Raw Sensor Fusion: creating robust environmental model to address functional safety and enable autonomous driving

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Raw Sensor Fusion: creating robust environmental model to address functional safety and enable autonomous driving

Event: AutoSens Detroit

, 2020

L2 and L2+ are becoming mainstream and are implemented in many vehicles today. However, the switch to L3 and above is extremely problematic since the responsibility moves from the driver to the AV. This means that the AV MUST be safer than the human driver (and many would say at least X10 times safer). In order to meet these functional safety requirements, sensor fusion algorithms must become much more precise, reliable, robust, and with multiple redundancies. In order to achieve this, Raw Sensor Fusion methodology must be implemented. Unlike Object Level Fusion, Raw Sensor Fusion methodology can achieve much better precision, reduce false alarms, work with multiple sensor inputs and continue working even when some sensors degrade in performance or go completely offline.