RTMaps-based Local Dynamic Map for multi-ADAS data fusion
Egileak:
Data: 30.05.2022
Abstract
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.
BIB_text
title = {RTMaps-based Local Dynamic Map for multi-ADAS data fusion},
keywds = {
Automated driving, ADAS, SAE-L4/L5, Positioning, EGNSS, Sensor Fusion
}
abstract = {
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.
}
date = {2022-05-30},
}