Monitoring driving safety using semi-supervised sequential...

Details Monitoring driving safety using semi-supervised sequential... Monitoring driving safety using semi-supervised sequential...

2008-07-31

2010-12-28

Vincent, David R (Department: 2129)

Data processing: artificial intelligence

Machine learning

Reexamination Certificate

active

07860813

ABSTRACT:
A computer-implemented method and system for predicting operation risks of a vehicle. The method and system obtains a training data stream of vehicular dynamic parameters and logging crash time instances; partitions the data stream into units representing dimension vectors, labels the units that overlap the crash time instances as most dangerous; labels the units, which are furthest from the units that are labeled as most dangerous, as most safe; propagates the most dangerous and the most safe labeling information of the labeled units to units which are not labeled; estimates parameters of a danger-level function using the labeled and unlabeled units; and applies the danger-level function to an actual data stream of vehicular dynamic parameters to predict the operation risks of the vehicle.

REFERENCES:
patent: 6937994 (2005-08-01), Iyengar
patent: 7610130 (2009-10-01), Dixon et al.
patent: 2007/0219433 (2007-09-01), Stupp

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