ADAS and AV programs collect enormous volumes of sensor data, yet model improvement depends on finding and labeling the events that truly matter. This roundtable will explore how teams can connect fleet logging, edge-case discovery, data curation, human-in-the-loop annotation, quality assurance, and validation feedback into one practical data flywheel. DDD will direct the conversation to discuss how to prioritize data for labeling, where AI-assisted annotation can be trusted, how to measure label quality by model impact, and what traceability is needed from raw event to validated dataset. The session is designed for OEMs, Tier 1s, perception teams, data platforms, and annotation partners working together.
By engineers, for engineers: A technically grounded guide to the rapidly evolving in-cabin technology industry and companies.
