How can sensors provide high levels of redundancy to improve the safety and reliability of autonomous vehicles?
Autonomous transportation is transforming the world of logistics and Mobility as a Service (MaaS) by promising safer operation, increased efficiency, and reduced congestion. One of the major challenges in the adoption of autonomous driving technology is convincing people that it is safe – at least as safe if not safer than a human driver. In order to demonstrate the safety and reliability of the systems and sensors controlling the vehicle, high levels of redundancy are required to minimise levels of risk in the case of system failures.
Nearly all autonomous vehicles already make use of multi-modal sensors to provide a level of redundancy by covering the weaknesses or operational deficiencies of certain sensors with complimentary systems. For example, radar has long range capability and is less susceptible to adverse weather, but does not have enough information for object classification whereas LiDAR has a much larger number of data points and spatial resolution, but has more variable range limitations and can be affected by snow or fog. While it’s common to see multiple perception sensors like LiDAR, radar, and cameras mounted all around the outside of an autonomous vehicle, a less obvious sensor that forms a key part of the localisation solution is the Inertial Navigation System (INS).
An INS has built-in levels of redundancy just through the inherent design of having sensor fusion between GNSS and an IMU. Utilising a combination of accelerometers and gyroscopes to continuously measure the vehicle’s motion and integrating this with the absolute position updates from GNSS, the INS operates independently of external references making it a robust sensor choice.
The OxTS AV200 system in particular offers additional layers of redundancy above the inherent GNSS and IMU sensor fusion. It features a new “multi-core” IMU design that integrates multiple discrete 6-axis sensor modules instead of a traditional singular 6-axis block of three accelerometers and 3 gyroscopes. OxTS’ gx/ix tight-coupling technology also provides an alternative and redundant processing algorithm for the GNSS RTK engine for areas where GNSS is difficult to obtain. Providing even more localisation stability in traditionally troublesome areas for autonomous navigation. Finally, it’s able to integrate data from external sensors including LiDAR and cameras and combine those in the sensor fusion engine, again providing an enhanced and additional localisation solution compared to standalone perception-based localisation solutions.
The transformative potential of autonomous transportation hinges upon the adoption of advanced technologies. Inertial Navigation Systems have emerged as a linchpin in this revolution, delivering precise localisation, reliability in challenging environments, redundancy, and adaptability. As the autonomous transportation industry continues to evolve, safe and secure systems will pave the way for the era of autonomous transportation.
Iain Clarke is a Senior Product Engineer at Oxford Technical Solutions