Vehicle computing represents a fundamental shift in how autonomous vehicles are designed and deployed, transforming them from isolated transportation systems into mobile computing platforms that support both safety-critical, real-time driving and data-centric services. In this setting, vehicles simultaneously support real-time driving pipelines and a growing set of data-driven applications, placing increased responsibility on the vehicle operating system to coordinate computation, data movement, storage, and access. These demands highlight recurring system considerations related to predictable execution, data and execution protection, efficient handling of high-rate sensor data, and long-term system evolvability, commonly summarized as Safety, Security, Efficiency, and Extensibility (SSEE). Existing vehicle operating systems and runtimes address these concerns in isolation, resulting in fragmented software stacks that limit coordination between autonomy workloads and vehicle data services. This paper presents DAVOS, the Delaware Autonomous Vehicle Operating System, a unified vehicle operating system architecture designed for the vehicle computing context. DAVOS provides a cohesive operating system foundation that supports both real-time autonomy and extensible vehicle computing within a single system framework.

翻译：车辆计算代表了自动驾驶汽车设计与部署方式的根本性转变，将其从孤立的交通系统转变为支持安全关键型实时驾驶与数据驱动服务的移动计算平台。在此背景下，车辆需同时支持实时驾驶流水线与日益增长的数据驱动应用，这对车辆操作系统在协调计算、数据移动、存储与访问方面提出了更高要求。这些需求凸显出与可预测执行、数据与执行保护、高速率传感器数据高效处理以及长期系统可演进性相关的系统性考量，通常概括为安全性、防护性、高效性与可扩展性（SSEE）。现有车辆操作系统与运行时环境孤立地处理这些问题，导致软件栈碎片化，限制了自动驾驶工作负载与车辆数据服务之间的协调。本文提出DAVOS（特拉华自动驾驶操作系统），一种专为车辆计算场景设计的统一车辆操作系统架构。DAVOS提供了统一的操作系统基础，在单一系统框架内同时支持实时自动驾驶与可扩展的车辆计算。