General Motors has patented a system for human-machine teaching in vehicle operation. The system compares current status reporting modes to previous user preferences, suggests solutions, and implements actions based on user selections. This innovation aims to enhance user experience and vehicle performance. GlobalData’s report on General Motors gives a 360-degree view of the company including its patenting strategy. Buy the report here.
According to GlobalData’s company profile on General Motors, Reformer integrated fuel cells was a key innovation area identified from patents. General Motors's grant share as of February 2024 was 72%. Grant share is based on the ratio of number of grants to total number of patents.
System for human-machine teaching for vehicle operation
A recently granted patent (Publication Number: US11926334B1) discloses a system for human-machine teaching for vehicle operation. The system includes one or more processors and a computer-readable medium with executable instructions. These processors perform operations such as determining currently enabled status reporting modes on a vehicle interface, comparing them to previous users' modes, selecting a status reporting mode, reporting the operational status of the vehicle to the current user, providing suggestions based on previous users' solutions, and implementing a vehicle action based on the user's selection.
Furthermore, the system involves applying similarity metrics like k nearest neighbor (KNN) or Latent Dirichlet Allocation (LDA) to identify similar users and determine preference values for status reporting modes. It also generates expert-weighted solutions, ranks them, and presents suggestions to the user. The system can update reporting modes and suggestions based on manual feedback from the user. The patent also covers a computer program product and a computer-implemented method for human-machine teaching for vehicle operation, detailing similar processes and functionalities as the system described in the claims. Overall, the patent aims to enhance the interaction between users and vehicles by providing personalized teaching and operational guidance based on previous user data and feedback.
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