CPS: Synergy: Doing More With Less: Cost-Effective Infrastructure for Automotive Vision Capabilities

许多安全关键的网络物理系统依赖于先进的传感能力来应对不断变化的环境条件。一个这样的领域是汽车系统。在这个领域，自主功能（盲点警告、自动车道保持等）范围的扩大正在推动先进传感器技术的激增。这种扩展的限制是完全自主，这已经在各种一次性原型中得到了证明，但代价是大量的硬件过度配置，这对于消费产品来说是不可行的。为了使商用车的功能接近完全自动化，需要软件基础设施，使多个传感器处理流能够以合理的成本多路复用到一个通用的硬件平台上。 该项目旨在开发这样的基础设施。所需的基础设施将通过关注一个特别引人注目的挑战性问题来开发：实现经济高效的驾驶员辅助和自动控制汽车功能，通过摄像头实现基于视觉的传感。这个问题将通过以下方式来研究：（i）基于实际的汽车用例，以各种固定价格点检查众多基于多核的硬件配置，以及（ii）描述使用待开发的软件基础设施可以切实支持的基于视觉的工作负载范围。将进行的研究将是一个合作，涉及学术研究人员在通用汽车研究和工程师。这项工作的协作性质增加了所获得的结果将对美国汽车行业产生真实的影响的可能性。此外，该项目预计将产生新的开放源码软件和工具、新的课程内容、通过参与联合国开发计划署的演示方案进行的公共宣传以及调查人员在国家和国际论坛上的讲座和研讨会。

Many safety-critical cyber-physical systems rely on advanced sensing capabilities to react to changing environmental conditions. One such domain is automotive systems. In this domain, a proliferation of advanced sensor technology is being fueled by an expanding range of autonomous capabilities (blind spot warnings, automatic lane-keeping, etc.). The limit of this expansion is full autonomy, which has been demonstrated in various one-off prototypes, but at the expensive of significant hardware over-provisioning that is not tenable for a consumer product. To enable features approaching full autonomy in a commercial vehicle, software infrastructure will be required that enables multiple sensor-processing streams to be multiplexed onto a common hardware platform at reasonable cost. This project is directed at the development of such infrastructure.The desired infrastructure will be developed by focusing on a particularly compelling challenge problem: enabling cost-effective driver-assist and autonomous-control automotive features that utilize vision-based sensing through cameras. This problem will be studied by (i) examining numerous multicore-based hardware configurations at various fixed price points based on realistic automotive use cases, and by (ii) characterizing the range of vision-based workloads that can be feasibly supported using the software infrastructure to be developed. The research to be conducted will be a collaboration involving academic researchers at UNC and engineers at General Motors Research. The collaborative nature of this effort increases the likelihood that the results obtained will have real impact in the U.S. automotive industry. Additionally, this project is expected to produce new open-source software and tools, new course content, public outreach through participation in UNC's demo program, and lectures and seminars by the investigators at national and international forums.