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Published on: 2026-06-26Updated on: 2026-08-18
Associated article: https://doi.org/10.26599/COMMTR.2026.9640038 From: Communications in Transportation Research

MILD: Mediator Agentic System with Bidirectional Perception and Multi-Layered Alignment for Human-Vehicle Collaboration

Jiyao Wang, Yunbiao Wang, Yubo Jiao, Xiao Yang, Dengbo He, Sasan Jafarnejad, Luis Miranda-Moreno, Raphaël Frank, Jiangbo Yu

The code and data for MILD. To access the original video of AIDE, DMD, and DriveLM, please refer to their source papers.

Automated vehicleLarge language models
DOI: 10.26599/ETSD.2026.9190024
CSTR: 32009.11.ETSD.2026.9190024
Category: Road transport data (passenger), Others
Data Type: Text data
Data and Code Disclosure and Sharing Policy
Cite this dataset
Jiyao Wang, Yunbiao Wang, Yubo Jiao, et al. MILD: Mediator Agentic System with Bidirectional Perception and Multi-Layered Alignment for Human-Vehicle Collaboration. ETS-Data, 2026. https://doi.org/10.26599/ETSD.2026.9190024
Jiyao Wang, Yunbiao Wang, Yubo Jiao, et al. MILD: Mediator Agentic System with Bidirectional Perception and Multi-Layered Alignment for Human-Vehicle Collaboration. ETS-Data, 2026. https://cstr.cn/32009.11.ETSD.2026.9190024
MILD103.30 MB
Funding information

The authors based in Quebec, Canada gratefully acknowledge financial support from the Fonds de recherche du Québec AUDACE International Program (FRQ AUDACE International), the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant program, and the Canada Research Coordination Committee’s New Frontiers in Research Fund (CRCC NFRF).

This research was also funded in part by the Luxembourg National Research Fund (FNR), grant reference: INR/AUDACE/25/19343746/EAMCIMCA. For the purpose of open access, and in fulfilment of the obligations arising from the grant agreement, the authors have applied a Creative Commons Attribution 4.0 International (CC BY 4.0) license to any Author Accepted Manuscript version arising from this submission.