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：主流自动驾驶汽车平台及测试基础设施均为专有闭源系统，因此难以评估安全关键型自动驾驶汽车的性能表现及其真实安全性。同样，当前鲜有平台支持多智能体协同分析这一迫切需求。为给传感器融合与协同分布式感知研究提供分析起点，我们基于AVstack设计了一套可访问的模块化感知平台，构建了协同分布式摄像头-雷达融合算法，并展示了一个涵盖自动驾驶数据集、物理仿真器及实体硬件设备的评估生态系统。该三位一体的生态系统支持测试当前开发平台难以实现的新一代配置方案。