首个原生支持OpenSCENARIO 2.x的高保真自动驾驶仿真框架
OSC2Runner: OpenSCENARIO 2.x Compliant High-Fidelity AV Simulation in CARLA
- 通过多遍编译器架构将v2.x DSL直接转为CARLA可执行行为树
- 实现毫秒级同步与精确空间触发，100.0毫秒内完成跨智能体通信
- 适合自动驾驶验证、HIL测试及LLM生成场景的确定性仿真
基于场景的自动驾驶测试主要依赖旧版ASAM OpenSCENARIO 1.x XML标准，因现有连续仿真框架缺乏对新成熟版本v2.x领域专用语言（DSL）的原生支持。将旧解析器适配v2.x逻辑会引入时空漂移、异步事件延迟和人工运动突变。针对此执行缺口，OSC2Runner首次提出原生映射OpenSCENARIO v2.x DSL至CARLA的调度框架。该框架通过多遍转换器架构，将场景翻译形式化为编译流程，跳过静态轨迹回放，直接合成类型安全的抽象语法树为动态确定性行为树（py_trees），并原生对接CARLA原子接口。在高度并发对抗性案例中实证验证表明：逐周期确定性、精确空间触发判定，以及100.0毫秒内跨智能体黑板同步。运动学分析证实严格遵循连续环境边界。该架构使基于场景的测试从近似行为解析跃升为数学严谨执行，为联合仿真、硬件在环测试及自动化大模型驱动生成流水线建立确定性后端。
原文摘要 · Abstract (English)
Scenario-Based Testing predominantly relies on the legacy ASAM OpenSCENARIO 1.x XML standard because existing continuous simulation frameworks lack native execution support for the recently matured v2.x Domain-Specific Language (DSL). Adapting legacy interpreters to evaluate v2.x logic introduces spatiotemporal drift, asynchronous event latencies, and artificial kinematic snapping. Addressing this execution gap, OSC2Runner introduces the first orchestration framework capable of natively mapping the OpenSCENARIO v2.x DSL to CARLA. The framework achieves this by formalizing scenario translation as a compilation pipeline through a multi-pass transpiler architecture. Bypassing static trajectory playback, the architecture synthesizes type-safe Abstract Syntax Trees directly into dynamic deterministic behavior trees (py_trees) natively mapped to CARLA's atomic APIs. Empirical validation in highly concurrent adversarial case studies demonstrates tick-by-tick determinism, exact spatial trigger evaluation, and 100.0 ms cross-actor blackboard synchronization. Kinematic analysis proves the strict adherence to continuous environmental boundaries. This architecture transitions Scenario-Based Testing from approximate behavioral interpretation to mathematically rigorous execution, establishing the deterministic backend required for co-simulation, hardware-in-the-loop testing, and automated LLM-driven generation pipelines.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。