activity
20162024
most citedUsing Neural Networks to Compute Approximate and Guaranteed Feasible Hamilton-Jacobi-Bellman PDE Solutions

20 citations · 21 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SY2024

Towards Safe Autonomous Intersection Management: Temporal Logic-based Safety Filters for Vehicle Coordination

Kaj Munhoz Arfvidsson, Frank J. Jiang, Karl H. Johansson +1

In this paper, we introduce a temporal logic-based safety filter for Autonomous Intersection Management (AIM), an emerging infrastructure technology for connected vehicles to coord…

cs.CV2024

Pedestrian Motion Prediction Using Transformer-based Behavior Clustering and Data-Driven Reachability Analysis

Kleio Fragkedaki, Frank J. Jiang, Karl H. Johansson +1

In this work, we present a transformer-based framework for predicting future pedestrian states based on clustered historical trajectory data. In previous studies, researchers propo…

eess.SY20241 cited

Guaranteed Completion of Complex Tasks via Temporal Logic Trees and Hamilton-Jacobi Reachability

Frank J. Jiang, Kaj Munhoz Arfvidsson, Chong He +2

In this paper, we present an approach for guaranteeing the completion of complex tasks with cyber-physical systems (CPS). Specifically, we leverage temporal logic trees constructed…

eess.SY2024

Formal Verification of Linear Temporal Logic Specifications Using Hybrid Zonotope-Based Reachability Analysis

Loizos Hadjiloizou, Frank J. Jiang, Amr Alanwar +1

In this paper, we introduce a hybrid zonotope-based approach for formally verifying the behavior of autonomous systems operating under Linear Temporal Logic (LTL) specifications. I…

eess.SY2023

Data-Driven Reachability Analysis of Pedestrians Using Behavior Modes

August Söderlund, Frank J. Jiang, Vandana Narri +2

In this paper, we present a data-driven approach for safely predicting the future state sets of pedestrians. Previous approaches to predicting the future state sets of pedestrians…

cs.LG201620 cited

Using Neural Networks to Compute Approximate and Guaranteed Feasible Hamilton-Jacobi-Bellman PDE Solutions

Frank Jiang, Glen Chou, Mo Chen +1

To sidestep the curse of dimensionality when computing solutions to Hamilton-Jacobi-Bellman partial differential equations (HJB PDE), we propose an algorithm that leverages a neura…