car-as-a-sensor: cooperative perception and learning for
TRANSCRIPT
Car-as-a-sensor: cooperative perception and learning for automated driving
Dr. Rainer Holve April 28th 2015
© Elektrobit (EB) 2015 2
How reliable are ADAS?
Car-as-a-sensor: cooperative perception and learning for automated driving
Car-as-a-sensor: cooperative perception and learning for automated driving
Current and future use of sensor data
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Car-as-a-sensor: cooperative perception and learning for automated driving
“Crowd sensing” and the sheer volume of data provide a far more precise picture of the road network
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Car-as-a-sensor: cooperative perception and learning for automated driving
Information generated by an ageing model is essential for automated driving vehicles
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Car-as-a-sensor: cooperative perception and learning for automated driving
Data Mining ensures reliable map data
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Accurate
Consistent
Up-to-date
Average
Car-as-a-sensor: cooperative perception and learning for automated driving
ADAS benefit from cloud map data
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Car-as-a-sensor: cooperative perception and learning for automated driving
Overall architecture as basis
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Car-as-a-sensor: cooperative perception and learning for automated driving
Self-learning systems: Higher degree of automation of the data processing system enables to exploit the full potential of sensor data
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Car-as-a-sensor: cooperative perception and learning for automated driving
Cloud map enrichment is a strong contributor for automated driving
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· Cloud map enrichment raises the quality of ADAS and supports driver´s acceptance and trust in technology, ADAS and automated driving
· Cloud map enriched data benefits from ADAS
· Cloud map enriched data contributes to ADAS
ADAS
