Identification of Safety Regions in Vehicle Platooning via Machine Learning
Contributo in Atti di convegno
Data di Pubblicazione:
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.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Vehicle platooning; Intelligible machine learning; Collision Prediction
Elenco autori:
Mongelli, Maurizio; Muselli, Marco
Link alla scheda completa:
Titolo del libro:
Proc. of WFCS 2018