This position paper presents a vision for self-driving particle accelerators that operate autonomously with minimal human intervention. We propose that future facilities be designed through artificial intelligence (AI) co-design, where AI jointly optimizes the accelerator lattice, diagnostics, and science application from inception to maximize performance while enabling autonomous operation. Rather than retrofitting AI onto human-centric systems, we envision facilities designed from the ground up as AI-native platforms. We outline nine critical research thrusts spanning agentic control architectures, knowledge integration, adaptive learning, digital twins, health monitoring, safety frameworks, modular hardware design, multimodal data fusion, and cross-domain collaboration. This roadmap aims to guide the accelerator community toward a future where AI-driven design and operation deliver unprecedented science output and reliability.

翻译：本立场文件提出了一种自动驾驶粒子加速器的愿景，这类加速器能够在最少人工干预下自主运行。我们建议未来设施应通过人工智能协同设计进行构建，即AI从初始阶段就联合优化加速器晶格结构、诊断系统和科学应用，以最大化性能并实现自主运行。我们设想的并非在以人为本的系统上附加AI，而是从底层开始将设施设计为AI原生平台。我们概述了九个关键研究方向，涵盖智能体控制架构、知识整合、自适应学习、数字孪生、健康监测、安全框架、模块化硬件设计、多模态数据融合以及跨领域协作。这一路线图旨在引导加速器学界走向一个由AI驱动设计与运行的时代，以实现前所未有的科学产出与可靠性。