Automated Mobility in Emerging Mixed Traffic

Motivation and Aim:

Automated vehicles (AVs) hold promise for revolutionizing transportation by improving road safety, traffic efficiency, and overall mobility. Despite the steady advancement in high-level AVs in recent years, the complete deployment of AVs with full and/or high automation remains a gradual process. This transition entails a period of mixed traffic conditions, where AVs of varying automation levels coexist with human-driven vehicles (HDVs) and need to interact with vulnerable road users (e.g., cyclists and pedestrians). This new reality of mixed traffic will lead to unprecedented road environments and traffic conditions, accompanied by novel types of interactions among vehicles at different levels of automation, which could have significant implications for both traffic safety and efficiency. Moreover, these emerging intricate interactions make them uncertain and hard to analyze and predict. 

Data-driven, empirical, model-based, and simulation-based research are considered critical for understanding the complex dynamics of mixed traffic, interactive behaviours of AVs, HDVs and other road users, as well as the impact of these interactions on the safety and efficiency of mixed traffic. Emerging open-sourced datasets, especially real-world empirical data, allow researchers to investigate these interactions and their implications on the performance of mixed traffic. However, several challenges still hinder progress in this research domain, e.g., the generalization capability problem of the data-driven modelling, discrepancies between simulation and reality, the lack of high-quality mixed-traffic datasets, the unfamiliarity of the research community with advanced data processing and analysis methods as well as simulation tools, and the absence of in-depth collaboration between the research community and the Original Equipment Manufacturers (OEMs).

To address these challenges, and to build up upon the success and experience of last year’s version of the workshop at ITSC 2023, this second edition of the workshop aims to 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:

1. State-of-the-art automated mobility and mixed traffic related datasets

2. Data collection, processing, managing, and publishing

3. Mixed traffic status prediction (long/medium/short term)

4. Behavioural modelling and interaction in mixed traffic

5. Role of artificial intelligence in data-driven research for mixed traffic

6. Impact evaluation methods of mixed traffic

7. Empirical evaluation of different vehicle automation levels

8. Safety impacts of vehicle automation in mixed traffic

9. Traffic flow impacts and string stability in mixed traffic

10. Driving behavioural adaptation in mixed traffic

11. Energy consumption/demand in mixed traffic

12. Empirical studies and field tests about mixed traffic 

13. Assumptions and simulation models for mixed traffic

14. Open-access and reproducibility

15. Policies, regulations, and codes of practice

Agenda

Agenda at a glance:

The detailed agenda is availabe at https://www.itsc2024.mixedtraffic.org/agenda.

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, the organizers hosted a previous edition of this workshop: https://sites.google.com/view/itsc2023-mixed-traffic.

Acknowledgment

The workshop is supported by the interdisciplinary research community (also a pending IEEE ITSS Technical Committee) of Automated Mobility in Mixed Traffic (http://mixedtraffic.org/).