Leading autonomous vehicle (AV) platforms and testing infrastructures are, unfortunately, proprietary and closed-source. Thus, it is difficult to evaluate how well safety-critical AVs perform and how safe they truly are. Similarly, few platforms exist for much-needed multi-agent analysis. To provide a starting point for analysis of sensor fusion and collaborative & distributed sensing, we design an accessible, modular sensing platform with AVstack. We build collaborative and distributed camera-radar fusion algorithms and demonstrate an evaluation ecosystem of AV datasets, physics-based simulators, and hardware in the physical world. This three-part ecosystem enables testing next-generation configurations that are prohibitively challenging in existing development platforms.
翻译:领先的自动驾驶(AV)平台和测试基础设施可访问性较差,且是专有的和闭源的。因此,评估安全关键AV的性能以及它们的真实安全性是困难的。同样,缺乏用于多智能体分析的平台。为了提供传感器融合和协作和分布式传感分析的起点,我们使用AVstack设计了一个可访问,模块化的传感平台。我们构建了协作和分布式的摄像头 - 雷达融合算法,并展示了一个AV数据集,物理模拟器和物理世界硬件的评估生态系统。该三部分生态系统使得在现有开发平台中难以完成的下一代配置测试成为可能。