During the media roundtable at the 2026 World Intelligent Connected Vehicles Conference, Ge Yuming, Director of the Vehicle Networking and Intelligent Transportation Research Department at the China Academy of Information and Communications Technology, emphasized the pressing need for high-quality data—particularly that derived from extreme scenarios—in the realm of autonomous driving R&D. He underscored the necessity for collaborative efforts between enterprises and the government to bridge the existing data gap.

From an enterprise perspective, Ge Yuming suggested that diversified and cooperative supply models should be promoted. This involves leveraging roadside sensing and communication infrastructure to gather data from real-world, complex traffic scenarios. Additionally, he highlighted the importance of advancing generative autonomous driving data technologies to facilitate the synthesis of long-tail scenario data. Moreover, he encouraged the exploration of trustworthy and controllable cross-entity data circulation mechanisms.

On the national front, Ge Yuming stressed the significance of deepening pilot verifications and fostering the creation of high-quality datasets. He called for organized research into core technologies and support for the development of key technologies related to data collection, annotation, and generation. Furthermore, he advocated for the swift formulation of standards governing the application, circulation, and security of intelligent connected vehicle data. Lastly, he emphasized the importance of international collaboration, urging participation in the development of international regulations and standards.