DBMay 13, 2022
RTMaps-based Local Dynamic Map for multi-ADAS data fusionMarcos Nieto, Mikel Garcia, Itziar Urbieta et al.
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.
2.3NIApr 22
Assessing the Challenges of Collective Perception via V2I Communications in High-Speed Scenarios with Open Road TestingJon Ander Iñiguez de Gordoa, Iker Alkorta, Itziar Urbieta et al.
This paper presents a comprehensive end-to-end evaluation of an infrastructure-assisted collective perception (ICP) system deployed on a highway using ITS-G5 technology. Open-road tests were conducted in the Bizkaia Connected Corridor (BCC), an operational corridor which covers a winding highway, enabling a realistic assessment of system performance in diverse traffic scenarios. The evaluation included three main aspects: (1) end-to-end Vehicle-to-Everything (V2X) communication latency, with a breakdown of delays introduced by each system component; (2) the effective range of ITS-G5 communications between vehicles and infrastructure; and (3) the perception system, using an independent sensor setup for ground truth annotation to account for errors beyond the detection model, such as synchronization, localization, and calibration inaccuracies. The results reveal that object detection and asynchronous transmission of collective perception messages (CPMs) are major latency bottlenecks, with results showing that synchronizing CPM transmission with local perception can reduce delays by up to 33%. Additionally, onboard perception struggles with detecting objects beyond 50 meters, highlighting the importance of collective perception in highway environments, where communication ranges significantly exceed detection limits. The findings provide valuable insights to optimize ICP deployments, supporting safer and more efficient cooperative mobility systems.