Human-like Car Following
Deep Reinforcement Learning; Deterministic Policy Gradient
Project:
Using Deep Reinforcement Learning to design a Human-like Car-Following system
- Leveraged an Actor-critic Reinforcement Learning framework to learn personalized car-following behaviors from empirical data
- Employed Deep Deterministic Policy Gradient (DDPG) to learn the continuous-control policy network.
Related Skills:
- MDP
- Bandit
- Actor-critic Reinforcement Learning
- Deep deterministic policy gradient
Meta Information:
- Time: Fall 2020
- Instructor: Hongning Wang
- Affiliation: University of Virginia
- Teamate: Xingbo Fu