Bio

I graduated from Tsinghua University with a doctor’s degree. My research covers reinforcement learning, autonomous driving, and optimal control. In Tsinghua, I worked at Intelligent Driving Lab (iDLab), where I was fortunate to be advised by Shengbo Eben Li and Bo Cheng. Since my graduate study, I have been committed to building more efficient and safer driving AI for the decision-making and control of automated vehicles, and to developing the next generation reinforcement learning algorithms that fuse both the data and the human knowledge for its application on advanced autonomous driving techniques.

Currently, I am working in Meituan Autonomous Driving team. Together with my talented colleagues, I am devoted to developing the most advanced technologies for the decision-making intelligence of automated vehicles, to build a safer, smarter delivery robot. Use autonomous vehicles to deliver everything for everyone everywhere!

Interests

  • Autonomous Driving
  • Decision-making
  • Reinforcement Learning
  • Optimal Control
  • Machine Learning

Education

  • Ph.D. in Vehicle Engineering, 2017-2022

    Tsinghua University

  • B.Eng in Vehicle Engineering, 2013-2017

    Beijing Institute of Technology

Working Experiences

 
 
 
 
 

Research Scientist

Meituan

October 2022 – Present Beijing
 
 
 
 
 

Research Intern

DiDi Global Inc.

September 2021 – December 2021 Beijing
 
 
 
 
 

Research Intern

Microsoft Research Asia

June 2021 – September 2021 Beijing
 
 
 
 
 

Research Intern

Idriverplus

June 2019 – September 2019 Beijing

Publications

Yang Guan (2022). Integrated Decision and Control of Automated Vehicles and Its Training by Mixed Reinforcement Learning. Dissertation of Tsinghua University.

Yang Guan*, Liye Tang*, Chuanxiao Li, Shengbo Eben Li, Yangang Ren, Junqing Wei, Bo Zhang, Keqiang Li (2022). Integrated Decision and Control for High-Level Automated Vehicles by Mixed Policy Gradient and Its Experiment Verification. In IEEE Trans. Industr. Inform. (under review).

Project Project

Jianyu Chen, Jingliang Duan, Yang Guan, Qi Sun, Yuming Yin, Shengbo Eben Li (2022). Self-learning Decision and Control for Highly Automated Vehicles. In book: AI-enabled Technologies for Autonomous and Connected Vehicles, Springer.

Source Document DOI

Jiaxin Gao*, Yang Guan*, Wenyu Li, Shengbo Eben Li, Fei Ma, Jianfeng Zheng, Junqing Wei, Bo Zhang, Keqiang Li (2022). Beyond Backpropagate Through Time: Efficient Model-Based Training Through Time-Splitting. In Int. J. Intell. Syst. (IF=10.3).

PDF DOI

Baiyu Peng, Jingliang Duan, Jianyu Chen, Shengbo Eben Li, Genjin Xie, Congsheng Zhang, Yang Guan, Yao Mu, Enxin Sun (2022). Model-Based Chance-Constrained Reinforcement Learning via Separated Proportional-Integral Lagrangian. In IEEE Trans. Neural. Netw. Learn. Syst. (IF=14.2).

PDF Video Source Document DOI

Yang Guan, Yangang Ren, Qi Sun, Shengbo Eben Li, Haitong Ma, Jingliang Duan, Yifan Dai, Bo Cheng (2022). Integrated Decision and Control: Toward Interpretable and Efficient Driving Intelligence. In IEEE Trans. Cybern. (IF=19.1).

Preprint PDF Code Project Project Video DOI

Jianhua Jiang, Yangang Ren, Yang Guan, Shengbo Eben Li, Yuming Yin, Dongjie Yu, Xiaoping Jin (2022). Integrated Decision and Control at Multi-Lane Intersections with Mixed Traffic Flow. In ICoIV 2021 (Best Student Paper).

Preprint PDF Project DOI

Baiyu Peng, Yao Mu, Yang Guan, Shengbo Eben Li, Yuming Yin, Jianyu Chen (2021). Model-Based Actor-Critic with Chance Constraint for Stochastic System. In IEEE CDC.

PDF Source Document DOI

Haitong Ma, Jianyu Chen, Shengbo Eben Li, Ziyu Lin, Yang Guan, Yangang Ren, Sifa Zheng (2021). Model-based Constrained Reinforcement Learning using Generalized Control Barrier Function. In IEEE/RSJ IROS.

PDF Code Project DOI

Yang Guan*, Yangang Ren*, Haitong Ma, Shengbo Eben Li, Qi Sun, Yifan Dai, Bo Cheng (2021). Learn Collision-Free Self-Driving Skills at Urban Intersections with Model-Based Reinforcement Learning. In IEEE ITSC (Best Student Paper).

PDF Project Video DOI

Jingliang Duan, Yangang Ren, Fawang Zhang, Yang Guan, Dongjie Yu, Shengbo Eben Li, Bo Cheng, Lin Zhao (2021). Encoding Distributional Soft Actor-Critic for Autonomous Driving in Multi-lane Scenarios. In IEEE Trans. Neural. Netw. Learn. Syst. (under review).

Preprint

Baiyu Peng, Yao Mu, Jingliang Duan, Yang Guan, Shengbo Eben Li, Jianyu Chen (2021). Separated Proportional-Integral Lagrangian for Chance Constrained Reinforcement Learning. In IEEE IV (Best Student Paper Finalists).

PDF DOI

Jingliang Duan*, Yang Guan*, Shengbo Eben Li, Yangang Ren, Qi Sun, Bo Cheng (2021). Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation Errors. In IEEE Trans. Neural. Netw. Learn. Syst. (IF=14.2).

PDF Code Video DOI

Haitong Ma, Yang Guan, Shengbo Eben Li, Xiangteng Zhang, Sifa Zheng, Jianyu Chen (2021). Feasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise Safety. In Arxiv.

Preprint Code Project Video

Kaiming Tang, Shengbo Eben Li, Yuming Yin, Yang Guan, Jingliang Duan, Wenhan Cao, Jie Li (2021). Approximate Optimal Filter for Linear Gaussian Time-invariant Systems. In Arxiv.

Preprint

Yiting Kong*, Yang Guan*, Jingliang Duan, Shengbo Eben Li, Qi Sun, Bingbing Nie (2021). Decision-Making under On-Ramp Merge Scenarios by Distributional Soft Actor-Critic Algorithm. In IEEE Trans. Intell. Veh. (under review).

Preprint Project Video

Yang Guan, Jingliang Duan, Shengbo Eben Li, Jie Li, Jianyu Chen, Bo Cheng (2021). Mixed Policy Gradient. In IEEE Trans. Neural. Netw. Learn. Syst. (under review).

Preprint Code Project

Yuhang Zhang, Yao Mu, Yujie Yang, Yang Guan, Shengbo Eben Li, Qi Sun, Jianyu Chen (2021). Steadily Learn to Drive with Virtual Memory. In Arxiv.

Preprint

Yang Guan, Shengbo Eben Li, Jingliang Duan, Jie Li, Yangang Ren, Bo Cheng (2020). Direct and Indirect Reinforcement Learning. In Int. J. Intell. Syst. (Cover Paper).

PDF DOI

Yang Guan, Yangang Ren, Shengbo Eben Li, Qi Sun, Laiquan Luo, Keqiang Li (2020). Centralized Cooperation for Connected and Automated Vehicles at Intersections by Proximal Policy Optimization. In IEEE Trans. Veh. Technol. (Top Journal in Intelligent Vehicles).

PDF Code Project Project Video DOI

Yangang Ren, Jingliang Duan, Shengbo Eben Li, Yang Guan, Qi Sun (2020). Improving Generalization of Reinforcement Learning with Minimax Distributional Soft Actor-Critic. In IEEE ITSC (Best Student Paper).

PDF Code DOI

Jie Li, Shengbo Eben Li, Yang Guan, Jingliang Duan, Wenyu Li, Yuming Yin (2020). Ternary Policy Iteration Algorithm for Nonlinear Robust Control. In IEEE Trans. Automat. Control. (under review).

Preprint

Jingliang Duan, Shengbo Eben Li, Yang Guan, Qi Sun, Bo Cheng (2020). Hierarchical Reinforcement Learning for Self-Driving Decision-Making without Reliance on Labeled Driving Data. In IET Intell. Transp. Syst..

PDF DOI

Long Xin, Yiting Kong, Shengbo Eben Li, Jianyu Chen, Yang Guan, Masayoshi Tomizuka, Bingbing Nie (2020). Enable Faster and Smoother Spatio-Temporal Trajectory Planning for Autonomous Vehicles in Constrained Dynamic Environment. In Proc. Inst. Mech. Eng. D: J. Automob. Eng..

PDF Project Video Source Document DOI

Shengbo Eben Li, Yang Guan, Lian Hou, Hongbo Gao, Jingliang Duan, Shuang Liang, Yu Wang, Bo Cheng, Keqiang Li, Wei Ren, Jun Li (2019). Key Technique of Deep Neural Network and Its Applications in Autonomous Driving. In J. Automot. Safety Energy..

PDF DOI

Yang Guan, Shengbo Eben Li, Jingliang Duan, Wenjun Wang, Bo Cheng (2018). Markov Probabilistic Decision Making of Self-Driving Cars in Highway with Random Traffic Flow: A Simulation Study. In J. Intell. Connect. Veh..

PDF Source Document DOI

Projects

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All Reinforcement Learning Autonomous Driving

Interpretable Driving AI with Highly Efficient Online Computation and Self-evolution Ability

The project aims to build an interpretable self-learning driving system by RL, for the real-time decision and control of automated …

Development of RL Library with High-throughput and Scalable Learning Architecture

This project aims to develop a highly modularized and extensible RL library, with the ability of scaling to use hundreds of CPU cores …

Development of RL environment for large-scale autonomous driving tasks

This project aims to build a general RL training and testing environment for the autonomous driving tasks. My works: 1) Combined a …

Driving AI: Centralized Decision and Control for Multiple Vehicles at Crossroad by RL

This project aims to develop a centralized coordination scheme of automated vehicles at an intersection without traffic signals using …

Automatic Decision Making and Planning at Crossroad

The project aims at designing an automatic decision making system for intelligent vehicle at a typical crossroad. My work focuses on …

Featured Publications

Integrated Decision and Control: Toward Interpretable and Efficient Driving Intelligence

Decision and control are core functionalities of high-level automated vehicles. Current mainstream methods, such as functional …
Yang Guan, Yangang Ren, Qi Sun, Shengbo Eben Li, Haitong Ma, Jingliang Duan, Yifan Dai, Bo Cheng
Preprint PDF Code Project Project Video DOI

Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation Errors

In reinforcement learning (RL), function approximation errors are known to easily lead to the Q-value overestimations, thus greatly …
Jingliang Duan*, Yang Guan*, Shengbo Eben Li, Yangang Ren, Qi Sun, Bo Cheng
PDF Code Video DOI

Mixed Policy Gradient

Reinforcement learning (RL) has great potential in sequential decision-making. At present, the mainstream RL algorithms are …
Yang Guan, Jingliang Duan, Shengbo Eben Li, Jie Li, Jianyu Chen, Bo Cheng
Preprint Code Project

Honors & Awards

  • Best student paper in IEEE ITSC 2021.

    Top conference of intelligent vehicles, Ranking: 2/597.

  • Cover paper in IJIS.

    The best paper in the issue.

  • First-class scholarship for comprehensive excellence in 2021.

    Presented to the best students in Tsinghua University.

  • The Award of Excellence.

    Stars of Tomorrow Internship Program in Microsoft Research Asia.

  • Best student paper in ICoIV 2021.

    Top conference of intelligent vehicles.

  • Best student paper Finalists in IEEE IV 2021.

    Top conference of intelligent vehicles, Ranking: 3/220.

  • Best student paper in IEEE ITSC 2020.

    Top conference of intelligent vehicles, Ranking: 3/573.

  • Outstanding graduates of Beijing for 2017.

    Presented to the best graduates in Beijing.

  • National Scholarship (Two consecutive years, 2015-2016).

    Presented to the best students in BIT.

  • Pacemaker to Merit Student (Three consecutive years, 2014-2016).

    Presented to the best students in BIT.

Contact

  • guanyang16@gmail.com
  • Hengdian Building, Chaoyang District, Beijing, 100084