Predicting the trajectories of surrounding objects is a critical task in self-driving and many other autonomous systems.
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.
no code implementations • 10 Mar 2022 • Junjie Shen, Ningfei Wang, Ziwen Wan, Yunpeng Luo, Takami Sato, Zhisheng Hu, Xinyang Zhang, Shengjian Guo, Zhenyu Zhong, Kang Li, Ziming Zhao, Chunming Qiao, Qi Alfred Chen
In this paper, we perform the first systematization of knowledge of such growing semantic AD AI security research space.
We demonstrate that the conventional evaluation fails to reflect the robustness in end-to-end autonomous driving scenarios.
The experiment results demonstrate that our approach can effectively mitigate the impact of adversarial attacks and can achieve 55% to 90% improvement over the original OpenPilot.
Automated Lane Centering (ALC) systems are convenient and widely deployed today, but also highly security and safety critical.
Lane-Keeping Assistance System (LKAS) is convenient and widely available today, but also extremely security and safety critical.