Nissan Motor had 20 patents in artificial intelligence during Q1 2024. Nissan Motor Co Ltd filed a patent in Q1 2024 for a system that uses state-action history entries to generate parameters representing probabilities of similar operational scenarios in a vehicle transportation network. This model can be used to optimize operations and decision-making in similar scenarios. GlobalData’s report on Nissan Motor gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Nissan Motor grant share with artificial intelligence as a theme is 55% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Transfer learning with experience filter for vehicle operation (Patent ID: US20240067195A1)
The patent filed by Nissan Motor Co Ltd describes a method and apparatus for traversing a vehicle transportation network using state-action history entries stored in a database. These entries represent experienced operational scenarios associated with features, and a group of entries is determined based on the similarity of these features. A parameter is generated to represent the probability of similar operational scenarios, and a model is created based on this parameter for use in similar scenarios within the transportation network. The method involves transferring the model to multiple vehicles in a fleet, blocking entries based on feature differences, and utilizing a Partially Observable Markov Decision Process (POMDP) or a Markov Decision Process (MDP) to generate the model.
The apparatus includes a non-transitory computer-readable medium and a processor that executes instructions to determine state-action history entries, generate parameters and models based on similarities, and transfer the model to multiple vehicles in a fleet. The processor also collects state-action samples, determines features, and stores them in the database. The similarity of features is determined based on a threshold distance, and the model can be a deep reinforcement learning (DRL) model. Overall, the patent focuses on utilizing historical data to create models that can assist in navigating vehicle transportation networks efficiently and effectively.
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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.
