51 citations · 164 across the 35 of their papers we have counts for
38 papers
Game Projection and Robustness for Game-Theoretic Autonomous Driving
Mushuang Liu, H. Eric Tseng, Dimitar Filev +2
Game-theoretic approaches are envisioned to bring human-like reasoning skills and decision-making processes for autonomous vehicles (AVs). However, challenges including game comple…
Decision-Making for Autonomous Vehicles with Interaction-Aware Behavioral Prediction and Social-Attention Neural Network
Xiao Li, Kaiwen Liu, H. Eric Tseng +2
Autonomous vehicles need to accomplish their tasks while interacting with human drivers in traffic. It is thus crucial to equip autonomous vehicles with artificial reasoning to bet…
Interaction-Aware Decision-Making for Autonomous Vehicles in Forced Merging Scenario Leveraging Social Psychology Factors
Xiao Li, Kaiwen Liu, H. Eric Tseng +2
Understanding the intention of vehicles in the surrounding traffic is crucial for an autonomous vehicle to successfully accomplish its driving tasks in complex traffic scenarios su…
Scheduling Dosage of Proton Pump Inhibitors Using Constrained Optimization With Gastric Acid Secretion Model
Yutong Li, Nan Li, Anouck Girard +1
Dosage schedule of the Proton Pump Inhibitors (PPIs) is critical for gastric acid disorder treatment. In this paper, we develop a constrained optimization based approach for schedu…
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…
Safe and Human-Like Autonomous Driving: A Predictor-Corrector Potential Game Approach
Mushuang Liu, H. Eric Tseng, Dimitar Filev +2
This paper proposes a novel decision-making framework for autonomous vehicles (AVs), called predictor-corrector potential game (PCPG), composed of a Predictor and a Corrector. To e…
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…
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…
Interaction-Aware Trajectory Prediction and Planning for Autonomous Vehicles in Forced Merge Scenarios
Kaiwen Liu, Nan Li, H. Eric Tseng +2
Merging is, in general, a challenging task for both human drivers and autonomous vehicles, especially in dense traffic, because the merging vehicle typically needs to interact with…
Energy-Efficient Autonomous Driving Using Cognitive Driver Behavioral Models and Reinforcement Learning
Huayi Li, Nan Li, Ilya Kolmanovsky +1
Autonomous driving technologies are expected to not only improve mobility and road safety but also bring energy efficiency benefits. In the foreseeable future, autonomous vehicles…
Set-theoretic Localization for Mobile Robots with Infrastructure-based Sensing
Xiao Li, Yutong Li, Nan Li +2
In this paper, we introduce a set-theoretic approach for mobile robot localization with infrastructure-based sensing. The proposed method computes sets that over-bound the robot bo…
Coordinated Receding-Horizon Control of Battery Electric Vehicle Speed and Gearshift Using Relaxed Mixed Integer Nonlinear Programming
Nan Li, Kyoungseok Han, Ilya Kolmanovsky +1
In this paper, we propose an approach to coordinated receding-horizon control of vehicle speed and transmission gearshift for automated battery electric vehicles (BEVs) to achieve…
Safe Reinforcement Learning Using Robust Action Governor
Yutong Li, Nan Li, H. Eric Tseng +3
Reinforcement Learning (RL) is essentially a trial-and-error learning procedure which may cause unsafe behavior during the exploration-and-exploitation process. This hinders the ap…
Safe Learning Reference Governor: Theory and Application to Fuel Truck Rollover Avoidance
Kaiwen Liu, Nan Li, Ilya Kolmanovsky +2
This paper proposes a learning reference governor (LRG) approach to enforce state and control constraints in systems for which an accurate model is unavailable, and this approach e…
Chance-Constrained Controller State and Reference Governor
Nan Li, Anouck Girard, Ilya Kolmanovsky
The controller state and reference governor (CSRG) is an add-on scheme for nominal closed-loop systems with dynamic controllers which supervises the controller internal state and t…
Suboptimal Nonlinear Model Predictive Control Strategies for Tracking Near Rectilinear Halo Orbits
Andrew W. Berning, Dominic Liao-McPherson, Anouck Girard +1
Near Rectilinear Halo Orbits (NRHOs), a subclass of halo orbits around the L1 and L2 Lagrange points, are promising candidates for future lunar gateways in cis-lunar space and as s…
Action Governor for Discrete-Time Linear Systems with Non-Convex Constraints
Nan Li, Kyoungseok Han, Anouck Girard +3
This paper introduces an add-on, supervisory scheme, referred to as Action Governor (AG), for discrete-time linear systems to enforce exclusion-zone avoidance requirements. It does…
A Game Theoretic Approach for Parking Spot Search with Limited Parking Lot Information
Yutong Li, Nan Li, H. Eric Tseng +4
We propose a game theoretic approach to address the problem of searching for available parking spots in a parking lot and picking the ``optimal'' one to park. The approach exploits…
Vision-Based Autonomous Driving: A Model Learning Approach
Ali Baheri, Ilya Kolmanovsky, Anouck Girard +2
We present an integrated approach for perception and control for an autonomous vehicle and demonstrate this approach in a high-fidelity urban driving simulator. Our approach first…
Rapid Uncertainty Propagation and Chance-Constrained Path Planning for Small Unmanned Aerial Vehicles
Andrew W. Berning, Anouck Girard, Ilya Kolmanovsky +1
With the number of small Unmanned Aircraft Systems (sUAS) in the national airspace projected to increase in the next few years, there is growing interest in a traffic management sy…
A Novel Approach for Optimal Trajectory Design with Multiple Operation Modes of Propulsion System, Part 2
Ehsan Taheri, John L. Junkins, Ilya Kolmanovsky +1
Equipping a spacecraft with multiple solar-powered electric engines (of the same or different types) compounds the task of optimal trajectory design due to presence of both real-va…
A Novel Approach for Optimal Trajectory Design with Multiple Operation Modes of Propulsion System, Part 1
Ehsan Taheri, John L. Junkins, Ilya Kolmanovsky +1
Efficient performance of a number of engineering systems is achieved through different modes of operation - yielding systems described as "hybrid", containing both real-valued and…
Spacecraft Relative Motion Planning Using Chained Chance-Constrained Admissible Sets
Andrew W. Berning, Nan I. Li, Anouck Girard +3
With the increasing interest in proximity and docking operations, there is a growing interest in spacecraft relative motion control. This paper extends a previously proposed constr…
Co-optimization of Speed and Gearshift Control for Battery Electric Vehicles Using Preview Information
Kyoungseok Han, Nan Li, Ilya Kolmanovsky +4
This paper addresses the co-optimization of speed and gearshift control for battery electric vehicles using short-range traffic information. To achieve greater electric motor effic…