Figure 1: iLDM implementation using Neo4j and RTMaps .
Provided each domain is governed by its own inertia, huge alignment efforts are required to interoperate perception, communication and digital map systems. Current approaches focus on creating inter-domain standards (e.g., ISO LDM, ASAM simulation branch), utilise multi-sensor application middlewares (e.g., RTMaps, ROS, ADTF) and apply semantic alignment of concepts .
One significant example which have attracted the attention of the automotive industry is the Local Dynamic Map (LDM) concept. Initially defined as an structure of road information categorized in layers (from static to dynamic information), methods to implement the structure itself have started to appear as a response to the publication of the LDM-related ETSI/ISO standards. In  an interoperable LDM (iLDM) implementation was presented, including a data model aligned with the recently published ASAM OpenLABEL standard , to leverage the interconnection of sensor data recording vehicle set-ups with ground truth generation.
Authors: Marcos Nieto, Mikel García, Itziar Urbieta (Vicomtech)
 ETSI EN 302 895 V1.1.1. Intelligent Transport Systems (ITS); Vehicular Communications; Basic Set of Applications; Local Dynamic Map (LDM) Basic Set of Applications-ETSI EN 302 895. 2014. Available online: https://www.etsi.org/deliver/etsi_en/302800_302899/302895/01.01.01_60/en_302895v010101p.pdf (accessed on 16 June 2021).
 Urbieta, I.; Nieto, M.; García, M.; Otaegui, O. Design and Implementation of an Ontology for Semantic Labeling and Testing: Automotive Global Ontology (AGO). Appl. Sci. 2021, 11, 7782.
 García, M.; Urbieta, I.;Nieto, M.; González de Mendibil, J.;Otaegui, O. iLDM: An Interoperable Graph-Based Local Dynamic Map.Vehicles 2022, 4, 42–59. https://doi.org/10.3390/vehicles4010003.
 ASAM. ASAM OpenLABEL V1.0.0. Available online: https://www.asam.net/project-detail/asam-OpenLABEL-v100/ (accessed on 6 July 2021).