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Uncertainty modeling and runtime verification for autonomous vehicles driving control: A machine learning-based approach

Journal Article · · Journal of Systems and Software
Not Available
Sponsoring Organization:
USDOE Office of Electricity (OE), Advanced Grid Research & Development. Power Systems Engineering Research
OSTI ID:
1702150
Journal Information:
Journal of Systems and Software, Journal Name: Journal of Systems and Software Journal Issue: C Vol. 167; ISSN 0164-1212
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

References (19)

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Statistical‐based approach for driving style recognition using Bayesian probability with kernel density estimation journal March 2018
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A survey of decision tree classifier methodology journal January 1991
Driver classification and driving style recognition using inertial sensors conference June 2013
Three Decades of Driver Assistance Systems: Review and Future Perspectives journal January 2014
Intelligent Transportation Systems journal March 2010
Driving Style Classification Using a Semisupervised Support Vector Machine journal October 2017
Semiautonomous Vehicular Control Using Driver Modeling journal December 2014
Verifying autonomous systems journal September 2013
Formal methods for semi-autonomous driving
  • Seshia, Sanjit A.; Sadigh, Dorsa; Sastry, S. Shankar
  • DAC '15: The 52nd Annual Design Automation Conference 2015, Proceedings of the 52nd Annual Design Automation Conference https://doi.org/10.1145/2744769.2747927
conference June 2015
A Support Vector Clustering Based Approach for Driving Style Classification [A Support Vector Clustering Based Approach for Driving Style Classification] journal June 2019

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