Automated vehicles (AVs) are becoming realistic with the rapid development of information technologies and hardware equipment. Traditional homogeneous traffic solely comprising human-driven vehicles (HDVs) is transiting to mixed traffic including both AVs and HDVs. Considering pedestrians further increases the complexity of a transportation system. In such a mixed traffic, understanding complex interactions between AVs, AVs and HDVs, AVs and pedestrians, and even AVs and road-side infrastructures is a key to enhancing traffic safety and improving traffic efficiency. However, accurate modeling, evaluation, and simulation of complex interactions in mixed traffic comprising pedestrians, AVs, and HDVs are not adequately studied.

This workshop provides a unique platform to gather researchers, policymakers, and industrial partners worldwide, aiming to advance the modeling, evaluation, and simulation methods in understanding the interaction processes in a mixed transportation system through:

• Showcasing research platforms for human-in-the-loop simulations and identifying their respective characteristics;

• Proposing state-of-the-art models for modelling interactions in safety evaluation, decision-making, and traffic control in mixed traffic scenarios;

• Validating models through empirical experiments incorporating cutting-edge techniques such as virtual reality and human-in-the-loop simulations;

• Providing a unique opportunity for knowledge and resource sharing by gathering notable researchers from leading groups and platforms focusing on related research fields.

Cross-disciplinary research is highly encouraged in this workshop, allowing participants to communicate with researchers using diverse equipment and techniques and thinking from different perspectives. The initiative is to promote resources and technology sharing across multiple disciplines, disseminate valuable research among fields, and establish unified standards over research groups. Moreover, platforms, datasets, and related technology developments discussed in this workshop will be integrated into a GitHub repository for summarizing the outcomes.

• Modeling, evaluation, and simulation of both explicit and implicit interactions in mixed traffic

• Empirical analysis of pedestrian-vehicle interactions

• Driver/pedestrian behavior modeling in mixed traffic

• Safety evaluation and impact of interaction processes in mixed traffic

• Calibration and validation using human-in-the-loop simulations

• Data collection, processing, managing, and publishing related to interactions in mixed traffic

• Traffic state estimation of pedestrians, AVs, and HDVs in mixed traffic

• AI for Traffic management and control in mixed traffic

• Driving environment perception via interactions

• Advanced simulation platforms

• How can we use AI to help understand complex interactions between traffic participants?

• How do simulations help understand complex interactions between traffic participants?

• What are the gaps between simulations and reality?

• What are human roles in the future transportation systems?

• Opening speech: Shaocheng JIA

• Simulation: Machine Learning From It, For It, and Beyond It

Prof. Hua WEI, Arizona State University

13:10 — 13:30

• Testing Scenario Generation for Cooperative Perception in Mixed Traffic

Prof. Xin PEI, Tsinghua University

13:30 — 13:50

• The Other Side of Autonomous Vehicles - Human Road Users

Prof. Siyang ZHANG, Tongji University

13:50 — 14:10

• Knowledge-Driven Urban Traffic Control via Foundation Intelligence

Prof. Xingyuan DAI, Institute of Automation, Chinese Academy of Science

14:10 — 14:30

• Towards Next Generation of Pedestrian and Connected Vehicle in-the-Loop Research: A Digital Twin Co-Simulation Framework

Dr. Zijin WANG, The University of Central Florida

14:30 — 14:50

• An introduction to OnSite Platform: Open Natural Driving Intelligence Automotive Simulation Test Environment

Ye Tian, Xiaocong Zhao, Peng Hang, Lishengsa Yue, and Haoyang Liang, Tongji University

14:50 — 15:05

• Planning and Control Algorithm Validation: Applications and Hands-on Experience with the OnSite Platform

Tianqi Ke, Tsinghua University

15:05 — 15:20

• Towards More Realistic Policy Control in Traffic Systems - with a Case Analysis in Traffic Signal Control

Longchao Da, Arizona State University

15:40 — 15:55

• Towards Interactive Autonomous Vehicle Testing: Vehicle-Under-Test-Centered Traffic Simulation

Yiru Liu, Tongji University

15:55 — 16:10

• Exploring the Influence of Pedestrian Attitude, Propensity, and Risk Perception on Gap Acceptance between Platooning Autonomous Trucks

Yun Ye, Ningbo University

16:10 — 16:25

• How Differently Do Pedestrians Interact with Autonomous Vehicles? An Investigation in Four Different Cities

Gabriel Lanzaro, The University of British Columbia

16:25 — 16:40

• Participants

Prof. Hua WEI, Prof. Xin PEI, Prof. Siyang ZHANG, Prof. Xingyuan DAI, Dr. Zijin WANG, Shaocheng JIA, Dr. Haoyang LIANG

• Closing remarks: Dr. Haoyang LIANG

• Shaocheng JIA, The University of Hong Kong, shaocjia@connect.hku.hk 

Shaocheng Jia is currently a Ph.D. candidate at The University of Hong Kong and a member of IEEE, IEEE ITSS, INFORMS, INFORMS TSL, CHTS, IACIP, and ITS of HKU. He received his B.E. degree from the Department of Electronic Information Engineering, China University of Petroleum (Beijing), and M.E. degree from the Department of Automation, Tsinghua University, in 2014 and 2018, respectively. His research interests include intelligent perception and control, connected and automated transportation, stochastic modelling and optimization, and machine learning. Shaocheng has published over 10 papers in prestigious journals and conferences, including Transportation Science, IEEE TITS, TR-Part C, the International Symposium on Transportation and Traffic Theory (ISTTT), etc., as well as 6 national invention patents. Shaocheng is also a recipient of the Outstanding Master’s Dissertation Awards from CHTS and Tsinghua University. He has chaired the regular session AVSS01 in the 26th IEEE ITSC and a Young Scholar Tech Talk at HKU, co-organized the workshop WS12 in the 26th IEEE ITSC, and been a reviewer for IEEE TITS, IEEE TNNLS, IEEE TMC, TRR, IEEE ITSC, TRB, etc.

• Dr. Haoyang LIANG, Tongji University, lianghy@connect.hku.hk 

Haoyang Liang is currently a Postdoc at Tongji University and a member of IEEE. He received his B.S. degree from the Department of Civil Engineering, Tsinghua University, and the Ph.D. degree from the University of Hong Kong, in 2018 and 2022, respectively. His research interests include crowd dynamics, pedestrian-vehicle interaction, virtual reality, and human factors. Haoyang has contributed to prestigious journals and conferences such as TR-Part B, PLoS ONE, and the International Symposium on Transportation and Traffic Theory (ISTTT). Currently, he is the principle investigator at Tongji University's CAVE VR lab, focusing on digital twin platforms for mixed traffic simulation and testing.

• Prof. Jian SUN, Tongji University, sunjian@tongji.edu.cn 

Sun Jian received the Ph.D. degree from Tongji University in 2006. Subsequently, he was at Tongji University as a Lecturer, and then promoted to the position as Professor in 2011, where he is currently a Professor with the College of Transportation Engineering and the Dean of the Department of Traffic Engineering. His main research interests include traffic flow theory, traffic simulation, connected vehicle-infrastructure system, and intelligent transportation systems. Sun Jian has published over 100 peer-reviewed articles, authored three monographs, and co-edited three provincial and ministerial standards. Additionally, he has filed more than 30 national invention patents and secured 6 software copyrights. He also contributes as the Associate Editor for the IET Intelligent Transportation Systems and the Journal of Intelligent and Connected Vehicles.

• Prof. Yun YE, Ningbo University, yeyun1@nbu.edu.cn 

Yun YE is currently an Associate Professor in the Faculty of Maritime and Transportation at Ningbo University and a member of IEEE. He received his B.E. and Ph. D. degree from Zhejiang University and The University of Hong Kong, in 2017 and 2021, respectively. During 2021-2023, he served as research engineer at Central Research Institute and Central Media Technology Institute, 2012 Lab, Huawei Technologies Co., Ltd. His current research interests include traffic safety, VR/AR-based simulation, pedestrian behaviors, and pedestrian-AVs interaction. Dr. YE has published more than 10 papers in prestigious journals and conferences, including Safety Science, Accident Analysis and Prevention, Travel Behaviour and Society, TRB Annual Meeting, etc. and serves as reviewers for IEEE TITS, TR-Part F, Transportmetrica A: Transport Science, Journal of Transportation Safety & Security, etc. He has also been responsible for or participated in more than 10 research and practical projects.

• Xiaocong ZHAO, Tongji University, zhaoxc@tongji.edu.cn 

Xiaocong Zhao is a Ph.D. candidate at the College of Transportation Engineering, Tongji University, China. From November 2022 to December 2023, he was a visiting researcher at Technische Universität Dresden, Germany. His primary research interests include social behaviors in driving interaction, decision-making in interactive driving scenarios, and computational game theory. Xiaocong led the champion group in the 2022 Commonroad Motion Planning Competition for Autonomous Vehicles. He has contributed to notable journals such as IEEE T-ITS, TR-Part C, Computer-Aided Civil and Infrastructure Engineering (CACAIE), and AA&P. Since 2021, he has been a regular attendee and contributor at IEEE conferences, including the ITSC and IV, participating in seminars and workshops. Xiaocong has served as a reviewer for TR-Part C, IEEE T-ITS, T-VT, ITSC, and IV. He is currently the working group leader of an IEEE Intelligent Transportation Systems Society (ITSS) New Initiative project.

• Prof. Weizi LI, University of Tennessee, Knoxville, weizili@utk.edu 

Weizi Li received his Ph.D. in Computer Science from the University of North Carolina at Chapel Hill. Currently, he is an assistant professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. Prior to this position, he was a Michael Hammer Postdoctoral Fellow at the Institute for Data, Systems, and Society (IDSS) of Massachusetts Institute of Technology (MIT). His current research interests include Intelligent Transportation Systems, Multi-agent Simulation, Virtual Environments, Machine Learning, and Robotics.

• Prof. Meng WANG, Technische Universität Dresden, meng.wang@tu-dresden.de 

Meng Wang received the B.Sc. degree from Tsinghua University in 2003, the M.Sc. degree from the Research Institute of Highway (RIOH), Ministry of Transport, in 2006, and the Ph.D. degree (Hons.) from TU Delft in 2014. He was an Assistant Professor (tenured in 2019) at the Department of Transport and Planning of TU Delft, from 2015 to 2021 and the Co-Director of the Electric and Automated Transport Laboratory (hEAT lab). From 2006 to 2009, he was an Assistant Researcher at the National ITS Center of RIOH and a Post-Doctoral Researcher at the Automotive Group, Faculty of Mechanical Engineering, TU Delft, from 2014 and 2015. He is a Full Professor (W3) and the Head of the Chair of Traffic Process Automation with the “Friedrich List” Faculty of Transport and Traffic Sciences, Technische Universität Dresden. His main research interests are traffic flow modelling and control, driver behaviour, control design, and impact assessment of connected and automated vehicles. He was a recipient of the IEEE ITS Society Best Ph.D. Dissertation Award in 2015 and the IEEE International Conference on Intelligent Transportation Systems (ITSC) Best Paper Award in 2013. He is an Associate Editor of the journal IEEE T-ITS, IET ITS, and Transportmetrica B and the Editorial Board Member of Transportation Research Part C.

• Iftekharul ISLAM, University of Tennessee, Knoxville, mislam73@vols.utk.edu  

Iftekharul Islam is a Ph.D. student in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. He received his B.Sc. in Computer Science from Rajshahi University of Engineering & Technology, Bangladesh. His research interests span Reinforcement Learning, Machine Learning, Transportation Autonomy, and Hyperspectral Imaging.  Prior to joining the University of Tennessee, he worked as a Lecturer at Bangladesh University.

• Prof. Hua WEI, Arizona State University

Hua Wei is an assistant professor at the School of Computing and Augmented Intelligence (SCAI) in Arizona State University (ASU). He got his PhD from Pennsylvania State University in 2020. He specializes in data mining, artificial intelligence and machine learning. He has been awarded the Best Paper at ECML-PKDD 2020, and his students and his own research work as a first author have been published in top conferences and journals in the fields of machine learning, artificial intelligence, data mining, and control (NeurlPS, AAAI, KDD, IJCAI, CDC, ECML-PKDD, WWW). His research has been funded by the National Science Foundation, the Department of Energy and the Department of Transportation.

• Prof. Xin PEI, Tsinghua University

Dr. Xin PEI received B.S. and M.S. degrees from Tsinghua University in 2005 and 2007, respectively, and Ph.D. degree from the University of Hong Kong in 2011. She is currently a Research Associate Professor with the Department of Automation in Tsinghua University. Her research focuses on road safety analysis. Research interests include safety evaluation, driving behavior analysis, CAV related safety, AI methods for traffic data analysis, etc. Dr. Pei has published more than 80 SCI/SSCI/EI-indexed papers, and serves as reviewers for IEEE Transactions on Intelligent Transportation Systems, Accident Analysis and Prevention, IEEE ITSC, TRB Annual Meeting, etc. She has also been responsible for or participated in more than 30 research and practical projects.

• Prof. Siyang ZHANG, Tongji University

Siyang Zhang works as an assistant professor at College of Transportation Engineering, Tongji University. She obtained her PhD degree from University of Missouri-Columbia, with a Civil Engineering major and a Statistics minor. She has been dedicated to multi-modal transportation simulator development and application, human factors, and road traffic safety since 2014. Her work was recognized as High-Value research by AASHTO in 2023 and 2021, and was adopted and implemented by Missouri Department of Transportation. She received TRB AHB55 Best Paper Award and was awarded Women Transportation Seminar (WTS) Helene M. Overly Memorial Scholarship in 2019. She served Central Missouri ITE as president, vice president, and secretary, and now serves as a member of DTS editorial board, and a reviewer of IEEE-series and TR-series journals.

• Prof. Xingyuan DAI, Institute of Automation, Chinese Academy of Science

Xingyuan Dai received his Ph.D. degree in Control Theory and Control Engineering from the University of Chinese Academy of Sciences, Beijing, China. He is currently serving as an Assistant Professor at the State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences. His research interests include intelligent transportation systems, intelligent vehicles, and deep reinforcement learning. He has published over 40 papers in TR-Part C, T-ITS, T-IV, CVPR, ICML, ITSC, et al, and has been awarded the Best Student Paper Award at ITSC 2022. He is currently an Associate Editor for IEEE Transactions on Intelligent Vehicles.

• Dr. Zijin WANG, University of Central Florida

Zijin Wang received his Ph.D. degree in Civil Engineering from the University of Central Florida in 2024. He is currently a Post-doctoral Researcher with the Department of Civil, Environmental, and Construction Engineering in the University of Central Florida. His research interests include traffic simulation, driving simulator study, CAV decision making, cooperative driving, and digital twin for ITS applications. He has published multiple papers in T-IV, AAP, and TRR. He also serves as a reviewer of various SCI-indexed journals.

• 2024 IEEE ITSS New Initiatives Program: Evidence-Based Communication Channel for Autonomous Driving Technology

• National Natural Science Foundation of China

• China Postdoctoral Science Foundation