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Lane Departure Warning Mechanism of Limited False Alarm Rate Using Extreme Learning Residual Network and ϵ-Greedy LSTM
Neglecting the driver behavioral model in lane-departure-warning systems has taken over as the primary reason for false warnings in human–machine interfaces. We propose a machine learning-based mechanism to identify drivers’ unintended lane-departure behaviors, and simultaneously predict the possibi...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038345/ https://www.ncbi.nlm.nih.gov/pubmed/31979330 http://dx.doi.org/10.3390/s20030644 |