autonomous Driving Planning under Physical-World Attacks
Ziwen Wan, Junjie Shen, Jalen Chuang +4
In high-level Autonomous Driving (AD) systems, behavioral planning is in charge of making high-level driving decisions such as cruising and stopping, and thus highly securitycritic…
Sensor Adversarial Traits: Analyzing Robustness of 3D Object Detection Sensor Fusion Models
Won Park, Nan Liu, Qi Alfred Chen +1
A critical aspect of autonomous vehicles (AVs) is the object detection stage, which is increasingly being performed with sensor fusion models: multimodal 3D object detection models…
On Robustness of Lane Detection Models to Physical-World Adversarial Attacks in Autonomous Driving
Takami Sato, Qi Alfred Chen
After the 2017 TuSimple Lane Detection Challenge, its evaluation based on accuracy and F1 score has become the de facto standard to measure the performance of lane detection method…
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks
Yulong Cao*, Ningfei Wang*, Chaowei Xiao* +6
In Autonomous Driving (AD) systems, perception is both security and safety critical. Despite various prior studies on its security issues, all of them only consider attacks on came…
End-to-end Uncertainty-based Mitigation of Adversarial Attacks to Automated Lane Centering
Ruochen Jiao, Hengyi Liang, Takami Sato +3
In the development of advanced driver-assistance systems (ADAS) and autonomous vehicles, machine learning techniques that are based on deep neural networks (DNNs) have been widely…