234 citations · 286 across the 7 of their papers we have counts for
4 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…
Integrating Inter-vehicular Communication, Vehicle Localization, and a Digital Map for Cooperative Adaptive Cruise Control with Target Detection Loss
Yuan Lin, Azim Eskandarian
Adaptive Cruise Control (ACC) is an Advanced Driver Assistance System (ADAS) that enables vehicle following with desired inter-vehicular distances. Cooperative Adaptive Cruise Cont…