New computing technologies inspired by the brain promise fundamentally
different ways to process information with extreme energy efficiency and the
ability to handle the avalanche of unstructured and noisy data that we are
generating at an ever-increasing rate. To realise this promise requires a brave
and coordinated plan to bring together disparate research communities and to
provide them with the funding, focus and support needed. We have done this in
the past with digital technologies; we are in the process of doing it with
quantum technologies; can we now do it for brain-inspired computing?

新的计算技术如何应用于处理信息，提高计算的效率和处理海量数据能力，实现这个目标需要勇气和协作计划，将分散的研究社区聚集在一起，为其提供资金、支持和关注。

脑启发式计算：我们需要一个总体规划

Brain-inspired computing: We need a master plan

The recent proliferation of computing technologies (e.g., sensors, computer
vision, machine learning, and hardware acceleration), and the broad deployment
of communication mechanisms (e.g., DSRC, C-V2X, 5G) have pushed the horizon of
autonomous driving, which automates the decision and control of vehicles by
leveraging the perception results based on multiple sensors. The key to the
success of these autonomous systems is making a reliable decision in real-time
fashion. However, accidents and fatalities caused by early deployed autonomous
vehicles arise from time to time. The real traffic environment is too
complicated for current autonomous driving computing systems to understand and
handle. In this paper, we present state-of-the-art computing systems for
autonomous driving, including seven performance metrics and nine key
technologies, followed by twelve challenges to realize autonomous driving. We
hope this paper will gain attention from both the computing and automotive
communities and inspire more research in this direction.

本研究论文综述了自动驾驶的最新计算系统、性能指标、核心技术和挑战，并旨在吸引计算机和汽车领域的关注和更多研究。