Title:

Curating, Processing, and Utilizing Connected and Automated Vehicle (CAV) Data: From Storage to Platform Integration

Modality:

Half-day (3 hours plus breaks)

Scope

Connected and Automated Vehicles (CAVs) are transforming the landscape of modern transportation. These vehicles generate massive volumes of heterogeneous data from diverse sources, including onboard sensors, communication modules, and control systems. Effectively managing this data is critical to advancing the development, testing, validation, and deployment of emerging transportation technologies.

This special session aims to convene experts from academia, industry, and government to explore state-of-the-art strategies for CAV data management. Topics of interest include methods for efficient data curation, robust database design, and scalable real-time data platforms. The session also seeks to address the integration of data systems with simulation and physical testing environments, which is essential for supporting rigorous evaluation of CAV technologies.

As transportation systems become increasingly data-driven, this session will highlight innovative approaches and practical case studies that demonstrate how well-managed data can enable smarter, safer, and more efficient mobility solutions. Through interdisciplinary collaboration, we aim to foster a deeper understanding of the technical and organizational challenges involved in CAV data management, and to identify actionable solutions that support the future of intelligent transportation.

This session will focus on, but is not limited to, the following topics:

• CAV data curation, labeling, and metadata generation
• Data storage architectures for scalable and efficient access
• Real-time and batch processing of CAV data
• Data platforms for testing and validation environments
• Integration of CAV data with simulation and hardware-in-the-loop (HiL) testbeds
• Open-source and standardized data formats and APIs
• Privacy, security, and ethical considerations in CAV data sharing
• Case studies of large-scale CAV data infrastructure or repositories
• Cloud-edge hybrid data handling for CAVs
• Interoperability and multi-source data fusion (e.g., infrastructure + vehicle + user data)