51 citations · 96 across the 20 of their papers we have counts for
5 papers · 1 filter
Safe Control and Learning Using Generalized Action Governor
Peiyuan Fang, Weiqi Zhang, Lu Xiong +7
This paper introduces the Generalized Action Governor (AG), a supervisory scheme that augments a nominal closed-loop system with the capability to enforce state and input constrain…
Robust Action Governor for Uncertain Piecewise Affine Systems with Non-convex Constraints and Safe Reinforcement Learning
Yutong Li, Nan Li, H. Eric Tseng +3
The action governor is an add-on scheme to a nominal control loop that monitors and adjusts the control actions to enforce safety specifications expressed as pointwise-in-time stat…
Robust AI Driving Strategy for Autonomous Vehicles
Subramanya Nageshrao, Yousaf Rahman, Vladimir Ivanovic +4
There has been significant progress in sensing, perception, and localization for automated driving, However, due to the wide spectrum of traffic/road structure scenarios and the lo…
Safe, Learning-Based MPC for Highway Driving under Lane-Change Uncertainty: A Distributionally Robust Approach
Mathijs Schuurmans, Alexander Katriniok, Christopher Meissen +2
We present a case study applying learning-based distributionally robust model predictive control to highway motion planning under stochastic uncertainty of the lane change behavior…
Potential Game-Based Decision-Making for Autonomous Driving
Mushuang Liu, Ilya Kolmanovsky, H. Eric Tseng +3
Decision-making for autonomous driving is challenging, considering the complex interactions among multiple traffic agents (e.g., autonomous vehicles (AVs), human drivers, and pedes…