Self validating reduction norton 360 some products not updating
The action of the vehicle is observed by a micro GPS system.
The quality is identified by a complex fuzzy-logic-based algorithm automatically.
We present an approach to acquire accurate 3D map data that can be used as ground truth and realistic 3D world models.
For safe autonomous vehicle products for all, validation on billions of kilometres is needed, thus using both massive and driver-in-the-loop simulation, with a large number of driving scenarios.
One of the main critical scenarios is the handover between manual and autonomous mode in different traffic situations.
Since sensors and systems in ADAS have achieved a sharp development curve, there is a high demand for test and validation to receive more attention in order to catch up.
Finally, we would like to discuss what steps need to be realised to bridge the gap between today’s ADAS test and validation and the expectation.
Multiple cognitive sensor sources in autonomous cars challenge the whole testing and validation scenario.