As important as these sensing modalities may be, none of these critical sensor inputs matter if the sensors themselves are not reliable and if their output signals are not captured accurately to be fed upstream as high precision sensor data: the phrase “garbage in, garbage out,” has rarely held so much import.
To achieve this, even the most advanced analog signal chains must be continuously improved to detect, acquire, and digitize sensor signal outputs so that their accuracy and precision do not drift with time and temperature. With the right components and design best practices, the effects of notoriously difficult issues such as bias drift with temperature, phase noise, interference, and other instability-causing phenomena can be greatly mitigated. High precision/high quality data is fundamental to the ability of machine learning and AI processors to be properly trained and to make the right decisions when put into operation. And there are few second chances.
Once the data’s quality is assured, the various sensor fusion approaches and AI algorithms can respond optimally toward a positive outcome. It’s simply a fact that no matter how well an AI algorithm is trained, once the model is compiled and deployed on devices at the network edge, they are completely dependent upon reliable, high precision sensor data for their efficacy.
This interplay between the sensor modalities, sensor fusion, signal processing, and AI has profound effects upon both the advancement of smart, cognitive, autonomous vehicles and the confidence with which we can ensure the safety of drivers, passengers, and pedestrians. However, all is moot without highly reliable, accurate, high precision sensor information, which is so foundational to safe autonomous vehicles.
As with any advanced technology, the more we work on this, the more complex use cases are identified that need to be addressed. This complexity will continue to confound existing technology, so we need to look forward to next-generation sensors and sensor fusion algorithms to address these issues.
Like the original moonshot, there is an aspiration that the entire initiative of autonomous vehicles will have a transformative and long-lasting impact on society. Moving from driver assistance to driver replacement will not only improve the safety of transportation dramatically, but it will also lead to huge productivity increases. This future all rests on the sensor foundation upon which everything else is built.
Analog Devices has been involved in automotive safety and ADAS for the past 25 years. Now ADI is laying the groundwork for an autonomous tomorrow. Organized around centers of excellence in inertial navigation and monitoring and high performance radar and lidar, Analog Devices offers high performance sensor and signal/power chain solutions that will not only dramatically improve the performance of these systems, but also reduce the total cost of ownership of the entire platform—accelerating our pace into tomorrow.