A comprehensive scientific review published in the European Transport Research Review examines how emerging data space architectures can overcome the critical data fragmentation bottleneck currently hindering the development of autonomous driving technologies.
To resolve these technical barriers, the authors conceptualize a specialized autonomous vehicle data space architecture anchored in the Reference Architecture Model established by the International Data Spaces Association.
Managing vehicular information within a data space requires an end-to-end data lifecycle framework spanning generation, acquisition, preparation, processing, model training, and compliant disposal.
Looking toward future transportation ecosystems, the review outlines critical governance, privacy, and architectural mechanisms required to scale autonomous driving data spaces across the global automotive industry.
Datasets and data spaces in the autonomous driving domain: insights and trends.