n this paper, we propose an architecture integrating Multi-access Edge Computing (MEC) nodes into 5G base stations and roadside units to enable dynamic service orchestration for on-demand perception offloading. In this approach, compute- intensive perception tasks, such as object detection, are instan- tiated as services on nearby edge nodes, with resources being allocated adaptively based on the locations and trajectories of the vehicles. The system was designed to support user mobility through service replication and seamless handovers between perception service instances in different edge nodes as vehicles move across coverage areas, ensuring continuous service delivery and Quality of Service (QoS) guarantees. We evaluate the proposed architecture in a real-world 5G edge-enabled testbed using an autonomous vehicle running an object detection service. The results demonstrate that offloading perception via 5G and MEC yields substantially lower processing latency, and that smart orchestration mechanisms are able to react to user mobility and platform stress situations, avoiding service degradation, thus validating the approach for Cooperative, Connected, and Automated Mobility (CCAM) use cases.