Microservice-Based Architecture for Enhancing Road Safety with Support for Low-Latency Services

Augmented Reality (AR) and edge computing can be used to enhance Vulnerable Road User (VRU) safety, leveraging a greater degree of interaction with the user and presenting real-time warning notifications, a use case that demands low latency for critical warnings. However, a new Multi-Access Edge Computing (MEC) system that distributes computational needs across edge nodes within the infrastructure is needed to meet these low-latency requirements. This paper proposes a microservice architecture designed to process data from various sources, including awareness and perception messages from road users and smart city sensors, through multiple communications technologies such as ITS-G5 and 5G. This work employs peer-to-peer decentralized communications to perform seamless integration and real-time processing, ensuring timely and relevant warnings for VRUs. Real-world road tests conducted in the Aveiro Tech City Living Lab in Aveiro, Portugal, and in commercial V2X equipment in the Autonomous Driving Test Field Baden-Württemberg in Karlsruhe, Germany, showed a maximum end-to-end latency of 110 ms, showcasing the system’s capabilities in real-life demanding use cases and the system’s interoperability.