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Automated Mobility in Mixed Traffic

Automated Mobility in Mixed Traffic2026-09-03T11:44:54-04:00
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Chair: Yongqi Dong
Co-Chair(s): Xin Pei
Advisor:  Bart van Arem, Haneen Farah

Short Description

The ITSS Technical Committee on Automated Mobility in Mixed Traffic aims to foster collaboration among researchers, practitioners, and students across disciplines, promoting innovative research, professional activities, and industry-academia partnerships. It focuses on advancing knowledge and addressing challenges in mixed traffic through data-driven methods, behavioral modeling, safety analysis, state-of-the-art AI applications, and policy development, while organizing events to facilitate knowledge sharing and community engagement.

Goal

This committee is committed to fostering collaboration among multidisciplinary researchers, practitioners, and students in relevant fields of automated mobility and mixed traffic. The committee aims to promote interdisciplinary research, professional activities, industry-academia partnerships, and international collaborations. It will provide a platform for knowledge sharing, showcasing emerging datasets and state-of-the-art modelling methods, as well as identifying research gaps and future research directions.

Committee Activities

Activity Plan

The committee members have organized several events under the IEEE ITSS Conferences and will continue to contribute to the society through the following activities:

  • Organize special sessions/workshops/tutorials related to Automated Mobility and Mixed Traffic during the IEEE International Conference on Intelligent Transportation Systems (ITSC), IEEE Intelligent Vehicles Symposium (IV), IEEE International Conference on Systems, Man, and Cybernetics (SMC), and other renowned conferences;
  • Initiate new journal special issues on Automated Mobility in Mixed Traffic at IEEE Transactions on Intelligent Vehicles, IEEE Transactions on Intelligent Transportation Systems, IEEE Intelligent Transportation Systems Magazine, and other top-tier journals;
  • Hold online workshops and symposiums frequently for fast knowledge exchange;
  • Develop a research community website with a mailing list (draft already available);
  • Promote the committee during ITSC 2025 with its website and mailing list;
  • Establish and release an open-sourced resource repository for sharing resources;
  • Designing a summer school on mixed traffic with the cooperation of the IDEA League.

Upcoming events

Currently, the committee members are planning to organize the 4th edition of the workshop on “Automated Mobility in Emerging Mixed Traffic” with a theme on Toward Robust, Human-Centric, and Trustworthy Systems (https://www.itsc2026.mixedtraffic.org/), to be held during ITSC 2026 on September 15, Naples, Italy. The workshop has been approved.

Relevant topics include, but are not limited to:

1) Data & Simulation:

  • Mixed traffic datasets, open data practices and open-source platforms.
  • Empirical studies, field tests, and simulation models.
  • Mixed traffic state prediction and system modeling (long/medium/short term).
  • Behavioral and interaction modeling in mixed traffic.

2) Human Interaction:

  • Human factors, trust and user perception of automated systems.
  • Human-AI co-adaptation and meaningful human involvement in mixed traffic.
  • Ethical considerations in mixed autonomy systems

3) Advanced AI in Automated Driving:

  • AI methods in mixed traffic research.
  • LLMs and VLMs applied to automated driving.
  • Sensing, perception, planning and control in automated driving.

4) Safety & Robustness:

  • Model robustness and generalization.
  • Safety assurance and uncertainty quantification.
  • Explainable and trustworthy AI in safety-critical environments.

5) System Impacts:

  • Impact evaluation methods of mixed traffic.
  • Empirical evaluation across automation levels.
  • Traffic flow safety, efficiency, and energy performance in mixed traffic.
  • Societal and policy implications of mixed autonomy.

A Special Issue on “AI-Empowered Automated Driving in Mixed Traffic: From Sensing, Perception, to Planning and Control” is currently underway in the IEEE Transactions on Intelligent Transportation Systems. Submitted papers are under review, and the issue is expected to appear online in early 2027.

Lastly, the committee actively welcomes new members to join and support its initiatives, enabling even greater achievements as the committee grows.

Committee Website:  https://www.mixedtraffic.org/

Past Activities

Committee Members

Audrey Bruneau, Toyota Motor Europe, Belgium
Bart van Arem, Delft University of Technology, Netherlands
Cathy Wu, Massachusetts Institute of Technology, USA
Chang Liu, Institute for Computer Science and Control (HUN-REN SZTAKI), Hungary
Charlotte Fléchon, PTV Group, Germany
Danjue Chen, North Carolina State University, USA
Dong Ngoduy, Monash University, Australia
Erwin de Gelder, Netherlands Organization for Applied Scientific Research, Netherlands
Fangchieh Chou, Nissan Alliance Innovation Lab – Silicon Valley, USA
Felix Fahrenkrog, BMW Group, Germany
Hai L. Vu, Monash University, Australia
Haneen Farah, Delft University of Technology, Netherlands
Haoxuan Dong, National University of Singapore, Singapore
Irene Martínez, Delft University of Technology, Netherlands
Jianye Xu, RWTH Aachen University, Germany
Jie Zhu, Volvo Cars, Sweden
Jinhao Liang, National University of Singapore, Singapore
Lina Kattan, University of Calgary, Canada
Makridis Michail, ETH Zurich, Switzerland
Maria Laura Delle Monache, University of California, Berkeley, USA
Nan Zheng, Monash University, Australia
Panagiotis Angeloudis, Imperial College London, UK
Saeed Rahmani, Delft University of Technology, Netherlands
Selpi Selpi, Chalmers University of Technology, Sweden
Solmaz Razmi Rad, the Department of Road Transport (RDW), Netherlands
Shen Wang, University College Dublin, Ireland
Shian Wang, University of Kansas, USA
Soyoung Ahn, University of Wisconsin – Madison, USA
Tianyi Li, University of Minnesota, USA
Vahid Hashemi, Audi AG, Germany
Wanjing Ma, Tongji University, China
Xin Pei, Tsinghua University, China
Yiyun Wang, Delft University of Technology, Netherlands
Yongqi Dong, RWTH Aachen University, Germany
Zhe Fu, University of California, Berkeley, USA
Zhiyuan Liu, Southeast University, China
Zuduo Zheng, University of Queensland, Australia

Committee News

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