Search Results for author: Qichao Zhang

Found 12 papers, 3 papers with code

Prototypical context-aware dynamics generalization for high-dimensional model-based reinforcement learning

no code implementations23 Nov 2022 Junjie Wang, Yao Mu, Dong Li, Qichao Zhang, Dongbin Zhao, Yuzheng Zhuang, Ping Luo, Bin Wang, Jianye Hao

The latent world model provides a promising way to learn policies in a compact latent space for tasks with high-dimensional observations, however, its generalization across diverse environments with unseen dynamics remains challenging.

Model-based Reinforcement Learning reinforcement-learning +1

Conditional Goal-oriented Trajectory Prediction for Interacting Vehicles with Vectorized Representation

no code implementations19 Oct 2022 Ding Li, Qichao Zhang, Shuai Lu, Yifeng Pan, Dongbin Zhao

Our CGTP framework is an end to end and interpretable model, including three main stages: context encoding, goal interactive prediction and trajectory interactive prediction.

Motion Forecasting Trajectory Forecasting

Multi-task Safe Reinforcement Learning for Navigating Intersections in Dense Traffic

no code implementations19 Feb 2022 Yuqi Liu, Qichao Zhang, Dongbin Zhao

In this paper, we formulate a multi-task safe reinforcement learning with social attention to improve the safety and efficiency when interacting with other traffic participants.

Autonomous Driving reinforcement-learning +2

A Reinforcement Learning Benchmark for Autonomous Driving in Intersection Scenarios

1 code implementation22 Sep 2021 Yuqi Liu, Qichao Zhang, Dongbin Zhao

The test benchmark and baselines are to provide a fair and comprehensive training and testing platform for the study of RL for autonomous driving in the intersection scenario, advancing the progress of RL-based methods for intersection autonomous driving control.

Autonomous Driving reinforcement-learning +1

Benchmarking Lane-changing Decision-making for Deep Reinforcement Learning

no code implementations22 Sep 2021 Junjie Wang, Qichao Zhang, Dongbin Zhao

We train several state-of-the-art deep reinforcement learning methods in the designed training scenarios and provide the benchmark metrics evaluation results of the trained models in the test scenarios.

Autonomous Driving Benchmarking +4

Dynamic Horizon Value Estimation for Model-based Reinforcement Learning

no code implementations21 Sep 2020 Jun-Jie Wang, Qichao Zhang, Dongbin Zhao, Mengchen Zhao, Jianye Hao

Existing model-based value expansion methods typically leverage a world model for value estimation with a fixed rollout horizon to assist policy learning.

Model-based Reinforcement Learning reinforcement-learning +1

BiFNet: Bidirectional Fusion Network for Road Segmentation

no code implementations18 Apr 2020 Haoran Li, Yaran Chen, Qichao Zhang, Dongbin Zhao

Considering the bird's eye views(BEV) of the LiDAR remains the space structure in horizontal plane, this paper proposes a bidirectional fusion network(BiFNet) to fuse the image and BEV of the point cloud.

Graph Attention Memory for Visual Navigation

no code implementations11 May 2019 Dong Li, Qichao Zhang, Dongbin Zhao, Yuzheng Zhuang, Bin Wang, Wulong Liu, Rasul Tutunov, Jun Wang

To address the long-term memory issue, this paper proposes a graph attention memory (GAM) architecture consisting of memory construction module, graph attention module and control module.

Graph Attention Reinforcement Learning (RL) +1

Lane Change Decision-making through Deep Reinforcement Learning with Rule-based Constraints

no code implementations30 Mar 2019 Jun-Jie Wang, Qichao Zhang, Dongbin Zhao, Yaran Chen

Autonomous driving decision-making is a great challenge due to the complexity and uncertainty of the traffic environment.

Autonomous Driving Decision Making +2

Reinforcement Learning and Deep Learning based Lateral Control for Autonomous Driving

1 code implementation30 Oct 2018 Dong Li, Dongbin Zhao, Qichao Zhang, Yaran Chen

The control module which is based on reinforcement learning then makes a control decision based on these features.

Autonomous Driving Multi-Task Learning +2

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