Detecting and diagnosing anomalous driving behavior using driving behavior models

US11400944B2 · kind B2 · utility

Inventors

• Baharak Soltanian · Mountain View, US
• Divyansh Pal · Milpitas, US
• Enrique Israel Hernandez · San Jose, US
• Fangming YE · Nanhu, CN
• Fei Xiao · Mountain View, US
• Jian Wang · Burnaby, CA
• Xiao Liu · Menlo Park, US
• Yan Deng · Beijing, CN

Key dates

• Filing date: Jan 4, 2019
• Grant date: Aug 2, 2022
• Expiry date: Jan 4, 2039

Classification

• Technology area (CPC H): Electricity
• CPC primary: H04W4/90
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

Embodiments and examples are disclosed for intelligent vehicle diagnostics using driving behavior modeling and monitoring. For one example, a data processing system for a vehicle includes a plurality of sensors and a vehicle control unit (VCU). The VCU may sample the output from each of the plurality of sensors and assemble a dataset which may be transmitted to a cloud computing center. The cloud computing center may apply statistical machine learning algorithms to the dataset and training data to develop a model of a user's expected driving behavior. The cloud computing center may transmit the model to the vehicle, wherein the VCU may utilize the model to monitor the user's driving behavior. In response to detecting driving behavior that is anomalous to the expected driving behavior, the VCU may diagnose the cause of the anomalous behavior and take one or more preventative actions based on the diagnosis.