Intelligent roadside infrastructure is a key enabler for cooperative intelligent transport systems (C-ITS), supporting vehicles equipped with automated driving systems (ADS), e.g., through enhanced environment perception. With a growing number and an expanding functional scope of roadside units, scalable and efficient operation becomes a challenge. This paper presents a cloud-native architecture for the operation of distributed roadside infrastructure based on a Kubernetes cluster spanning roadside units and a cloud server. Building on this architecture, a demand-driven orchestration approach is implemented to dynamically deploy resource-intensive services only when required. As a representative use case, a V2X-based collective perception application is deployed on-demand when a connected vehicle is nearby. The approach is validated in a real-world experiment in our test field in Aachen, demonstrating that the collective perception application starts in time for the vehicle to benefit from it. Without any demand, the application remains inactive, reducing energy consumption, channel congestion, and hardware wear. Beyond the primary evaluation, V2X recordings from the test field are analyzed to estimate the energy-saving potential of demand-driven operation. In summary, the results demonstrate the practical feasibility of cloud-native, demand-driven operation of roadside infrastructure and indicate its potential to improve scalability and (energy) efficiency in future C-ITS deployments.

翻译：智能路侧基础设施是协同智能交通系统（C-ITS）的关键支撑，通过增强环境感知等方式为配备自动驾驶系统（ADS）的车辆提供支持。随着路侧单元数量增长与功能范围扩展，其可扩展且高效的运行面临挑战。本文提出一种基于Kubernetes集群（覆盖路侧单元与云服务器）的云原生架构，用于分布式路侧基础设施的运行管理。在此架构基础上，实现需求驱动式编排方法，仅在必要时动态部署资源密集型服务。以V2X协同感知应用为典型案例，当网联车辆临近时按需部署该应用。通过在亚琛试验场的真实实验验证，该协同感知应用能及时启动以服务车辆。无需求时应用保持非活跃状态，从而降低能耗、信道拥塞与硬件磨损。除主要评估外，还分析试验场V2X记录数据以估算需求驱动运行模式的节能潜力。总之，实验结果证明了云原生、需求驱动的路侧基础设施运行的实践可行性，并揭示了其在未来C-ITS部署中提升可扩展性与（能源）效率的潜力。