A survey of end-to-end driving: Architectures and training methods
A Tampuu, T Matiisen, M Semikin… - … on Neural Networks …, 2020 - ieeexplore.ieee.org
Autonomous driving is of great interest to industry and academia alike. The use of machine
learning approaches for autonomous driving has long been studied, but mostly in the …
learning approaches for autonomous driving has long been studied, but mostly in the …
Invisible for both camera and lidar: Security of multi-sensor fusion based perception in autonomous driving under physical-world attacks
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 camera-or …
various prior studies on its security issues, all of them only consider attacks on camera-or …
Physical attack on monocular depth estimation with optimal adversarial patches
Deep learning has substantially boosted the performance of Monocular Depth Estimation
(MDE), a critical component in fully vision-based autonomous driving (AD) systems (eg …
(MDE), a critical component in fully vision-based autonomous driving (AD) systems (eg …
[PDF][PDF] Avoiding an oppressive future of machine learning: A design theory for emancipatory assistants
Widespread use of machine learning (ML) systems could result in an oppressive future of
ubiquitous monitoring and behavior control that, for dialogic purposes, we call “Informania.” …
ubiquitous monitoring and behavior control that, for dialogic purposes, we call “Informania.” …
Attacks on self-driving cars and their countermeasures: A survey
Intelligent Traffic Systems (ITS) are currently evolving in the form of a cooperative ITS or
connected vehicles. Both forms use the data communications between Vehicle-to-Vehicle …
connected vehicles. Both forms use the data communications between Vehicle-to-Vehicle …
Dirty road can attack: Security of deep learning based automated lane centering under {Physical-World} attack
Automated Lane Centering (ALC) systems are convenient and widely deployed today, but
also highly security and safety critical. In this work, we are the first to systematically study the …
also highly security and safety critical. In this work, we are the first to systematically study the …
I can see the light: Attacks on autonomous vehicles using invisible lights
The camera is one of the most important sensors for an autonomous vehicle (AV) to perform
Environment Perception and Simultaneous Localization and Mapping (SLAM). To secure …
Environment Perception and Simultaneous Localization and Mapping (SLAM). To secure …
Pla-lidar: Physical laser attacks against lidar-based 3d object detection in autonomous vehicle
Autonomous vehicles and robots increasingly exploit LiDAR-based 3D object detection
systems to detect obstacles in environment. Correct detection and classification are …
systems to detect obstacles in environment. Correct detection and classification are …
Poltergeist: Acoustic adversarial machine learning against cameras and computer vision
Autonomous vehicles increasingly exploit computer-vision-based object detection systems
to perceive environments and make critical driving decisions. To increase the quality of …
to perceive environments and make critical driving decisions. To increase the quality of …
A Comprehensive Survey of Threats in Platooning—A Cloud-Assisted Connected and Autonomous Vehicle Application
Cloud-Assisted Connected and Autonomous Vehicles (CCAV) are set to revolutionise road
safety, providing substantial societal and economic advantages. However, with the evolution …
safety, providing substantial societal and economic advantages. However, with the evolution …