CalAmp’s patent involves using machine learning to detect abnormal driving behavior through vehicle telematics data. The system calculates a driver risk score and can engage safety systems based on identified anomalies. This innovation aims to enhance vehicle safety by proactively addressing risky driving behaviors. GlobalData’s report on CalAmp gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on CalAmp, Vehicle fault diagnosis automation was a key innovation area identified from patents. CalAmp's grant share as of February 2024 was 83%. Grant share is based on the ratio of number of grants to total number of patents.
Vehicle safety system based on driver risk score
The granted patent (Publication Number: US11919523B2) discloses a method for engaging a vehicle safety system based on driver risk score and data received from a vehicle telematics device. The method involves identifying safety violations, generating safety control signals, and engaging safety systems such as reducing engine rotations, applying brakes, shifting gears, or even disabling the vehicle temporarily. Additionally, the safety system can instruct an autonomous driving system to take over and drive the vehicle to a safe location, or alert the driver through visual or audio cues of unsafe driving behavior.
Furthermore, the method includes disengaging the safety system once it has responded to the safety control signal, and utilizes machine learning processes to calculate driver risk scores based on anomalies in the telematics data. The safety violations are identified by comparing data to reference threshold values, which are dependent on the driver risk score. The method also allows for generating multiple safety control signals to engage different safety systems, confirming their responses through sensor data, and subsequently disengaging them once the response is confirmed. Overall, the patent outlines a comprehensive approach to enhancing vehicle safety through real-time monitoring and intervention based on driver behavior and risk assessment.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
