7 papers
SHIELD: Scalable Optimal Control with Certification using Duality and Convexity
Hansung Kim, Siddharth H. Nair, Francesco Borrelli
We present SHIELD, a hierarchical algorithm that reduces both the decision-variable dimension and the constraint set in -regularized convex programs. From strong convexity…
Energy-Aware Lane Planning for Connected Electric Vehicles in Urban Traffic: Design and Vehicle-in-the-Loop Validation
Hansung Kim, Eric Yongkeun Choi, Eunhyek Joa +4
Urban driving with connected and automated vehicles (CAVs) offers potential for energy savings, yet most eco-driving strategies focus solely on longitudinal speed control within a…
Parking of Connected Automated Vehicles: Vehicle Control, Parking Assignment, and Multi-agent Simulation
Xu Shen, Yongkeun Choi, Alex Wong +3
This paper introduces a comprehensive approach to optimize parking efficiency for connected and Automated vehicle (CAVs) fleets. We present a multi-vehicle parking simulator, equip…
A Simple Approach to Constraint-Aware Imitation Learning with Application to Autonomous Racing
Shengfan Cao, Eunhyek Joa, Francesco Borrelli
Guaranteeing constraint satisfaction is challenging in imitation learning (IL), particularly in tasks that require operating near a system's handling limits. Traditional IL methods…
Learning Two-agent Motion Planning Strategies from Generalized Nash Equilibrium for Model Predictive Control
Hansung Kim, Edward L. Zhu, Chang Seok Lim +1
We introduce an Implicit Game-Theoretic MPC (IGT-MPC), a decentralized algorithm for two-agent motion planning that uses a learned value function that predicts the game-theoretic i…
Approximate solution of stochastic infinite horizon optimal control problems for constrained linear uncertain systems
Eunhyek Joa, Francesco Borrelli
We propose a Model Predictive Control (MPC) with a single-step prediction horizon to approximate the solution of infinite horizon optimal control problems with the expected sum of…