RTMaps-based Local Dynamic Map for multi-ADAS data fusion
This addresses the problem of integrating diverse ADAS data for real-time decision-making in vehicles, though it appears incremental by applying existing middleware to an emerging standard.
The paper tackles the lack of defined mechanisms for fusing information across layers in Local Dynamic Maps (LDM) by implementing a real-time LDM component using RTMaps middleware, deployed in vehicles and road-side units to serve as a central database for multi-ADAS systems.
Work on Local Dynamic Maps (LDM) implementation is still in its early stages, as the LDM standards only define how information shall be structured in databases, while the mechanism to fuse or link information across different layers is left undefined. A working LDM component, as a real-time database inside the vehicle is an attractive solution to multi-ADAS systems, which may feed a real-time LDM database that serves as a central point of information inside the vehicle, exposing fused and structured information to other components (e.g., decision-making systems). In this paper we describe our approach implementing a real-time LDM component using the RTMaps middleware, as a database deployed in a vehicle, but also at road-side units (RSU), making use of the three pillars that guide a successful fusion strategy: utilisation of standards (with conversions between domains), middlewares to unify multiple ADAS sources, and linkage of data via semantic concepts.