A Survey of Autonomous Driving: Common Practices and Emerging Technologies
Automated driving systems (ADSs) promise a safe, comfortable and efficient driving
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …
Survey on scenario-based safety assessment of automated vehicles
S Riedmaier, T Ponn, D Ludwig, B Schick… - IEEE …, 2020 - ieeexplore.ieee.org
When will automated vehicles come onto the market? This question has puzzled the
automotive industry and society for years. The technology and its implementation have …
automotive industry and society for years. The technology and its implementation have …
Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods for robotics and control
Learning-enabled control systems have demonstrated impressive empirical performance on
challenging control problems in robotics, but this performance comes at the cost of reduced …
challenging control problems in robotics, but this performance comes at the cost of reduced …
A review of motion planning for highway autonomous driving
L Claussmann, M Revilloud, D Gruyer… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Self-driving vehicles will soon be a reality, as main automotive companies have announced
that they will sell their driving automation modes in the 2020s. This technology raises …
that they will sell their driving automation modes in the 2020s. This technology raises …
Safe nonlinear control using robust neural lyapunov-barrier functions
Safety and stability are common requirements for robotic control systems; however,
designing safe, stable controllers remains difficult for nonlinear and uncertain models. We …
designing safe, stable controllers remains difficult for nonlinear and uncertain models. We …
nuplan: A closed-loop ml-based planning benchmark for autonomous vehicles
In this work, we propose the world's first closed-loop ML-based planning benchmark for
autonomous driving. While there is a growing body of ML-based motion planners, the lack of …
autonomous driving. While there is a growing body of ML-based motion planners, the lack of …
F1tenth: An open-source evaluation environment for continuous control and reinforcement learning
The deployment and evaluation of learning algorithms on autonomous vehicles (AV) is
expensive, slow, and potentially unsafe. This paper details the F1TENTH autonomous …
expensive, slow, and potentially unsafe. This paper details the F1TENTH autonomous …
Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods
Learning-enabled control systems have demonstrated impressive empirical performance on
challenging control problems in robotics, but this performance comes at the cost of reduced …
challenging control problems in robotics, but this performance comes at the cost of reduced …
High-level decision making for safe and reasonable autonomous lane changing using reinforcement learning
B Mirchevska, C Pek, M Werling… - 2018 21st …, 2018 - ieeexplore.ieee.org
Machine learning techniques have been shown to outperform many rule-based systems for
the decision-making of autonomous vehicles. However, applying machine learning is …
the decision-making of autonomous vehicles. However, applying machine learning is …
ScenarioNet: Open-source platform for large-scale traffic scenario simulation and modeling
Large-scale driving datasets such as Waymo Open Dataset and nuScenes substantially
accelerate autonomous driving research, especially for perception tasks such as 3D …
accelerate autonomous driving research, especially for perception tasks such as 3D …