Disrupting the UK inertial sensor supply chain to increase resilience and safety for self-driving vehicles

零点运动（ZPM）开发超灵敏的芯片级设备来测量运动物体的加速度和旋转速率。这些惯性传感器的灵敏度比现有的车内传感器高100倍，因为我们使用光来代替嘈杂的电子读数，使我们的传感器能够测量更小的运动，而不会变得更大或更昂贵。我们的传感器可以提高无人驾驶汽车的性能、安全性和弹性，因为惯性传感器可以随时随地工作。目前，自主导航依赖于来自卫星（如GPS）、激光雷达/雷达或摄像头的外部参考信号。然而，所有这些外部参考输出数据的速率比惯性传感器低10-100倍，并且它们的信号可能被欺骗、阻塞或拒绝，例如，GPS在地下或隧道中不可用，并且是一个容易受到干扰的弱信号，而LIDAR/RADAR和相机需要巨大的计算处理能力来拼接图像，如果跟踪虚假目标或没有显著特征，则可能会失败。使用单一传感器解决方案，自动驾驶汽车无法达到5级完全自主，而是将多种输入融合在一起（传感器融合），例如LIDAR/RADAR和摄像头可以跟踪和避开障碍物，卫星导航提供相对于地球的绝对位置，惯性传感器可以测量汽车的动态。因此，改进惯性传感器对于保证可追溯的决策至关重要，因为它们提供的是测量结果，而不是“黑匣子”软件或人工智能/机器学习对静态激光雷达/雷达/相机数据的解释。为了准备我们的传感器进行汽车认证，我们将使用已知的标准包装实践来满足监管测试，并开始我们的质量保证流程，运行AEC-Q100认证定义的测试。我们的合作伙伴WAE将在赛车运动平台上进行测试，将我们的传感器暴露在现实世界的极端动态和条件下。为了验证惯性传感器在导航堆栈中的位置，以及与外部参考相比，它在安全或任务关键方面发挥的作用，我们的合作伙伴UWE将利用其在自动驾驶汽车上的专业知识，对其完整性和弹性进行独立研究。我们将与我们的合作伙伴皇家导航研究所合作，通过举办两场涉及自主导航学术和行业领导者的活动，确保我们的imu和UWE的研究在英国CAM硬件供应链中可见，并鼓励围绕传感器融合、安全、弹性和英国立场的主题进行辩论和讨论。这些活动是在感兴趣的利益相关者之间产生新见解和合作的机会。

Zero Point Motion (ZPM) develops ultra sensitive chipscale devices to measure acceleration and rate of rotation of moving objects. These inertial sensors are 100x more sensitive than existing ones inside cars today because we use light instead of a noisy electrical readout, enabling our sensors to measure smaller motions without becoming larger in size or more expensive. Our sensors can improve the performance, safety and resilience of driverless cars because inertial sensors work anywhere, anytime. Currently, autonomous navigation relies on external reference signals from satellites (e.g. GPS), LIDAR/RADAR or cameras. However, all these external references output data at 10-100x lower rates than inertial sensors, and their signals can be spoofed, jammed or denied, for example, GPS is not available underground or in tunnels and is a weak signal prone to interference, whereas LIDAR/RADAR and cameras require huge computational processing powers to stitch together images which can fail if false objects are tracked or if there are no prominent features.Autonomous vehicles cannot reach Level 5 full autonomy using a single sensor solution, but instead, a multitude of inputs that are fused together (sensor fusion) such that LIDAR/RADAR and cameras enable obstacle tracking and avoidance, satellite navigation provides an absolute position relative to the Earth, and inertial sensors measure the car dynamics. Improving the inertial sensors is therefore critical to guarantee traceable decision making, as they provide measurements and not 'black box' software or AI/machine learning interpretations of static LIDAR/RADAR/camera data.To prepare our sensors for automotive certification, we will use standard packaging practices known to satisfy regulatory testing and begin our quality assurance process, running tests defined by the AEC-Q100 certification. Our partner WAE will conduct testing on motorsport platforms, exposing our sensor to real-world extreme dynamics and conditions. To verify how the inertial sensor sits within the navigation stack and the safety or mission critical role it plays compared to external references, our partner UWE will conduct independent research on integrity and resilience using their expertise on autonomous vehicles. We will work with our partner the Royal Institute of Navigation to ensure our IMUs and UWE's research is visible to the UK CAM hardware supply chain by holding two events involving academic and industry leaders in autonomous navigation, and to encourage debate and discussion on topics around sensor fusion, safety, resilience and the UK's position. These events are opportunities to generate new insights and collaborations between interested stakeholders.