most citedAutomated Lane Change Decision Making using Deep Reinforcement Learning in Dynamic and Uncertain Highway Environment

5 citations · 5 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2023

Beyond Traditional DoE: Deep Reinforcement Learning for Optimizing Experiments in Model Identification of Battery Dynamics

Gokhan Budan, Francesca Damiani, Can Kurtulus +1

Model identification of battery dynamics is a central problem in energy research; many energy management systems and design processes rely on accurate battery models for efficiency…

cs.RO2019★ 5 cited

Automated Lane Change Decision Making using Deep Reinforcement Learning in Dynamic and Uncertain Highway Environment

Ali Alizadeh, Majid Moghadam, Yunus Bicer +3

Autonomous lane changing is a critical feature for advanced autonomous driving systems, that involves several challenges such as uncertainty in other driver's behaviors and the tra…