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Sensor Fusion Makes Sense for Autonomous Vehicles

Image of Sensor Fusion for Self Driving Vehicles

Sensor Fusion for Self Driving Vehicles

The automotive industry remains divided on the sensor configuration needed to support autonomous driving. Tesla is resolute that cameras and radar systems will be sufficient, yet both systems have their shortcomings. Harman, a Samsung company believes safe automated and autonomous driving can only be achieved by combining LiDAR (Light Detection and Ranging), radar and cameras in a sensor fusion design.

Just Auto recently interviewed Robert Kempf, Harman’s vice president in ADAS/automated driving, on how it’s overcoming today’s LiDAR issues with recently-launched solid-state LiDAR technology and why the merging of this data in the ECU architecture is key to its success.

Appropriate sensor topology for autonomous driving is a highly debated topic. What is Harman’s current stance? 

There is much discussion and Harman is of the opinion that to support the quality and diversity of information required in automated and autonomous driving, a combination of LiDAR, radar and cameras is the optimum. Each offer advantages and disadvantages, so the successful fusion of the data sets provided by these sensors is imperative for a robust solution.

Can radar and cameras alone not be enough?

Both systems are hugely important for autonomous driving. However, there are limitations. Today’s automotive radar systems deliver their information selectively and with a small detection range. They are also vulnerable to disturbances by sensors of the same type so they could be severely hampered by other vehicles on the road as an example.

Meanwhile, cameras are hugely affected by a range of conditions. Lighting, weather such as rain, fog or snow, can disrupt performance. They are often not robust enough to provide the consistent and error-free detailed information needed for autonomous driving.

What are the challenges of LiDAR in its current form?

To date, LiDAR has been too complex and too expensive for mass-market use. Commercially-available LiDAR has relied on mechanically rotating components that are susceptible to vibration and shock. They also have limited resolution and range to deliver the quality data necessary, or are too large and expensive at the required performance level. Additionally, the more complex and sizeable the component, the harder it is to protect it from dust and moisture ingress. Large, fragile systems with high unit costs means typically, they aren’t viable for mass-market automotive use.

To overcome these issues, Harman’s partner Innoviz has developed solid-state LiDAR technology that was designed from the ground up specifically for automotive applications. InnovizOne solves the previous issues of LiDAR and provides the industry with a commercially-viable solution.

For the complete article click here.

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