15 citations · 28 across the 19 of their papers we have counts for
6 papers · 1 filter
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…