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Identification of Safety Regions in Vehicle Platooning via Machine Learning

Conference Paper
Publication Date:
2018
abstract:
The paper introduces the use of machine learning with rule generation to validate collision avoidance in vehicle platooning. Cooperative Adaptive Cruise Control is under test over a range of system parameters including speed and distance of the vehicles as well as packet error rate of the communication channel. Safety regions are evidenced on test data with statistical error very close to zero.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Vehicle platooning; Intelligible machine learning; Collision Prediction
List of contributors:
Mongelli, Maurizio; Muselli, Marco
Authors of the University:
MONGELLI MAURIZIO
MUSELLI MARCO
Handle:
https://iris.cnr.it/handle/20.500.14243/347180
Book title:
Proc. of WFCS 2018
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URL

https://www.dropbox.com/s/irbc7mdziv4jqnb/bare_conf.pdf?dl=0
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