234 citations · 310 across the 9 of their papers we have counts for
5 papers · 1 filter
Comparison of Deep Reinforcement Learning and Model Predictive Control for Adaptive Cruise Control
Yuan Lin, John McPhee, Nasser L. Azad
This study compares Deep Reinforcement Learning (DRL) and Model Predictive Control (MPC) for Adaptive Cruise Control (ACC) design in car-following scenarios. A first-order system i…
Anti-Jerk On-Ramp Merging Using Deep Reinforcement Learning
Yuan Lin, John McPhee, Nasser L. Azad
Deep Reinforcement Learning (DRL) is used here for decentralized decision-making and longitudinal control for high-speed on-ramp merging. The DRL environment state includes the sta…
Longitudinal Dynamic versus Kinematic Models for Car-Following Control Using Deep Reinforcement Learning
Yuan Lin, John McPhee, Nasser L. Azad
The majority of current studies on autonomous vehicle control via deep reinforcement learning (DRL) utilize point-mass kinematic models, neglecting vehicle dynamics which includes…
GolfDB: A Video Database for Golf Swing Sequencing
William McNally, Kanav Vats, Tyler Pinto +3
The golf swing is a complex movement requiring considerable full-body coordination to execute proficiently. As such, it is the subject of frequent scrutiny and extensive biomechani…
STAR-Net: Action Recognition using Spatio-Temporal Activation Reprojection
William McNally, Alexander Wong, John McPhee
While depth cameras and inertial sensors have been frequently leveraged for human action recognition, these sensing modalities are impractical in many scenarios where cost or envir…