This clause describes the integration of oneM2M IoT platforms and ETSI MEC edge computing to enable continuous real-time processing for autonomous vehicles (AVs). By combining these technologies, the system provides ultra-low-latency data handling, dynamic orchestration, and seamless service continuity, which are essential for safe and efficient autonomous driving.
At the heart of this architecture is a cloud-based oneM2M IN-CSE, which serves as a centralized hub to manage and store data related to each vehicle, including location, LIDAR and radar sensor data, and external conditions such as road infrastructure and traffic signals. When an AV enters a coverage area managed by a MEC node, the IN-CSE dynamically offloads computational tasks—including real-time object detection, collision risk analysis, and navigation updates—to MN-CSE instances deployed on the edge. These MN-CSEs process time-sensitive data locally, providing immediate decision-making feedback to the vehicle with minimal latency.
The MN-CSE instances not only consume data generated by the AV but also integrate additional real-time information from other MEC applications, such as local traffic analytics and environmental monitoring. This collaboration enriches the AV’s situational awareness and enables context-aware decision-making, including adaptive braking, lane changes, and obstacle avoidance.
As the AV moves between coverage areas, the system seamlessly transitions its services to the next MEC node. The architecture continuously tracks the vehicle’s position and triggers a migration process when the vehicle approaches a new MEC zone. During migration, the MN-CSE’s runtime state, offloaded applications, and contextual data are securely and rapidly transferred to the new edge node. This ensures that all critical services remain active without disruption, maintaining consistent performance and safety throughout the vehicle’s journey.
The oneM2M platform orchestrates data synchronization between the cloud and edge layers to guarantee that all information remains accurate and up-to-date. This edge-to-edge service continuity is crucial for sustaining AV operations in dynamic environments, where even brief interruptions could compromise safety.
By integrating oneM2M’s standardized data management and interoperability with MEC’s distributed, low-latency processing capabilities, this use case demonstrates a scalable approach to supporting autonomous vehicle services. The architecture supports both static IoT applications and highly dynamic mobility services, dynamically adapting to vehicle movement and network conditions. As a result, AVs benefit from real-time updates, uninterrupted decision-making capabilities, and seamless service delivery as they traverse multiple zones.
Enabling standardized IoT deployments in MEC environments for safe and efficient autonomous mobility.
The founding members of this initiative are CNIT, UNIMORE, xFlow, JK Consulting and Projects, FSCOM, Sejong University, Digital SME, Deutsche Telekom AG, Exacta GSS, Networks SRL, and Telecom Italia S.p.A. To register or learn more, contact estimed@etsi.org or visit https://estimed.etsi.org.
About ETSI
ETSI provides members with an open and inclusive environment to support the development, ratification, and testing of globally applicable standards for ICT systems and services across all sectors of industry and society. We are a non-profit body with more than 950 member organizations worldwide, drawn from 64 countries and five continents. Our members include large and small private companies, research entities, academia, government, and public organizations. ETSI is officially recognized by the EU as a European Standardization Organization (ESO). For more information, visit https://www.etsi.org.
Author:
CNIT
