138 citations · 318 across the 20 of their papers we have counts for
20 papers
Safety Under Uncertainty: Tight Bounds with Risk-Aware Control Barrier Functions
Mitchell Black, Georgios Fainekos, Bardh Hoxha +2
We propose a novel class of risk-aware control barrier functions (RA-CBFs) for the control of stochastic safety-critical systems. Leveraging a result from the stochastic level-cros…
A Neurosymbolic Approach to the Verification of Temporal Logic Properties of Learning enabled Control Systems
Navid Hashemi, Bardh Hoxha, Tomoya Yamaguchi +3
Signal Temporal Logic (STL) has become a popular tool for expressing formal requirements of Cyber-Physical Systems (CPS). The problem of verifying STL properties of neural network-…
Model-based Evaluation of Driver Control Workloads in Haptic-based Driver Assistance Systems
Kenechukwu C. Mbanisi, Hideyuki Kimpara, Zhi Li +2
This study presents a novel approach for modeling and simulating human-vehicle interactions in order to examine the effects of automated driving systems (ADS) on driving performanc…
Risk-Awareness in Learning Neural Controllers for Temporal Logic Objectives
Navid Hashemi, Xin Qin, Jyotirmoy V. Deshmukh +4
In this paper, we consider the problem of synthesizing a controller in the presence of uncertainty such that the resulting closed-loop system satisfies certain hard constraints whi…
Risk-Bounded Control with Kalman Filtering and Stochastic Barrier Functions
Shakiba Yaghoubi, Georgios Fainekos, Tomoya Yamaguchi +2
In this paper, we study Stochastic Control Barrier Functions (SCBFs) to enable the design of probabilistic safe real-time controllers in presence of uncertainties and based on nois…
Neural Network Repair with Reachability Analysis
Xiaodong Yang, Tom Yamaguchi, Hoang-Dung Tran +3
Safety is a critical concern for the next generation of autonomy that is likely to rely heavily on deep neural networks for perception and control. Formally verifying the safety an…