Autonomy, from the Greek autos (self) and nomos (law), refers to the capacity to operate according to internal rules without external control. Autonomous vehicles (AuVs) are therefore understood as systems that perceive their environment and execute pre-programmed tasks independently of external input, consistent with the SAE levels of automated driving. Yet recent research and real-world deployments have begun to showcase vehicles that exhibit behaviors outside the scope of this definition. These include natural language interaction with humans, goal adaptation, contextual reasoning, external tool use, and the handling of unforeseen ethical dilemmas, enabled in part by multimodal large language models (LLMs). These developments highlight not only a gap between technical autonomy and the broader cognitive and social capacities required for human-centered mobility, but also the emergence of a form of vehicle intelligence that currently lacks a clear designation. To address this gap, the paper introduces the concept of agentic vehicles (AgVs): vehicles that exhibit agency, the capacity for goal-driven reasoning, strategic adaptation, self-reflection, and purposeful engagement with complex environments. We conclude by outlining key challenges in the development and governance of AgVs and their potential role in shaping future agentic transportation systems that align with user and societal needs.

翻译：自主性（autonomy）源自希腊语 autos（自我）和 nomos（法则），指依据内部规则运行、不受外部控制的能力。因此，自主车辆被理解为感知环境并独立于外部输入执行预设任务的系统，这与SAE驾驶自动化分级标准一致。然而，近期研究和实际部署已开始展示超出该定义范围的车辆行为，包括与人类的自然语言交互、目标适应、情境推理、外部工具使用以及处理未预见的伦理困境——这些能力部分得益于多模态大型语言模型。这些进展不仅凸显了技术自治与以人为本移动性所需的更广泛认知和社会能力之间的差距，还揭示了一种尚缺乏明确命名的车辆智能形式的涌现。为弥合这一鸿沟，本文提出“代理型车辆”（agentic vehicles, AgVs）概念：即具备能动性（agency）、目标驱动推理、策略适应、自我反思以及有目的地处理复杂环境能力的车辆。最后，我们概述了AgV开发与治理中的关键挑战，以及其在塑造未来符合用户和社会需求的代理型交通系统中的潜在作用。