Dueling deep Q network for highway decision making in autonomous vehicles: A case study
This work optimizes the highway decision making strategy of autonomous vehicles by using
deep reinforcement learning (DRL). First, the highway driving environment is built, wherein …
deep reinforcement learning (DRL). First, the highway driving environment is built, wherein …
Dueling Deep Q Network for Highway Decision Making in Autonomous Vehicles: A Case Study
T Liu, X Mu, X Tang, B Huang, H Wang… - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
This work optimizes the highway decision making strategy of autonomous vehicles by using
deep reinforcement learning (DRL). First, the highway driving environment is built, wherein …
deep reinforcement learning (DRL). First, the highway driving environment is built, wherein …
[PDF][PDF] Dueling Deep Q Network for Highway Decision Making in Autonomous Vehicles: A Case Study
T Liu, X Mu, X Tang, B Huang, H Wang, D Cao - researchgate.net
This work optimizes the highway decision making strategy of autonomous vehicles by using
deep reinforcement learning (DRL). First, the highway driving environment is built, wherein …
deep reinforcement learning (DRL). First, the highway driving environment is built, wherein …