VAST：面向V2X/动态地图的自动驾驶系统验证工具链
VAST: V2X/Dynamic Map-Aware Autonomous Driving Systems Validation Toolchain
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- Saitama University（埼玉大学）
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中文总结 AI 辅助
VAST工具链通过解决互操作性问题，提升遮挡场景边缘案例发现率至80%，并利用动态地图将碰撞率降至40%，为协作式自动驾驶提供高效验证。
中文摘要 AI 辅助
在物联网到边缘到云连续体中的协作式自动驾驶需要在车辆、基础设施传感器、边缘侧动态地图服务和车载自动驾驶栈之间进行系统级验证。本文提出了VAST，一种面向V2X/动态地图的验证工具链，它连接了Scenic、Scenario Simulator v2、AWSIM、Autoware和SIM-LDM。VAST并未引入新的搜索算法；相反，它解决了互操作性挑战，包括Lanelet2到Scenic的映射、通过SS2进行的基于ROS 2的协同仿真、将动态地图对象注入Autoware，以及收集TTC、PET、碰撞、超时和性能测量数据。在遮挡交叉口场景中，兼容Lanelet2的约束采样将边缘案例发现率从40.0%提高到80.0%，并将每个发现边缘案例的平均时间从259.7秒减少到110.4秒。在相同的生成场景分布下，动态地图的可用性将碰撞率从78.0%降低到40.0%，并将非碰撞结果从22.0%提高到60.0%，且TTC/PET变化具有统计显著性。一项包含1-16个NPC的吞吐量研究表明，采样时间保持在0.1秒以下，而AWSIM/Autoware的执行和重启开销主导了运行时。这些结果使VAST成为协作式自动驾驶信息物理系统的一种实用验证基础设施。
英文摘要
Cooperative autonomous driving in the IoT-to-Edge-to-Cloud continuum requires system-level validation across vehicles, infrastructure sensors, edge-side Dynamic Map services, and in-vehicle autonomous-driving stacks. This paper presents VAST, a V2X/Dynamic Map-aware validation toolchain that connects Scenic, Scenario Simulator v2, AWSIM, Autoware, and SIM-LDM. VAST does not introduce a new search algorithm; instead, it addresses interoperability challenges, including Lanelet2-to-Scenic mapping, ROS 2-based co-simulation through SS2, Dynamic Map object injection into Autoware, and collection of TTC, PET, collision, timeout, and performance measurements. In occluded-intersection scenarios, Lanelet2-compatible constrained sampling increases the edge-case discovery rate from 40.0% to 80.0% and reduces the average time per discovered edge case from 259.7 s to 110.4 s. Under the same generated scenario distribution, Dynamic Map availability reduces the collision rate from 78.0% to 40.0% and increases non-collision outcomes from 22.0% to 60.0%, with statistically significant TTC/PET shifts. A throughput study with 1-16 NPCs shows that sampling remains below 0.1 s, whereas AWSIM/Autoware execution and restart overhead dominate runtime. These results position VAST as a practical validation infrastructure for cooperative autonomous-driving CPSs.
