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Document type:
Konferenzbeitrag 
Author(s):
Tim Salzmann, Julian Thomas, Thomas Kühbeck, Jou-ching Sung, Sebastian Wagner, Alois Knoll 
Title:
Online Path Generation from Sensor Data for Highly Automated Driving Functions 
Abstract:
State-of-the-art autonomous driving systems rely on high precision map data. These map data are crucial to the driving function and therefore need to be validated during drive time. This work describes a probabilistic neural model inferring information about the road in front of an automated vehicle from sensory data. This problem is modeled as a pixel- wise classification problem. Thereby, the limitations of systems relying on pre-processed map data are overcome by replacing navigation related...    »
 
Dewey Decimal Classification:
000 Informatik, Wissen, Systeme 
Editor:
IEEE 
Book / Congress title:
Proceedings of the 22nd IEEE International Conference on Intelligent Transportation Systems 
Organization:
IEEE 
Date of publication:
27.10.2019 
Year:
2019 
Quarter:
4. Quartal 
Year / month:
2019-10 
Month:
Oct 
Reviewed:
ja