Zirui Li

About Me

Zirui Li received the B.S. degree from the Beijing Institute of Technology (BIT), Beijing, China, in 2019, where he is currently pursuing the Ph.D. degree in mechanical engineering under the supervision of Prof. Jianwei Gong. Now, Zirui is also a researcher in TU Dresden. From June, 2021 to July, 2022, he was a visiting researcher in Delft University of Technology (TU Delft) with CSC funding from China under the supervision of Prof. Bart van Arem, Prof. Victor Knoop and Prof. Meng Wang. From Aug, 2022. He is the visiting researcher in the Chair of Traffic Process Automation at the Faculty of Transportation and Traffic Sciences “Friedrich List” of the TU Dresden under the supervision of Prof. Meng Wang. His research focuses on interactive behavior modeling, risk assessment and motion planning of automated vehicles. Any interest on my work you can drop me email (zirui.li@tu-dresden.de)

Research Interests

• Data-driven interactive behaviour modelling for VRUs
• The integration of behaviour prediction and motion planning for AVs
• Interactive behaviour definition, measurement and detection

News

• [Dec. 2023] Zirui is appointed as the working group leader of intelligent vehicle risk assessment under IEEE Standard Assosiation (SA) and is leading the development of Standard for driving risk assessment procedure in SAE Level 1-3. Welcome to join the group.
• [Nov. 2023] Zirui will give a talk at 2023 ITS WiE/YP Workshop & Research Forum with title Towards integrating subjective and objective risks in human-centric automated driving (20-21 Nov, 2023 @ Cairo, Egypt).
• [Nov. 2023] One paper about Multi-stream Information Fusion in Low-illumination Scenarios is accepted by IEEE T-ITS. Find code and paper here.
• [Oct. 2023] One paper about reachable set based risk assessment is accepted by Engineeing. The online version will come soon.
• [Oct. 2023] One paper about continual driver behavior learning is accepted by IEEE T-ITS. Find code and paper here.
• [Sep. 2023] Zirui will give a talk at IEEE ITSC 2023 Workshop with title Continual Driver Behavior Learning in Interactive Urban Scenarios (24 September, 2023 @ Bilbao, Bizkaia, Spain).
• [Sep. 2023] Zirui won the IEEE ITSS Young Professionals Travelling Fellowship (2023).
• [Aug. 2023] One paper Rate GQN is accepted by IEEE T-ITS. The published version and open source code will be coming soon.
• [July. 2023] Four papers are accepted by ITSC 2023.
• [June. 2023] Our workshop proposal Cooperative Decision-making for Connected and Automated Vehicles in Intelligent Transportation Systems is accepted by IEEE ITSC 2023. Welcome your contributions.
• [June. 2023] I start as Researcher in TU Dresden.
• [June. 2023] Our workshop Social, Interactive and Safe Behaviors for Intelligent Vehicles: Benchmark, Models and Applications is successfully held at IEEE IV 2023.
• [May. 2023] Our Proceedings of MFTS 2022, where I serve as one of the editors, is online published now, download here.
• [May. 2023] Two papers are accepted at IEEE T-ITS.

Selected publications

For the full and newest publications CLICK HERE.

• Personalized Driver Braking Behavior Modelling in the Car-following Scenario: An Importance Weight-based Transfer Learning Approach
  Zirui Li, Jianwei Gong, Chao Lu, Jinghang Li,
  IEEE Transactions on Industrial Electronics . IEEE T-IE 2022.
  [PDF]

• Interactive Behaviour Prediction for Heterogeneous Traffic Participants In the Urban Road: A Graph Neural Network-based Multi-task Learning Framework
  Zirui Li, Jianwei Gong, Chao Lu, Yangtian Yi,
  IEEE/ASME Transactions on Mechatronics. IEEE/ASME T-MECH 2021.
  [PDF]

• A Hierarchical Framework for Interactive Behaviour Prediction of Heterogeneous Traffic Participants based on Graph Neural Network
  Zirui Li, Chao Lu, Yangtian Yi, Jianwei Gong,
  IEEE Transactions on Intelligent Transportation Systems. IEEE T-ITS 2021.
  [PDF]

• Importance Weighted Gaussian Process Regression for Transferable Driver Behaviour Learning in the Lane Change Scenario
  Zirui Li, Jianwei Gong, Chao Lu, Junqiang Xi,
  IEEE Transactions on Vehicular Technology. IEEE T-VT 2020.
  [PDF]

Services

Reviewer

• IEEE Intelligent Vehicles Symposium 2018-2024.
• IEEE International Conference on Intelligent Transportation Systems 2018-2023.
• IEEE Transactions on Vehicular Technology.
• IEEE Transactions on Intelligent Transportation Systems.
• IEEE Transactions on Neural Networks and Learning Systems.
• Frontiers of Information Technology & Electronic Engineering.
• IEEE Transactions on Intelligent Vehicles.
• eTransportation.
• Geoscience and Remote Sensing Letters.
• IET Intelligent Transport Systems.
• Journal of Transportation Engineering, Part A.
• Sensors.
• Remote Sensing.
• IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
• IEEE International Conference on Unmanned Systems (ICUS).
• IEEE International Conference on Robotics and Automation (ICRA).
• Applied Sciences.
• Machines.
• Electronics.
• Scientific report.

Chair/Co-chairs

• Working group leader, intelligent vehicle risk assessment under IEEE Standard Assosiation (SA).
• Co-chair, workshop on Cooperative Decision-making for Connected and Automated Vehicles in Intelligent Transportation Systems at IEEE ITSC 2023
• Associate Editor for IEEE IV 2023
• Chair, workshop on Social, interactive and safe behaviors for AVs: benchmarks, models and applications at IEEE IV 2023.
• Organising committee, MFTS 2022
• Chair, workshop on Social and Interactive Behavior Modelling in Intelligent Transportation Systems at IEEE ITSC 2021.

Membership

• IEEE student member
• SAE China student member
• ITSS member

Talks

• Nov, 2023 Towards integrating subjective and objective risks in human-centric automated driving at 2023 ITS WiE/YP Workshop & Research Forum, Cairo, Egypt.
• Sep. 2023 Continual Driver Behavior Learning in Interactive Urban Scenarios at ITSC 2023, Bilbao, Bizkaia, Spain.
• Dec. 2022 Interactive Behavior Modeling for Vulnerable Road Users with Risk-taking Styles in Urban Scenarios: A Heterogeneous Graph Learning Approach at IEEE ITSC 2022 workshop.
• Dec. 2022 Towards Safe, efficient and Co-operative Decision-making for CAVs in Mixed Autonomy: An Attention-Enhanced Graphic Reinforcement Learning Approach at MFTS 2022.
• Nov. 2022 Interactive Behavior Modeling for Vulnerable Road Users with Risk-taking Styles in Urban Scenarios: A Heterogeneous Graph Learning Approach at IEEE ITSC 2022 workshop Cooperative and Automated Driving.
• Oct. 2022, Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic environments at IEEE ITSC 2022.
• June. 2022, Interactive Behavior Modeling for Vulnerable Road Users with Risk-taking Styles in Urban Scenarios: A Heterogeneous Graph Learning Approach at the Chair of Traffic Process Automation TU Dresden.
• Oct. 2021, Defining the Interactive Behavior: A Mutual Information-based Approach at hEAT Lab, TU Delft.
• June. 2021, Graph Neural Network for Interactive behaviours: Modelling, Risk Assessment and Multi-task Prediction at Traffic Dynamics, Modelling and Control lab, TU Delft. -April. 2021, Graph Neural Network for Interactive behaviours: Modelling, Risk Assessment and Multi-task Prediction at hEAT Lab, TU Delft.
• June. 2019, Transferable Driver Behavior Learning via Distribution Adaption in the Lane Change Scenario at IEEE IV 2019.
• June. 2018, Development and Evaluation of Two Learning-Based Personalized Driver Model for Pure pursuit Path-Tracking Behaviors at IEEE IV 2018.

Awards

• IEEE ITSS Young Professionals Travelling Fellowship (2023).
• Two-Year Graduate Student Fellowship of China Scholarship Councils (CSC), 2021-2023.
• Excellent Graduate Study Scholarship, 2021.
• National Scholarship for College Student, Ministry of Education of China, 2021.
• Champions for Formula Student Driverless China, 2017&2018.
• Innovation Scholarship first prize, Ministry of Industry and Information Technology, 2018.

Mentorship Experience

• Cheng Gong, Beijing Institute of Technology
• Yunlong Lin, Beijing Institute of Technology
• Chenxu Wen, Beijing Institute of Technology
• Fanyi Wei, TU Dresden
• Haowen Wang, Shanghai Jiaotong University
• Hailong Gong, Beijing Institute of Technology
• Lianzhen Wei,Beijing Institute of Technology
• Yangtian Yi, Beijing Institute of Technology
• Xianqi He, Beijing Institute of Technology
• jingyi Xu, Beijing Institute of Technology
• Yingqi Tan, Beijing Institute of Technology
• Tanran Chen, Beijing Institute of Technology