32 citations · 177 across the 32 of their papers we have counts for
4 papers · 1 filter
Model-Based Actor-Critic with Chance Constraint for Stochastic System
Baiyu Peng, Yao Mu, Yang Guan +3
Safety is essential for reinforcement learning (RL) applied in real-world situations. Chance constraints are suitable to represent the safety requirements in stochastic systems. Pr…
Guided Policy Search Model-based Reinforcement Learning for Urban Autonomous Driving
Zhuo Xu, Jianyu Chen, Masayoshi Tomizuka
In this paper, we continue our prior work on using imitation learning (IL) and model free reinforcement learning (RL) to learn driving policies for autonomous driving in urban scen…
End-to-end Autonomous Driving Perception with Sequential Latent Representation Learning
Jianyu Chen, Zhuo Xu, Masayoshi Tomizuka
Current autonomous driving systems are composed of a perception system and a decision system. Both of them are divided into multiple subsystems built up with lots of human heuristi…
Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning
Jianyu Chen, Shengbo Eben Li, Masayoshi Tomizuka
Unlike popular modularized framework, end-to-end autonomous driving seeks to solve the perception, decision and control problems in an integrated way, which can be more adapting to…