Automated Mobility in Mixed Traffic

Motivation and Aim: 

The integration of automated vehicles (AVs) into existing transportation systems is transforming our mobility, presenting unprecedented challenges and opportunities in mixed-traffic environments. In mixed traffic, AVs of varying automation levels coexist with and navigate alongside human-driven vehicles (HDVs) and vulnerable road users (e.g., cyclists and pedestrians). While AVs operate through algorithms, human drivers rely on intuition, experience, and social cues, creating intricate differences in decision-making approaches. These new realities will lead to unprecedented road traffic conditions, accompanied by novel types of interactions, which could have significant implications for both traffic safety and efficiency, uncertain and hard to analyze and predict.

Data-driven, empirical, model-based, and simulation-based research with the emerging powerful AI algorithms and tools are considered critical for understanding the complex dynamics, interactive behaviors, and their impact in mixed traffic. However, several challenges still hinder progress, e.g., the generalization capability of the data-driven modeling, discrepancies between simulation and reality, the lack of high-quality mixed-traffic datasets, and the absence of in-depth collaboration between academia and industry.

 Bringing together diverse perspectives and expertise, this workshop aims to mitigate these gaps, advance the understanding of mixed traffic dynamics, and shape the development of AI-driven mobility systems that are both innovative and responsive to societal needs.  Building upon the success and experience of previous versions of the workshops at ITSC 2024 and ITSC 2023, this third edition further push forward the research for automated mobility in mixed traffic by: 

• Providing a unique opportunity for knowledge sharing by gathering together notable researchers in the domain and experts from the leading data collection and vehicle automation companies;

• Showcasing the available emerging datasets, their formats, and structure, and discuss their limitations, and challenges for the current research;

• Showcasing and validating state-of-the-art modelling methods and assumptions, with mixed traffic flow datasets; 

• Identifying current research gaps and future research directions, as well as the opportunities for creating synergy between data-driven and theory-driven research;

• Presenting the new IEEE ITSS Technical Committee with its community website for sharing relevant resources (open-sourced datasets, simulation tools and platforms, and pertinent publications).

Participants of this workshop will have the opportunity to communicate with other researchers and experts face-to-face. The goals are to share best practices, discuss common problems that have not been addressed, and gain insights on future research directions, so as to stay ahead of the curve. Additionally, a set of relevant research resources, e.g., open-sourced datasets with detailed summaries, simulation platforms and tools, relevant publication list, will be shared with the participants after the workshop.

Topics of Interest: 

Interested researchers are invited to present their works on the following relevant topics, including but not limited to:

• Automated mobility and mixed traffic related datasets;

• Data collection, processing, managing, and publishing;

• Mixed traffic status prediction (long/medium/short term);

• Behavioural modelling and interaction in mixed traffic;

• Traffic flow in mixed traffic;

• AI in data-driven research for mixed traffic; 

• LLM and VLM applied for AVs; 

• Meaningful human control in mixed autonomy;  

• Robustness, transparency, and trustworthy of AI in mixed traffic; 

• Impact evaluation methods of mixed traffic; 

• Empirical evaluation of different vehicle automation levels; 

• Driving behavioral adaptation in mixed traffic; 

• Energy consumption/demand in mixed traffic; 

• Empirical studies and field tests about mixed autonomy; 

• Assumptions and simulation models for mixed traffic;

• Open-access and reproducibility of research in mixed traffic;

• Policies, regulations, and codes of practice.

Potential Speakers 

Agenda

The detailed agenda will be available and released later.

Resource Repository

The online resource repository for sharing relevant Datasets, Simulation Platforms, and Publications on Automated Mobility in Emerging Mixed Traffic can be accessed at https://qiqiqi.gitbook.io/mixed-traffic and https://github.com/IEEE-ITSS-OpenHub/Resource---Emerging-Mixed-Traffic-of-AV-and-HDV.

If you want to share relevant resources with the research community, please contact the workshop organizers.

Previous Editions 

At IEEE ITSC 2023 and 2024, the organizers hosted a previous edition of this workshop:  

https://www.itsc2024.mixedtraffic.org/ ,

https://sites.google.com/view/itsc2023-mixed-traffic.

Acknowledgment

The workshop is supported by the interdisciplinary research community and IEEE ITSS Technical Committees of Automated Mobility in Mixed Traffic and Cooperative & Connected Vehicles.